CN100399721C - Transmission method of orthogonal beam shaping in advance based on sending assistant selection of user's feedbacks - Google Patents

Abstract

The present invention discloses a data transmitting method for wireless networks. A system is firstly initialized and then the system sends signals according to cycles; in current sending cycle, the system selects partial users in the system to carry out feedback according to the feedback threshold gamma of a former sending cycle, and feedback users select sub-channels to increase code words and also feed back the increase of the code words to a sending end through a feedback channel. Users selecting feedback select the vector quantity of quantified pre-beams and feed back the vector quantity of quantified pre-beams together with the increase of code words in the sub-channel to the sending end. The sending end selects N < T > users among all users carrying out feedback according to a standard orthogonal design method to form N < T > signals for the selected users and to form main sending signals for the system. In the current sending cycle, the system is provided with a feedback threshold gamma and carries out broadcasting for all users by utilizing a system broadcasting channel for a next periodic system to select users.

Description

Orthogonal pre-beamforming transmission method based on sending auxiliary selection user feedback

Technical Field

The invention relates to a data transmission method of a wireless network, in particular to an orthogonal pre-beam forming transmission method based on sending auxiliary selection user feedback.

Background

Multiple Input Multiple Output (MIMO) technology can multiply the capacity and spectrum utilization of a wireless communication system without increasing bandwidth. It is widely recognized that mimo technology will have practical applications in next generation cellular networks, ad hoc networks, wireless local area networks, and broadband access networks. In the 90 s, AT & TBell laboratory scholars firstly complete the foundation-building work of the multiple-input multiple-output technology; after that, researchers such as Teladar, Foshinia, Tarokh and the like successively study the capacity, signal processing algorithm and space-time code of the MIMO system; wolniansky et al established a multiple input multiple output experimental system using the vertical-Bell labs layered space-time (V-BLAST) algorithm in 1998; more recently, standards such as IS-856, HSDPA, IEEE 802.11n, 802.16, and 802.20 have formally incorporated Multiple Input Multiple Output (MIMO) technology into their standards bodies or as a recommended technology.

At present, the research of a single-user multiple-input multiple-output system is mature, a great deal of work is on developing the research of a multi-user multiple-input multiple-output system, and the emphasis is on the aspects of multi-user signal processing and transmission methods.

The transmission method of the MIMO system can be divided into two types, the first type is a fixed transmission method, and can be divided into space diversity and space division multiplexing, the traditional space diversity method can effectively improve the link performance by utilizing a space-time coding technology, wherein, the orthogonal space-time block code is a type of space-time coding which has simple decoding and can obtain the full diversity order in the Rayleigh fading channel, but the application of the orthogonal space-time block code is limited by the number of antennas, and the orthogonal space-time block code cannot provide antenna array gain like other diversity technologies utilizing the channel state information; the traditional space division multiplexing method can obtain high spectrum efficiency by using different antennas to transmit independent sub-streams, and has lower complexity compared with space-time coding. Unfortunately, conventional spatial multiplexing is vulnerable to degradation of the rank-deficient channel state due to lack of spatial redundancy. These two techniques have obvious advantages, but cannot utilize channel state information, cannot adapt to the time-varying characteristics of the channel, and limit further improvement of system performance.

Aiming at the time-varying characteristic of a multi-input multi-output channel, a self-adaptive transmission method is introduced, a sending end carries out self-adaptive distribution on multi-dimensional wireless resources such as power, bits, space and the like according to channel state information, and the performance of a system can be effectively improved in a fading channel. The adaptive method has two parallel technologies, namely an adaptive modulation technology and a precoding technology. At present, the practicability and research result of the precoding technology of the mimo system exceed the adaptive modulation technology. For complexity reasons, there has been little research taking both of these techniques into account. In contrast, precoding optimization design by joint processing of transmission and reception has been intensively studied. The precoding optimization design allows the system to adaptively adjust the code words according to the channel state of the user, and better performance is obtained by maximizing the signal-to-interference ratio. In the study of precoding methods based on different criteria and linear receiving structures, the simplest techniques are mimo channel pre-beamforming and receive beamforming. The mimo pre-beamforming system transmits one data stream through a plurality of transmit antennas and combines received signals using a plurality of receive antennas to obtain superior transmission performance. Compared with the traditional space-time coding, under the assumption of complete channel state information, the transmitting end can select the optimal beam vector to obtain complete diversity gain and obvious antenna array gain.

Since the multi-user mimo system is limited by co-channel interference, the adaptive transmission strategy must be able to manage the interference between users effectively. The Dirty Paper Coding (DPC) performs interference avoidance by a sequential pre-subtraction method of user signals, and is an effective acquisition strategy for the capacity of a multiple-input multiple-output broadcast channel. However, as studied in many documents, DPC is a non-causal code transmission method and is complex and impractical. At present, a multi-user diversity method based on DPC technology is researched to a certain extent. The multi-user diversity can effectively resist channel fading in a multi-user packet switching wireless network, and can effectively approach the channel capacity through the optimal user selection, but the user selection method and the signal processing method still have higher complexity.

The huge capacity potential of mimo systems depends on the utilization of the full channel state, and likewise, the performance of the adaptive transmission method depends on the knowledge of the channel state. That is, in order to guarantee the performance of the transmission method, the transmitting end needs the receiving end to feed back the full channel state information. However, the increase of the number of antennas causes a rapid increase of the amount of channel state information, so that the feedback of the channel state becomes a heavy overhead of the system. Therefore, a limited feedback method for reducing the amount of feedback information becomes a research focus at present, and the research result will effectively promote the practical process of the mimo system.

In a multi-user system, there are two ideas for reducing the feedback information quantity: one is to reduce the amount of feedback information per user; another is to select user feedback. The second idea can be combined with a multi-user diversity method and is well applied to a non-real-time service system. Reducing the amount of channel information feedback while maintaining system performance at an acceptable level becomes a performance metric for a limited feedback approach.

Disclosure of Invention

The invention provides an orthogonal pre-beam forming transmission method capable of reducing feedback information amount and selecting user feedback based on transmission assistance.

The invention adopts the following technical scheme:

the first step is as follows: the system is initialized by adopting the following steps:

a. determining system user channel correlation matrix R according to channel physical parameters and system parameters, and further determining user channel state matrix H distribution function, H maximum characteristic sub-channel gain distribution function and statistical mean E [ H ] by R²]，

b. Counting the total number K of users in the cell, and calculating the normalized user number kl as K/N_T，N_TIn order to transmit the number of antennas,

c. setting the target feedback number Kn of system users as a transmitting antenna N_T6 to 10 times of the total weight of the composition,

d. giving an initial feedback threshold gamma required by the system to start working, and making the feedback threshold be E [ h²]，

e. The method for setting the pre-beam vector codebook required by constructing the transmission signal comprises the following steps:

a) the channel power degradation coefficient target value ζ due to quantization of the beam vector for a given system,

b) determining the number N of code words in a pre-beam vector codebook, wherein N is the minimum positive integer meeting the following two conditions:

firstly, ensuring that the power degradation coefficient is larger than a target value zeta, and enabling <math><mrow> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>=</mo> <mi>&zeta;</mi> <mo>/</mo> <mi>E</mi> <mo>[</mo> <msup> <mi>h</mi> <mn>2</mn> </msup> <mo>]</mo> </mrow></math> For normalizing power degradation coefficient target values, i.e. <math><mrow> <mi>N</mi> <mo>&GreaterEqual;</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msup> <mrow> <mo>(</mo> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>kl</mi> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> </mrow></math>

N is the number of transmitting antennas N_TAn integer multiple of the number of the first and second,

c) designing Nm groups of vector code words, Nm being N determined in step b) and the number of transmitting antennas N_TQuotient of (2), each group N_lThe vector code words are mutually orthogonal, and the specific process is as follows:

generating a sample H of the channel state matrix, and performing singular value decomposition H ═ A Λ B^HLet a first group N_TN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as B¹，

Generating another sample H of the channel state matrix, and carrying out singular value decomposition H ═ A Λ B^HIf B is^HB¹，B^HB²，…，B^HB^n-1All elements in (A) are between 1/Nm and 1-1/Nm in absolute value,

let N group N_lN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as Bⁿ. Otherwise, the sample H is regenerated,

thirdly, repeating the step two until Nth group N is generated_TThe code word group of the mutually orthogonal pre-beam vector code words is marked as B^Nm，

f. And constructing a subchannel gain increment codebook required by the transmitted signal, wherein the subchannel gain increment refers to a difference value obtained by subtracting a feedback threshold from the subchannel gain. The method for setting the subchannel gain increment codebook comprises the following steps:

a) determining the gain increment range of the sub-channel according to the gain distribution function of the H maximum characteristic sub-channel, and setting the gain increment range to be 0-Mh²For all greater than Mh²All gain increments of (1) are made Mh²，

b) The number M of the constant gain increment codebooks is the minimum positive integer which meets the following two conditions:

meeting the system requirement given by the system,

② the logarithm of M with base 2 is a positive integer,

c) for 0 to Mh²And (3) dividing the gain increment range, wherein the specific process is as follows:

is to 0-Mh²Normalizing the gain increment range to make the gain increment range be in a distribution range of 0-1,

secondly, compressing the gain increment value between 0 and 1 according to the A rate,

(iii) dividing the compressed gain increment value into M sections on average, and setting Δ ═ Δ { (Δ {)¹，Δ²，…Δ^M}，

Fourthly, coding the M intervals, wherein each log₂M binary numbers form a code word, and a gain increment codebook C ═ C is obtained corresponding to an interval¹，C²，…C^M}，

The second step is that: the system sends signals according to periods, and the signal construction method in each sending period is as follows:

a. in the current sending period, the system selects part of users in the system to feed back according to a feedback threshold gamma in the previous sending period, and the specific process is as follows:

after channel state estimation is completed at the receiving end for user K (K is 1, …, K is the total number of users in the system), singular value decomposition is performed on the channel matrix <math><mrow> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <msubsup> <mi>B</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Obtaining the maximum subchannel gain value h_k ²，

Secondly, all users with the maximum subchannel gain value more than or equal to the feedback threshold are selected as feedback users, the information is fed back to the sending end, the other users wait, the total number of the feedback users is set to be K',

b. the feedback user selects the subchannel gain increment code word and feeds the subchannel gain increment code word back to the sending end through the feedback channel, and the selection process of the subchannel gain increment code word is as follows:

t user K ' (K ' 1, …, K ') calculates the maximum subchannel gain value h_k′ ²The difference with the feedback threshold is set to,

determining the increment interval corresponding to the difference

Selecting the code word corresponding to the increment interval as the code word to be fed back by the user, and setting the code word as the code word to be fed back by the user

c. The user who selects feedback selects the quantized pre-beam vector, and feeds back the quantized pre-beam vector to the sending end through the feedback channel together with the subchannel gain increment code word, and the quantized pre-beam vector selection process is as follows:

the user K ' (K ' 1, …, K ') is decomposed according to the singular values of the channel <math><mrow> <msub> <mi>H</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <msub> <mi>A</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msub> <mi>&Sigma;</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>B</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> </mrow></math> Obtaining an optimal pre-beam

Vector b_k′，b_k′Is B_kThe first column of column vectors of (a),

② selecting quantized pre-beam vector codewords from the pre-beam vector codebook, i.e.

<math><mrow> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>k</mi> </msub> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mi>N</mi> </mrow> </munder> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> <mo>-</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>,</mo> </mrow></math>

d. The sending end selects N from all the users performing feedback according to a quasi-orthogonal design method_lThe specific process of each user is as follows:

measuringCalculating the maximum subchannel gain of user K ' (K ' is 1, …, K ') <math><mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>=</mo> <mi>&Gamma;</mi> <mo>+</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <msub> <mi>m</mi> <mi>k</mi> </msub> </msup> <mo>,</mo> </mrow></math>

Calculating the signal-to-noise ratio of the user k' receiving end <math><mrow> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>l</mi> </msub> <mo>)</mo> </mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>/</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>,</mo> </mrow></math>

Selecting the first user <math><mrow> <mi>use</mi> <mn>1</mn> <mo>=</mo> <mi>arg</mi> <munder> <mi>min</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </munder> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>,</mo> </mrow></math>

Selecting the kth user <math><mrow> <msup> <mi>usek</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mn>1</mn> <mo>,</mo> <mo>,</mo> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> Here, the <math><mrow> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>|</mo> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>i</mi> </msub> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>j</mi> </msub> </msup> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow></math>

Repeating step d until k ″, N_T，

e. Structure N_TThe signal of the selected user is first given to user k ″ (k ″ ═ 1, …, N_T) The pre-beam vector of <math><mrow> <msub> <mi>f</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> <mo>=</mo> <msqrt> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>l</mi> </msub> </msqrt> <msup> <mi>f</mi> <msub> <mi>n</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> </msup> <mo>,</mo> </mrow></math> Obtaining the signal f sent by user k ″_k″x_k″Where x_k″For the information symbol to be transmitted by the user,

f. constructing a total transmission signal of the system by directly superimposing N_TThe signal of the selected user is obtained, i.e. <math><mrow> <mi>Tx</mi> <mo>=</mo> <msub> <mi>f</mi> <mn>1</mn> </msub> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>f</mi> <mn>2</mn> </msub> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>+</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>+</mo> <msub> <mi>f</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <msub> <mi>x</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <mo>,</mo> </mrow></math>

g. In the current sending period, the system sets a feedback threshold value gamma, and broadcasts to all users by using a system broadcast channel so as to be used by the system to select the users in the next period, wherein the setting process of the feedback threshold value gamma is as follows:

calculating the gain average value h of all sub-channels of all feedback users in the current period²，

Calculating the maximum value and the difference value of K' and Kn, calculating the quotient of the difference value and the maximum value, multiplying the quotient by the gain average value of the sub-channel to obtain the adjustment step length of the feedback threshold,

and the next period feedback threshold is the current feedback threshold value minus the adjustment step length.

Compared with the prior art, the invention has the following advantages:

the invention effectively controls the number of feedback users by setting a self-adaptive feedback threshold to reduce the feedback quantity, quantizes the feedback information by designing an orthogonal beam vector codebook to further reduce the feedback information quantity, and simultaneously selects the final user and directly constructs the user signal by utilizing the vector codebook. Under the condition that the channel states of the users are subjected to independent same distribution and change rapidly, the method and the device simultaneously support the short-term fairness and the long-term fairness of the users.

1. Performance may approach the optimum, for example in suburban cellular propagation environments:

a) under the condition that the number of different users and the average signal-to-noise ratio SNR of the system are 20dB, the sum capacity obtained when the codebook N is 6 and the codebook N is 15 approaches the obtaining capacity of the method 1 quickly along with the increase of the number of users. This is because as the number of users increases, the vector codeword in the vector codebook approaches the optimal pre-beam vector of a part of users with an increasing probability, reducing the quantization error. For the same reason, the capacities obtained by the codebooks N-6 and N-15 tend to approach as the number of users increases.

b) Under the condition that different signal-to-noise ratios and the number of users K are 100, the three-antenna system has robustness on the channel state of the users due to the fact that the adaptive feedback threshold is set, and therefore with the increase of the signal-to-noise ratios, the acquired capacity of the three-antenna system and the method 1 keeps a small relatively fixed difference value.

c) Under the condition that the number of different users and the average signal-to-noise ratio SNR of the system are 20dB, the capacity acquired by the method quickly approaches to the method 1 along with the increase of the number of users. It can also be seen from the figure that when the codebook is set to N-8 and N-16, respectively, the obtained capacity is closer, and at the same time, the capacity is closer as the number of users increases. Therefore, when the number of users of the system is large, a codebook having N ═ 8 can be used.

d) The performance of the four-antenna system under different signal-to-noise ratios is very close to that of the method 3 and the method 1.

2. The feedback information quantity is small, the feedback information quantity can be greatly reduced by effectively controlling the feedback quantity of the user and simultaneously utilizing the orthogonally designed beam quantization codebook. The amount of information fed back by the system optimization method (method 1) is K × 2 × N_T ²X f (M), where f (M) is the channel gain feedback information amount, and the feedback information amount of the present invention (method 3) is Kn x log₂N×log₂M, Kn is much smaller than K, and method 3 has about 90% less feedback than method 1. For example, in the four-antenna system, when the number of feedback users is set to 30 and the capacity is reduced by less than 1 bit/s/Hz when the number of feedback users is set to 100 under the condition that the codebook N is 8, the feedback amount is reduced by 70%.

3. The transmitting signal has simple structure and is only N_TThe direct superposition of the user signals does not need the joint processing of the signals among the users, and simultaneously, the interference among the users can be effectively inhibited.

4. The invention comprises two user selection processes: the first process is to select users with subchannel gains larger than the feedback threshold by using the feedback threshold, and the process aims to select users with better subchannel quality and ensure the performance of user space diversity gain and array gain; the second process selects N by using a quasi-orthogonal design method_TThe user, the purpose of this process is to select the users with the best orthogonal characteristic among each other, and the orthogonal characteristic among the users is guaranteed. Gain and array due to space diversityThe column gain performance and the orthogonality performance among users are contradictory, so that the user diversity gain and array gain performance and the user orthogonality performance are compromised by two user selection processes in the invention, and the overall performance of the system is effectively ensured.

5. The feedback threshold of the system broadcast is adaptively changed according to the target feedback quantity of the users and the channel state information fed back by the users, and compared with the method for determining the fixed feedback threshold according to the long-term statistical characteristic of the system channel state, the method has robustness to the channel state change and ensures the performance of the method.

6. The codebook design method provided by the invention tries to maximize the minimum chordal distance between code groups by limiting the minimum value of the minimum inner product absolute value among the code words, thereby optimizing the performance of the codebook, and the design process is a circular search process. Meanwhile, the codebook design considers the correlation of the channel, is a universal design method, is irrelevant to the number of receiving antennas, and can flexibly design the codebook according to specific channel conditions.

Advantages 1 and 2 of the present invention consider three-and four-antenna systems in suburban cellular propagation environments, but its performance is not limited to the above propagation environments and three-and four-antenna multiple-input multiple-output systems. The invention can be conveniently applied to a MIMO-OFDM wireless transmission system.

Drawings

Figure 1 is a block diagram of a mimo system architecture for a pre-beamforming transmission method based on transmit-assisted selection of user feedback,

figure 2 is a flow chart of the method of the present invention,

figure 3 is a graph comparing the capacity and the number of different users of the three-antenna system,

figure 4 is a graph comparing the capacity and different signal-to-noise ratios of the three-antenna system,

figure 5 is a graph comparing the capacity and the number of different users of the four-antenna system,

figure 6 is a graph comparing the capacity and signal to noise ratio of the four antenna system,

fig. 7 is a graph showing the influence of different feedback user numbers and capacities of a four-antenna system.

Detailed Description

Example 1

The first step is as follows: the system is initialized by adopting the following steps:

a. determining system user channel correlation matrix R according to channel physical parameters and system parameters, and further determining user channel state matrix H distribution function, H maximum characteristic sub-channel gain distribution function and statistical mean E [ H ] by R²]，

b. Counting the total number K of users in the cell, and calculating the normalized user number kl as K/N_T，N_TIn order to transmit the number of antennas,

c. setting the target feedback number Kn of system users as a transmitting antenna N_T6 to 10 times of the total weight of the composition,

d. giving an initial feedback threshold gamma required by the system to start working, and making the feedback threshold be E [ h²]，

e. The method for setting the pre-beam vector codebook required by constructing the transmission signal comprises the following steps:

a) the channel power degradation coefficient target value ζ due to quantization of the beam vector for a given system,

b) determining the number N of code words in a pre-beam vector codebook, wherein N is the minimum positive integer meeting the following two conditions:

firstly, ensuring that the power degradation coefficient is larger than a target value zeta, and enabling <math><mrow> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>=</mo> <mi>&zeta;</mi> <mo>/</mo> <mi>E</mi> <mo>[</mo> <msup> <mi>h</mi> <mn>2</mn> </msup> <mo>]</mo> </mrow></math> For normalizing power degradation coefficient target values, i.e. <math><mrow> <mi>N</mi> <mo>&GreaterEqual;</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msup> <mrow> <mo>(</mo> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>kl</mi> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> </mrow></math>

N is the number of transmitting antennas N_TAn integer multiple of the number of the first and second,

c) designing Nm groups of vector code words, Nm being N determined in step b) and the number of transmitting antennas N_TQuotient of (2), each group N_TThe vector code words are mutually orthogonal, and the specific process is as follows:

generating a sample H of the channel state matrix, and performing singular value decomposition H ═ A Λ B^HLet a first group N_TN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as B¹，

Generating another sample H of the channel state matrix, and carrying out singular value decomposition H ═ A Λ B^HIf B is^HB¹，B^HB²，…，B^HB^n-1All the elements in the group are between 1/Nm and 1-1/Nm in absolute value, let the nth group N_lN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as Bⁿ. Otherwise, the sample H is regenerated,

thirdly, repeating the step two until Nth group N is generated_TThe code word group of the mutually orthogonal pre-beam vector code words is marked as B^Nm，

f. And constructing a subchannel gain increment codebook required by the transmitted signal, wherein the subchannel gain increment refers to a difference value obtained by subtracting a feedback threshold from the subchannel gain. The method for setting the subchannel gain increment codebook comprises the following steps:

a) determining the gain increment range of the sub-channel according to the gain distribution function of the H maximum characteristic sub-channel, and setting the gain increment range to be 0-Mh²For all greater than Mh²All gain increments of (1) are made Mh²，

b) The number M of the constant gain increment codebooks is the minimum positive integer which meets the following two conditions:

meeting the system requirement given by the system,

② the logarithm of M with base 2 is a positive integer,

c) for 0 to Mh²And (3) dividing the gain increment range, wherein the specific process is as follows:

is to 0-Mh²Normalizing the gain increment range to make the gain increment range be in a distribution range of 0-1,

secondly, compressing the gain increment value between 0 and 1 according to the A rate,

(iii) dividing the compressed gain increment value into M sections on average, and setting Δ ═ Δ { (Δ {)¹，Δ²，…Δ^M}，

Fourthly, coding the M intervals, wherein each log₂M binary numbers form a code word, and a gain increment codebook C ═ C is obtained corresponding to an interval¹，C²，…C^M}，

The second step is that: the system sends signals according to periods, and the signal construction method in each sending period is as follows:

a. in the current sending period, the system selects part of users in the system to feed back according to a feedback threshold gamma in the previous sending period, and the specific process is as follows:

after channel state estimation is completed at the receiving end for user K (K is 1, …, K is the total number of users in the system), singular value decomposition is performed on the channel matrix <math><mrow> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <msubsup> <mi>B</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Obtaining the maximum subchannel gain value h_k ²，

Secondly, all users with the maximum subchannel gain value more than or equal to the feedback threshold are selected as feedback users, the information is fed back to the sending end, the other users wait, the total number of the feedback users is set to be K',

b. the feedback user selects the subchannel gain increment code word and feeds the subchannel gain increment code word back to the sending end through the feedback channel, and the selection process of the subchannel gain increment code word is as follows:

t user K ' (K ' 1, …, K ') calculates the maximum subchannel gain value h_k′ ²The difference with the feedback threshold is set to,

determining the increment interval corresponding to the difference

Selecting the code word corresponding to the increment interval as the code word to be fed back by the user, and setting the code word as the code word to be fed back by the user

c. The user who selects feedback selects the quantized pre-beam vector, and feeds back the quantized pre-beam vector to the sending end through the feedback channel together with the subchannel gain increment code word, and the quantized pre-beam vector selection process is as follows:

the user K ' (K ' 1, …, K ') is decomposed according to the singular values of the channel <math><mrow> <msub> <mi>H</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <msub> <mi>A</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msub> <mi>&Sigma;</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>B</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> </mrow></math> Obtaining the optimal pre-beam vector b_k′，b_k′Is B_kThe first column of column vectors of (a),

② selecting quantized pre-beam vector codewords from the pre-beam vector codebook, i.e.

<math><mrow> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>k</mi> </msub> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>,</mo> <mi>N</mi> </mrow> </munder> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> <mo>-</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>,</mo> </mrow></math>

d. The sending end selects N from all the users performing feedback according to a quasi-orthogonal design method_lThe specific process of each user is as follows:

calculating the maximum subchannel gain of user K '(K' 1, …, K '), (K' K ═ K <math><mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>=</mo> <mi>&Gamma;</mi> <mo>+</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <msub> <mi>m</mi> <mi>k</mi> </msub> </msup> <mo>,</mo> </mrow></math>

Calculating the signal-to-noise ratio of the user k' receiving end <math><mrow> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>l</mi> </msub> <mo>)</mo> </mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>/</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>,</mo> </mrow></math>

Selecting the first user <math><mrow> <mi>use</mi> <mn>1</mn> <mo>=</mo> <mi>arg</mi> <munder> <mi>min</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </munder> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>,</mo> </mrow></math>

Selecting the kth user <math><mrow> <msup> <mi>usek</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mn>1</mn> <mo>,</mo> <msup> <mrow> <mo>,</mo> <mi>k</mi> </mrow> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> Here, the <math><mrow> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>|</mo> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>i</mi> </msub> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>j</mi> </msub> </msup> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow></math>

Repeating step d until k ″, N_T，

e. Structure N_TThe signal of the selected user is first given to user k ″ (k ″ ═ 1, …, N_T) The pre-beam vector of <math><mrow> <msub> <mi>f</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> <mo>=</mo> <msqrt> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> </msqrt> <msup> <mi>f</mi> <msub> <mi>n</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> </msup> <mo>,</mo> </mrow></math> Obtaining the signal f sent by user k ″_k″x_k″Where x_k″For the information symbol to be transmitted by the user,

f. constructing a total transmission signal of the system by directly superimposing N_TThe signal of the selected user is obtained, i.e. <math><mrow> <mi>Tx</mi> <mo>=</mo> <msub> <mi>f</mi> <mn>1</mn> </msub> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>f</mi> <mn>2</mn> </msub> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>+</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>+</mo> <msub> <mi>f</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <msub> <mi>x</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <mo>,</mo> </mrow></math>

g. In the current sending period, the system sets a feedback threshold value gamma, and broadcasts to all users by using a system broadcast channel so as to be used by the system to select the users in the next period, wherein the setting process of the feedback threshold value gamma is as follows:

calculating the gain average value h of all sub-channels of all feedback users in the current period²，

Calculating the maximum value and the difference value of K' and Kn, calculating the quotient of the difference value and the maximum value, multiplying the quotient by the gain average value of the sub-channel to obtain the adjustment step length of the feedback threshold,

and the next period feedback threshold is the current feedback threshold value minus the adjustment step length.

Example 2

The invention provides a simplified user selection method on the basis of multi-user diversity and pre-beam forming, avoids the signal processing of joint users, simultaneously selects user feedback through a transmission auxiliary strategy, effectively reduces the system feedback information quantity, provides the beam vector design and quantization strategy of a multi-user system, supports the effective transmission of a transmitting end signal through limited feedback,

the invention aims at the following broadcast channel model of a multiple input multiple output system: base station has N_TA transmitting antenna, wherein the system has K users distributed independently, and each user has N_kThe system signal model is as follows:

<math><mrow> <mi>y</mi> <mo>=</mo> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>y</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>y</mi> <mi>K</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>H</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>H</mi> <mi>K</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>[</mo> <msub> <mi>F</mi> <mn>1</mn> </msub> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <msub> <mrow> <mo>,</mo> <mi>F</mi> </mrow> <mi>K</mi> </msub> <mo>]</mo> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>x</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>x</mi> <mi>K</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>+</mo> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>n</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>n</mi> <mi>K</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow></math>

wherein,a signal is received for user k.

Is the channel matrix from the base station to user k,

for information sequences, x is satisfied_kx_k ^H～N(0，I)，

For precoding matrices, let Q_k＝F_kF_k ^HSatisfying a total power constraint for transmitting a covariance matrix <math><mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </msubsup> <mi>Tr</mi> <mrow> <mo>(</mo> <msub> <mi>Q</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>&le;</mo> <mi>P</mi> <mo>,</mo> </mrow></math> P is the total power of the transmitting end.

The receiving end independently and equally distributes and circularly and symmetrically forms complex Gaussian noise vectors which satisfy n_kn_k ^H～N(0，δ²I)。

The invention firstly solves the capacity domain and the sending covariance matrix of the user under the constraint conditions of multiple access channels and power by an iterative water injection method, because the optimal user selection strategy of the broadcast channel can be given.

Order multiple accessThe optimal transmission correlation matrix set of users in the channel is sigma_k}_k＝1 ^KThe solving process can be expressed as the following convex optimization problem:

<math><mrow> <mi>max</mi> <mi>imize</mi> <msub> <mi>log</mi> <mn>2</mn> </msub> <mo>|</mo> <mi>I</mi> <mo>+</mo> <msup> <mi>&delta;</mi> <mrow> <mo>-</mo> <mn>2</mn> </mrow> </msup> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msubsup> <mi>H</mi> <mi>k</mi> <mi>H</mi> </msubsup> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow></math>

s.t.Tr(∑_k)≤P_k， <math><mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msub> <mi>P</mi> <mi>k</mi> </msub> <mo>&le;</mo> <mi>P</mi> <mo>,</mo> </mrow></math> ∑_k≥0，k＝1，…，K

where P is_kPower allocated for user k. Order to <math><mrow> <msub> <mi>N</mi> <mi>k</mi> </msub> <mo>=</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mi>I</mi> <mo>+</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mi>j</mi> <mo>&NotEqual;</mo> <mi>k</mi> </mrow> <mi>K</mi> </munderover> <msubsup> <mi>H</mi> <mi>j</mi> <mi>H</mi> </msubsup> <msub> <mi>&Sigma;</mi> <mi>j</mi> </msub> <msub> <mi>H</mi> <mi>j</mi> </msub> </mrow></math> For the noise plus interference correlation matrix of user i, $W_k=H_k^H{N}_k^{-1}{H}_k$ for the equivalent channel correlation matrix of user k, for W_kPerforming SVD to obtain <math><mrow> <msub> <mi>W</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>U</mi> <mi>k</mi> </msub> <msub> <mi>&Delta;</mi> <mi>k</mi> </msub> <msubsup> <mi>U</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Note the book <math><mrow> <msub> <mi>&Delta;</mi> <mi>k</mi> </msub> <mo>=</mo> <mi>diag</mi> <mrow> <mo>(</mo> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mn>1</mn> </mrow> <mn>2</mn> </msubsup> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>,</mo> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <msub> <mi>N</mi> <mi>k</mi> </msub> </mrow> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> Then the optimum sigma_kThe expression is as follows:

<math><mrow> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>U</mi> <mi>k</mi> </msub> <msub> <mover> <mi>&Delta;</mi> <mo>~</mo> </mover> <mi>k</mi> </msub> <msubsup> <mi>U</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow></math>

here, the <math><mrow> <msub> <mover> <mi>&Delta;</mi> <mo>~</mo> </mover> <mi>k</mi> </msub> <mo>=</mo> <mi>diag</mi> <mrow> <mo>(</mo> <msup> <mrow> <mo>(</mo> <mi>&lambda;</mi> <mo>-</mo> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mn>1</mn> </mrow> <mrow> <mo>-</mo> <mn>2</mn> </mrow> </msubsup> <mo>)</mo> </mrow> <mo>+</mo> </msup> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <msup> <mrow> <mo>(</mo> <mi>&lambda;</mi> <mo>-</mo> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <msub> <mi>N</mi> <mi>k</mi> </msub> </mrow> <mrow> <mo>-</mo> <mn>2</mn> </mrow> </msubsup> <mo>)</mo> </mrow> <mo>+</mo> </msup> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> (x)⁺Max (x, 0), λ is the water injection level, satisfying the total power constraint. Further, let user k allocate power P_k＝Tr(∑_k). The process is sequentially executed from the user 1 to the user K, and then final optimization is carried out through multiple iterations to obtain an optimal solution { P }_k}_k＝1 ^KFinally according to sigma_k＝1 ^KP_kThe size relationship with P adjusts λ. Thereby giving a multiple access channel and capacity (equal to broadcast channel and capacity) calculation method.

Method 1

1. And (5) initializing. An appropriate lambda initial value and p initial value are given.

2. From user 1 to user K, assuming the state of other users is unchanged, the current user transmission correlation matrix is obtained by equation (3).

3. Repeating the step 2 until sigma_k}_k＝1 ^KConverge to a fixed value.

4. Is composed of { ∑_k}_k＝1 ^KCalculating { P_k}_k＝1 ^KIf, if <math><mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </msubsup> <msub> <mi>P</mi> <mi>k</mi> </msub> <mo>></mo> <mi>P</mi> <mo>,</mo> </mrow></math> λ is λ - ρ.

5. Repeating the steps 2 to 4 until <math><mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </msubsup> <msub> <mi>P</mi> <mi>k</mi> </msub> <mo>&le;</mo> <mi>P</mi> <mo>,</mo> </mrow></math> Obtaining the final solution { ∑_k}_k＝1 ^K。

Through duality and simple closed expression, the method can be represented by { ∑_k}_k＝1 ^KDirectly obtain { Q_k}_k＝1 ^K. Here, the present invention does not give { Q_k}_k＝1 ^KBecause the invention requires conclusions can be drawn by pairing { ∑ s_k}_k＝1 ^KThe analysis leads directly to two conclusions: first, most of sigma_k(corresponds to Q)_k) Is a zero matrix; the second is that the remaining non-zero matrix diagonal elements are substantially zero except for the first element.

Method 1 is based on a space division multiplexing method, i.e.

User can transmit N at a time_kA symbol. The above conclusion shows that in the practical multi-user mimo system, the user channels generally exhibit strong correlation and thus cannot support N_kTransmission of one symbol. The number of symbols which can be transmitted by the user k at each time is called the degree of freedom of the user and is recorded as L_k。N_TN may be provided for each transmit antenna_TSpatial degrees of freedom, which are competitively allocated among users according to a specific method, and N is maximally obtained by a user k_kOne degree of freedom, i.e. L_k＝N_k. If each user only occupies one degree of freedom, i.e. L_kAt most, the system can access N without interference_TAnd (4) users. For method 1, when the number of users K is relative to N_TWhen the method is large, the essence is that users participate in competition with optimal sub-channels, and the result is that each user usually only occupies one degree of freedom, and the result of the method 1 is consistent with the result of the beam forming method.

In addition, method 1 assumes that the transmitting end and the receiving end obtain complete channel state information from power control (multi-user power division)Distribution), the closed-loop power control method given by method 1 can obtain the optimal power distribution result by adopting the water filling method, but as a result, the power is distributed only in the optimal sub-channels of some users, and the result is close to the average distribution result. So method 1 can be modified to best N only among all users_TThe power is equally distributed among the sub-channels and then N is given_TThe performance of each sub-channel is inevitably close to that of the method 1 by performing the joint precoding optimization design.

But even for only N_TThe sub-channels are allocated with power, and the correction method still needs complete channel state information to carry out iterative precoding design, and the complexity is still high. Further analysis shows that the iterative precoding design is essentially to suppress the inter-user interference, and when the transmitting end does not have ideal channel state information, the inter-user interference cannot be effectively suppressed.

The invention provides a quasi-orthogonal transmission method based on pre-beam forming, which utilizes the natural (quasi-) orthogonal characteristic among users to design user signals, and is independently carried out based on each user without joint design, thereby effectively inhibiting the interference among the users and reducing the complexity of the method.

Precoding vector for user k

For the beamforming vector, f is given below_kThis is an important aspect and feature of the present invention. Since each user is assigned only one degree of freedom, it can only be assigned on the best sub-channel, looking first at the sub-channel of each user. To H_kPerforming SVD to obtain <math><mrow> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi>&Lambda;</mi> <mi>k</mi> </msub> <msubsup> <mi>B</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Let h_k＝maxdiag(∑_k)，h_kIs B_kA first column of column vectors defining an equivalent channel matrix for user k as h_kh_k。

The quasi-orthogonal design method provided by the invention is characterized in that N is selected by a specific method_TGroups having mutually (quasi-) orthogonal h_kDirectly order f_k＝h_k，k＝1，…N_T. Considering the data rate available to user k

$R_k={\mathrm{<figure-callout\; id="2"\; label="log"\; filenames="C20051003766600292.png"\; state="\{\{state\}\}">log</figure-callout>}}_2|I+Z_k^{-1}{H}_k{f}_k{f}_k^H{H}_k^H|---\left(4\right)$

Here, the <math><mrow> <msub> <mi>Z</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mi>k</mi> </mrow> </msub> <msub> <mi>H</mi> <mi>k</mi> </msub> <msub> <mi>f</mi> <mi>i</mi> </msub> <msubsup> <mi>f</mi> <mi>i</mi> <mi>H</mi> </msubsup> <msubsup> <mi>H</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>+</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mi>I</mi> <mo>.</mo> </mrow></math> Considering the linear receiving structure (which also ensures the lower complexity of the invention), let the user k receiving end equalization matrix be g_kLet g_kIs A_k ^HThe first row vector, then equation (4) can be rewritten as

<math><mrow> <msub> <mi>R</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>log</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mfrac> <mrow> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <msub> <mi>P</mi> <mi>avg</mi> </msub> </mrow> <mrow> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>+</mo> <msub> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mi>k</mi> </mrow> </msub> <msub> <mi>&eta;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <msub> <mi>P</mi> <mi>avg</mi> </msub> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> k＝1，…N_T (5)

Wherein P is_avg＝P/N_T； <math><mrow> <msub> <mi>&eta;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>|</mo> <msubsup> <mi>h</mi> <mi>k</mi> <mi>H</mi> </msubsup> <msub> <mi>h</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow></math> The degree of correlation can be characterized as the square of the absolute value of the inner product of the two beam vectors. User selection can be expressed as an optimization problem as follows

<math><mrow> <mi>max</mi> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>N</mi> <mi>i</mi> </msub> </msubsup> <msub> <mi>R</mi> <mi>k</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow></math>

s.t.k∈S

Wherein S is any N of the set of users {1, 2, … K }_TA dimension subset. Defining user k received signal-to-noise ratio as <math><mrow> <msub> <mi>SNR</mi> <mi>k</mi> </msub> <mo>=</mo> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <msub> <mi>P</mi> <mi>avg</mi> </msub> <mo>/</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>,</mo> </mrow></math> Then R is_kIs g_k＝1/SNR_k+∑_i≠k，η_k，iA function of (a) can be represented by g_kAnd (5) characterizing. (6) The formula is not a convex optimization problem, and a closed solution is difficult to obtain. The invention provides a user selection method, which can obtain an approximate solution of a formula (6).

Method 2

Step 1 is to select the first user, $\mathrm{<figure-callout\; id="1"\; label="use"\; filenames="C20051003766600281.png,C20051003766600282.png"\; state="\{\{state\}\}">use</figure-callout>}1=\mathrm{<figure-callout\; id="1"\; label="arg\; min\; i"\; filenames="C20051003766600281.png,C20051003766600282.png"\; state="\{\{state\}\}">arg</figure-callout>}\underset{i}{\min }\underset{}{}1/{\mathrm{SNR}}_i.$

step 2 is to select the user k and, <math><mrow> <mi>usek</mi> <mo>=</mo> <munder> <mi>arg</mi> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mn>1</mn> <mo>,</mo> </mrow> </munder> <munder> <mi>min</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>.</mo> </mrow></math>

step 3 repeat step 2 until N is completed_TAnd (4) selecting by a user.

In the user selection process, there is a contradiction between the orthogonality between the user signals and the diversity gain, i.e., ensuring the orthogonality of the user signals reduces the diversity gain, and ensuring the diversity gain of the user reduces the orthogonality between the user signals. Step 2 of method 2 compromises this conflict and effectively achieves overall performance.

In the above analysis process, the assumption that the sending end knows the channel state information is used. Method 1 is based on the full channel state assumption and method 2 is based on the partial channel state assumption (beam vector and maximum subchannel gain). Therefore, in order to implement the above method, the system needs all users to feed back channel state information to the transmitting end. Considering the feedback pi offset and cost of the actual system, feedback of the full channel state is generally not supported, and the method 2 is simpler than the method 1, not only in the method itself, but also in that less information needs to be fed back, so that the feedback overhead of the system can be reduced.

However, when the number K of users in the system is large, the system cannot bear even if each user feeds back only part of the channel state information. This requires a further reduction in the amount of feedback information. There are two solutions: firstly, feedback information is quantized; and secondly, selecting user feedback, namely only allowing part of users to feed back channel state information.

Considering that the feedback information required by method 2 is focused on the pre-beam vector and the maximum subchannel gain, the present invention will quantize it. Meanwhile, a method for selecting user feedback is invented on the basis of quantification, and the system feedback overhead can be further reduced.

The quantization method and the quantization based selection user feedback method are given below.

Since one of the features of the present invention is that each user uses the same codebook, only the quantization feedback problem of the beamforming method of the single-user mimo system is considered.

The beam vector quantization is to determine a vector codebook

And numbering the vector code words therein, the numbering being known and consistent to the transmitting end and the receiving end. The receiving end only needs to select a code word closest to the actual beam vector in the vector codebook and feed back the number of the code word, and the bit number required by the number is far smaller than the beam vector, so that the feedback information quantity can be reduced.

Assuming that the system has an error-free feedback link, the system signal transmission model shown in equation (1) is rewritten as

y＝Hfx+n (7)

SVD decomposition is carried out on H to obtain H ═ A Λ B^HLet us say the vector codebook

Wherein the selected beam vector is f, and the fed back beam vector $\sqrt{P}f=\sqrt{P}(b+\tilde{b}),$ B is the first column vector of B,

for quantizing the error vector, the equalization matrix is g is A^HH ═ maxdiag (Λ), then

$\hat{x}=\mathrm{gy}=\sqrt{P}\mathrm{hx}+\sqrt{P}h{b}^H\tilde{b}x+\mathrm{gn}---\left(8\right)$

Considering that n is an independent complex gaussian vector, the unit complex vector does not change its distribution for its rotation, so the interference variance due to quantization error is

$E{\left|\right|\sqrt{P}h{b}^H\tilde{b}x\left|\right|}^2={\mathrm{Ph}}^{2}E\left[\mathrm{Tr}\left(b^H\tilde{b}x{x}^H{\tilde{b}}^{H}b\right)\right]={\mathrm{Ph}}^{2}E{\left|\right|\tilde{b}\left|\right|}^2---\left(9\right)$

As can be seen from equation (9), the error variance due to the beam quantization depends on the euclidean norm of the quantization error vector, which also defines the channel power degradation coefficient as | Hb |_l ²-‖Hf‖_H ²Which satisfies

<math><mrow> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <mi>Hb</mi> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>-</mo> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <mi>Hf</mi> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>&le;</mo> <msup> <mi>h</mi> <mn>2</mn> </msup> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <msup> <mi>bb</mi> <mi>H</mi> </msup> <mo>-</mo> <msup> <mi>ff</mi> <mi>H</mi> </msup> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow></math>

Here, | |)_FRepresenting the Frobenius norm. Due to the fact that

And | | bb^H-ff^H‖_F ²Has the same monotonicity, so the interference variance can be also represented by | bb^H-ff^H‖_l ²And (5) characterizing. Thereby obtaining the vector codebook of the invention

Criteria for selecting a vector

$f=\underset{f^i,i=1,,N}{\arg \min }{\left|\right|{\mathrm{bb}}^H-f^i{\left(f^i\right)}^H\left|\right|}_l^2---\left(11\right)$

To provide a design method of a vector codebook, a statistical distribution condition of a channel state matrix H needs to be analyzed first. Setting the user channel matrix H as independent complex Gaussian variable and B as one right singular matrix in complex Gaussian random matrix, and selecting any one of the matrix

B and HB have the same distribution. Let f be a single-bit column vector of B for any

f and Hf have the same distribution.

f is in N_TDimensional complex vector spaceCan be expanded from f

One-dimensional subspace S of a space_fAll of them belong to

Subspace S spanned by vector f' of space_f′The set is called the complex Grassmannian space. Defining the chord distance of two subspaces of Grassmannian space as $d(S_{f^i},S_{f^j})=\sqrt{1-{\left|{\left(f^i\right)}^H{f}^j\right|}^2}.$ Because of using limited beam vectors

To construct all the subspaces of the Grassmannian space, a new definition needs to be given. Is defined by fⁱExtended packet is

Here, the <math><mrow> <mi>D</mi> <mo>=</mo> <munder> <mi>min</mi> <mrow> <mn>1</mn> <mo>&le;</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>&le;</mo> <mi>N</mi> </mrow> </munder> <mi>d</mi> <mrow> <mo>(</mo> <msub> <mi>S</mi> <msup> <mi>f</mi> <mi>i</mi> </msup> </msub> <mo>,</mo> <msub> <mi>S</mi> <msup> <mi>f</mi> <mi>j</mi> </msup> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> <math><mrow> <mi>D</mi> <mo>&le;</mo> <msqrt> <mfrac> <mrow> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>l</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mi>N</mi> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mrow> <mo>(</mo> <mi>N</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> </msqrt> <mo>.</mo> </mrow></math> Packet density defining the Grassmannian space ofWhere Ψ (-) is a normalized metric over the Grassmannian space, consisting of

Spatial haar metric introduction. When N is present_TWhen it is larger

While the upper bound of the formula (10) can be expressed approximately as

(12) Equation is a monotonic decreasing function of D, so minimizing the (12) equation boundary can be achieved by maximizing D with N fixed. The value of N can also be determined simply by equation (12) given the target value ζ of the power degradation coefficient of the channel. First, calculate the statistical mean value E [ h ] of the maximum sub-channel gain²]Obtaining a normalized power degradation coefficient value <math><mrow> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>=</mo> <mi>&zeta;</mi> <mo>/</mo> <mi>E</mi> <mo>[</mo> <msup> <mi>h</mi> <mn>2</mn> </msup> <mo>]</mo> <mo>,</mo> </mrow></math> Utilizing (1)2) The formula is obtained:

<math><mrow> <mi>N</mi> <mo>&GreaterEqual;</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>13</mn> <mo>)</mo> </mrow> </mrow></math>

the traditional vector quantization method for maximizing D does not consider the channel correlation and the orthogonality among vectors, but the core idea of the invention is that all users use the same codebook, and the final user selection depends on the orthogonality among the users, which is directly derived from the orthogonality among the vectors in the codebook. Meanwhile, considering the correlation of the mimo channel, and setting the channel correlation matrix as R, R should be considered in the codebook design.

(13) The formula is a single-user code word number constraint formula, and in a multi-user system, when the number K of users is large, the number N of code words in a codebook can be reduced, that is, N can be reduced along with the increase of the average number K of users in the system. Let kl equal K/N_lNormalizing the number of users for the system, then

This gives:

<math><mrow> <mi>N</mi> <mo>&GreaterEqual;</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msup> <mrow> <mo>(</mo> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>kl</mi> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <msub> <mrow> <mn>4</mn> <mi>N</mi> </mrow> <mi>T</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>14</mn> <mo>)</mo> </mrow> </mrow></math>

therefore, the invention provides a new codebook design method, which comprises the following steps

1. Determining a current channel correlation matrix R, and determining a distribution function of a channel state matrix H represented by R and a maximum subchannel gain statistical mean E [ H [ ]²]。

2. Determining the number N of the code words according to the target value zeta of the power degradation coefficient of the given channel and the number of the transmitting antennas, wherein N is the minimum positive integer meeting the following two conditions:

a) the number N of vector code words satisfies the formula (14)

b) Number N of vector codewords_TIs Nm ═ N/N_T。

3. Designing Nm groups of vector codewords, each group N_TThe vector codewords are orthogonal to each other, under the precondition that D is maximized.

a) One sample H of the channel state matrix is generated and singular value decomposition H ═ A Λ B is carried out^HLet a first group N_TN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as B¹。

b) Generating another sample H of the channel state matrix, and performing singular value decomposition H ═ A Λ B^HIf B is^HB¹，B^HB²，…，B^HB^n-1All elements in (A) are between 1/Nm and 1-1/Nm in absolute value,let N group N_lN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as Bⁿ. Otherwise, regenerating the sample H and re-executing b).

c) Repeating step b) until Nth group N is generated_TA pre-beam vector code word orthogonal to each other, the code word set being denoted as B^Nm。

In the codebook design method, the minimum value of the absolute value of the inner product of the vector code word is not less than 1/Nm, so that the D is indirectly maximized.

To further reduce the amount of feedback for a multi-user system, user feedback may be selected. One method is to determine a fixed decision threshold r based on the long-term statistical characteristics of the system channel, and feed back information when the channel gain of the user is greater than the threshold. This method has the disadvantage that the number of users that can not be fed back is effectively controlled (too many or too few), limiting the performance of the method.

The invention provides a method for selecting user feedback based on sending end assistant decision, which has the following basic idea: the sending end calculates channel gain statistical conditions such as mean value and the like according to the feedback information of all the feedback users last time, on the basis of the channel gain statistical conditions, the number Kn of the given target feedback users is combined, a judgment threshold gamma is determined, system broadcasting is carried out, and the users judge whether to feed back according to the threshold. The method can effectively control the number of feedback users by adaptively adjusting the decision threshold, thereby ensuring the performance of the method.

The self-adaptive adjustment of the decision threshold gamma means that the feedback threshold is continuously changed according to the performance requirement and the target value of the feedback user number. Setting the statistical mean value of the user feedback channel gain as h²The feedback threshold Γ then depends on h²And feeding back the number Kn of the user targets. The design steps of the feedback threshold gamma are as follows:

1. calculating the maximum value and the difference value of the current actual feedback user number Kf and the feedback user target number Kn, calculating the quotient of the difference value and the maximum value, and multiplying the quotient by the subchannel gain mean value h²Obtaining an adjustment step length DeltaGamma of the feedback threshold, i.e.

<math><mrow> <mi>&Delta;&Gamma;</mi> <mo>=</mo> <msup> <mover> <mi>h</mi> <mo>&OverBar;</mo> </mover> <mn>2</mn> </msup> <mfrac> <mrow> <mi>Kn</mi> <mo>-</mo> <mi>Kf</mi> </mrow> <mrow> <mi>max</mi> <mrow> <mo>(</mo> <mi>Kf</mi> <mo>,</mo> <mi>Kn</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>.</mo> </mrow></math>

2. The feedback threshold Γ is adjusted to Γ ═ Γ - Δ Γ.

In addition, in order to achieve acceptable performance requirements with a lower M-state quantization level, the present invention proposes a new subchannel gain quantization method based on a transmission-aided method. The idea is as follows: the user takes the feedback threshold given by the system as a base point, and adopts a similar delta modulation method to quantize the subchannel gain increment and encode the quantization state. The method for setting the subchannel gain increment codebook comprises the following steps:

1. determining the gain increment range of the sub-channel according to the gain distribution function of the H maximum characteristic sub-channel, and setting the gain increment range to be 0-Mh²For all greater than Mh²All gain increments of (1) are made Mh²。

2. Determining the number M of gain increment codebooks, wherein M is the minimum positive integer satisfying the following two conditions

a) And meets the system requirements given by the system.

b) The logarithm of M with the base 2 is a positive integer.

3. For 0 to Mh²The gain increment range is divided as follows

a) For 0 to Mh²Gain incrementAnd (4) normalizing the range to ensure that the range is in a distribution range of 0-1.

b) Compressing the gain increment value between 0 and 1 according to the A rate.

c) The compressed gain increment value is divided into M sections on average, and Δ ═ Δ { [ Δ ] }¹，Δ²，…Δ^M}。

d) The M intervals are encoded, per log₂M binary numbers form a code word, and a gain increment codebook C ═ C is obtained corresponding to an interval¹，C²，…C^M}。

The user k subchannel gain is quantized to one of the following mapping relations (with threshold Γ as base point):

<math><mrow> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <mo>-</mo> <mi>&Gamma;</mi> <mo>:</mo> <mo>&RightArrow;</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mi>m</mi> </msup> <mo>:</mo> <mo>&RightArrow;</mo> <msup> <mi>C</mi> <mi>m</mi> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>15</mn> <mo>)</mo> </mrow> </mrow></math>

represents h_k ²The difference of- Γ falls at Δ^mThe quantization interval of (2) is then quantized, i.e. the quantized code word is Δ^mCorresponding code word C^m. The incremental state progression M may be determined based on performance requirements.

The following provides a method for selecting user feedback pre-beamforming transmission based on the transmit-end aided decision.

Method 3

Step 1, a sending end broadcasts current judgment threshold information.

And 2, the system selects the user with the maximum subchannel gain not less than the feedback threshold to feed back.

And 3, selecting the beam vector code words by the selected users in the step 3 according to the formula (11), selecting the gain increment code words according to the formula (15), and feeding back the gain increment code words to the transmitting end.

Step 4 order <math><mrow> <msub> <mi>&eta;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>|</mo> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>k</mi> </msub> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>i</mi> </msub> </msup> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow></math>

And feeding back the pre-beam vector for the user k, and further performing user selection by the sending end according to the method 2.

Step 5 directly makes the precoding of the user selected in step 4 as $f_k=\sqrt{P/N_T}{f}^{n_k},$ k＝1，…，N_TSystem transmitting signal <math><mrow> <mi>Tx</mi> <mo>=</mo> <msub> <mi>f</mi> <mn>1</mn> </msub> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>f</mi> <mn>2</mn> </msub> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>+</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>+</mo> <msub> <mi>f</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <msub> <mi>x</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <mo>,</mo> </mrow></math> Wherein x_kIs the information symbol of user k.

Step 6, calculating the feedback threshold of the next sending period, namely calculating the subchannel gain average value h of all feedback users in the current period²And then calculating the maximum value and the difference value of the number of the actual feedback users and Kn, calculating the quotient of the difference value and the maximum value, and multiplying the quotient by the average value of the gain of the sub-channel to obtain the adjustment step length of the feedback threshold. The feedback threshold of the next period is the current feedback threshold value minus the adjustment step length.

Example 3

The structure block diagram of the transmission method of the multi-user mimo system proposed by the present invention is shown in fig. 1. Firstly, the system determines the feedback threshold of the system according to the information fed back by the user and the feedback quantity of the user target, and broadcasts to all users by using a system broadcast channel; after finishing channel state estimation, a user receiving end determines whether to feed back information according to a comparison result of a maximum sub-channel gain value and a feedback threshold; the selected user then selects an optimal pre-beam vector from the vector codebook, and the optimal pre-beam vector and the maximum subchannel gain increment quantization value are fed back to the sending end through a special feedback channel; then, the sending end selects users in all the users who carry out feedback according to a quasi-orthogonal design method; and finally, the sending end synthesizes the finally selected user signals and sends the user signals to each user through multiple antennas.

Consider a typical suburban cellular propagation environment. Assuming that the channel has Lp scattering clusters, the same cluster of scatterersThe sent paths have the same time delay, the channel matrixes of different clusters are not correlated, and the scatterer of the first cluster has the same average arrival angle theta_lThe actual angle of arrival is <math><mrow> <msub> <mi>&theta;</mi> <mi>l</mi> </msub> <mo>=</mo> <msub> <mover> <mi>&theta;</mi> <mo>&OverBar;</mo> </mover> <mi>l</mi> </msub> <mo>+</mo> <msub> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mi>l</mi> </msub> <mo>,</mo> <msub> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mi>l</mi> </msub> <mo>~</mo> <mi>N</mi> <mrow> <mo>(</mo> <mn>0</mn> <mo>,</mo> <msubsup> <mi>&delta;</mi> <mi>l</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> δ_lReferred to as small angle spread, path gain is g_l ². Theta of all clusters_lThe statistical variance Θ of (a) is called the large angle spread. Relative distance between base station antennas is delta d-d/lambda_w，λ_wIs the carrier wavelength, d is the physical antenna spacing, then the correlation matrix between the receiving antennas is defined as: <math><mrow> <msub> <mrow> <mo>[</mo> <msub> <mi>R</mi> <mi>l</mi> </msub> <mo>]</mo> </mrow> <mrow> <mi>a</mi> <mo>,</mo> <mi>b</mi> </mrow> </msub> <mo>=</mo> <msubsup> <mi>g</mi> <mi>l</mi> <mn>2</mn> </msubsup> <mo>&CenterDot;</mo> <msup> <mi>e</mi> <mrow> <mo>-</mo> <mi>j</mi> <mn>2</mn> <mi>&pi;</mi> <mrow> <mo>(</mo> <mi>b</mi> <mo>-</mo> <mi>a</mi> <mo>)</mo> </mrow> <mi>&Delta;</mi> <mi>d</mi> <mi>cos</mi> <mrow> <mo>(</mo> <msub> <mover> <mi>&theta;</mi> <mo>&OverBar;</mo> </mover> <mi>l</mi> </msub> <mo>)</mo> </mrow> </mrow> </msup> <mo>&CenterDot;</mo> <msup> <mi>e</mi> <mrow> <msup> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <mn>2</mn> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mn>2</mn> <mi>&pi;</mi> <mrow> <mo>(</mo> <mi>b</mi> <mo>-</mo> <mi>a</mi> <mo>)</mo> </mrow> <mi>&Delta;</mi> <mi>d</mi> <mi>sin</mi> <mrow> <mo>(</mo> <msub> <mover> <mi>&theta;</mi> <mo>&OverBar;</mo> </mover> <mi>l</mi> </msub> <mo>)</mo> </mrow> <msub> <mi>&delta;</mi> <mi>l</mi> </msub> <mo>)</mo> </mrow> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow> </msup> </mrow></math> a，b＝1，…，N_Tthe channel correlation matrix is <math><mrow> <mi>R</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>Lp</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>R</mi> <mi>l</mi> </msub> <mo>,</mo> </mrow></math> The channel matrix is <math><mrow> <mi>H</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>Lp</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msup> <msub> <mi>R</mi> <mi>l</mi> </msub> <mrow> <mn>1</mn> <mo>/</mo> <mn>2</mn> </mrow> </msup> <msub> <mi>H</mi> <mi>w</mi> </msub> <mo>,</mo> </mrow></math> $H_w{H}_w^H=I.$ Defining average SNR (signal-to-noise ratio) P/delta²。

The flow of the method of the present invention is shown in fig. 2, and the following steps executed in the flow chart are explained:

the first step is as follows: and (5) initializing.

1. A pre-beam vector codebook is determined.

a) The cell average total number K is estimated, for example, K equals 100.

b) Channel parameters: lp is 3, delta_l5 °, Θ is 180, and Δ d is 2. Calculating the statistical mean value E [ h ] of the gain of the maximum characteristic sub-channel²]E.g. E [ h ]²]＝3.5。

c) The power degradation coefficient target value ζ is set, and the normalized power degradation coefficient target value ζ is calculated, where ζ is 0.1, for example.

For three antennas N_TWhen N is 6, the vector codebook is obtained from equation (14) as follows (2 sets of orthogonal vectors, with the maximum inner product absolute value being 0.5):

to improve system performance, let N be 15, and vector codebook as follows (5 sets of orthogonal vectors, maximum inner product absolute value being 0.8142):

$\left\{\begin{array}{ccccccc}05772& -03048& -09067& 04632& 05195& -07307& 09007\\ {-02602-07644}_1& {-05614-02422}_1& {-01953+03493}_1& 06183-{05450}_1& 05907+{01167}_1& {-01298-05404}_1& {-01313+01728}_1\\ {01217+00075}_1& {-02040-07011}_1& {01283+00351}_1& {02524-02061}_1& {-06025+00685}_1& {-01845-03511}_1& 00765-03684_1\end{array}\right.$

$\left.\begin{array}{cccccccc}-03305& -0.5014& -07917& -03646& -03095& -02620& 07308& -03216\\ {01756-04668}_1& {04700-02583}_1& {00809-00233}_1& -{01517-01272}_1& {01709+07415}_1& {04545-06201}_1& -0069{4+01682}_1& {07549+02459}_1\\ {-06829-04191}_1& -{06605+01572}_1& {-06044+00301}_1& {05623+07153}_1& {04236-03817}_1& 04174+04075_1& {-06131+02385}_1& {05146+00364}_1\end{array}\right\}$

for four-antenna N_TWhen N is 16, the vector codebook is obtained from equation (14) as follows (4 sets of orthogonal vectors, with the maximum inner product absolute value being 0.7630):

$\left\{\begin{array}{cccccccc}-00086& -04842& 05093& -06467& 06318& 03595& 01910& 02896\\ {-01126+04923}_1& {-01395+05353}_1& {-02962+01331}_1& {06764+00828}_1& {-00195-06027}_1& {-05502-01734}_1& {00535+08512}_1& {02964+02878}_1\\ {05551-03246}_1& {03116+03732}_1& {02629-06912}_1& {01303+01217}_1& {-00109-02779}_1& {04852+02642}_1& {02979+02964}_1& {-2256+02483}_1\\ {-05757+00057}_1& {-04293+01969}_1& {-00640-02903}_1& {-02802+00842}_1& {-03761-01358}_1& {03089+03706}_1& {-00315+02418}_1& {03520+07153}_1\end{array}\right.$

$\left.\begin{array}{cccccccc}03135& -03516& -08314& -04877& -07088& 07160& 01140& 05114\\ {03302+01154}_1& {-02907-04790}_1& {-01466+02437}_1& -01648{-01385}_1& {01300-04921}_1& {00391+02139}_1& {01641-02435}_1& {05330-01889}_1\\ {00242+07097}_1& {03020-05726}_1& {02680-03431}_1& {-07955-00550}_1& {-00057+00701}_1& {01154-01614}_1& {02813+00887}_1& {-04673-00379}_1\\ {-03435+03963}_1& {-03785+00137}_1& {-01681-01003}_1& {02784-00496}_1& {-04802+00542}_1& {-06313-00462}_1& {-08878+01602}_1& {-02863-03420}_1\end{array}\right\}$

to further reduce the amount of feedback information, let N be 8, and the vector codebook be as follows (2 sets of orthogonal vectors, with maximum inner product absolute value being 0.5):

$\left\{\begin{array}{cccccccc}-00086& 05093& 06318& 01910& 03135& -08314& -07088& 01140\\ -01126+{04923}_1& {-02962+01331}_1& {-00195-06027}_1& {00535+08512}_1& {03302+01154}_1& {-01466+02437}_1& {01300-04921}_1& {01641-02435}_1\\ {05551-03246}_1& {02692-06912}_1& {-00109-02779}_1& {02979+02964}_1& {00242+07097}_1& {02680-03431}_1& {-00057+00701}_1& {02813+00887}_1\\ {-05757+00057}_1& {-00640-02903}_1& {-03761-01358}_1& {-00315+02418}_1& {-03435+0.3963}_1& {-01681-01003}_1& {-04802+00542}_1& {-08878+01602}_1\end{array}\right\}$

2. a maximum subchannel gain increment quantization level (M) is determined. With N_TFor example, M is 8 and the channel parameters are the same as above.

<math><mrow> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfenced open='{' close='}'> <mtable> <mtr> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>1</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>2</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>3</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>4</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>5</mn> </msup> <mi></mi> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>6</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>7</mn> </msup> </mtd> <mtd> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mn>8</mn> </msup> </mtd> </mtr> <mtr> <mtd> <mn>000</mn> </mtd> <mtd> <mn>001</mn> </mtd> <mtd> <mn>010</mn> </mtd> <mtd> <mn>011</mn> </mtd> <mtd> <mn>100</mn> </mtd> <mtd> <mn>101</mn> </mtd> <mtd> <mn>110</mn> </mtd> <mtd> <mn>111</mn> </mtd> </mtr> <mtr> <mtd> <mn>0.1</mn> </mtd> <mtd> <mn>0.2</mn> </mtd> <mtd> <mn>0.3</mn> </mtd> <mtd> <mn>0.4</mn> </mtd> <mtd> <mn>0.6</mn> </mtd> <mtd> <mn>1</mn> </mtd> <mtd> <mn>2</mn> </mtd> <mtd> <mn>3</mn> </mtd> </mtr> </mtable> </mfenced> </mrow></math>

C＝{000 001 010 011 100 101 110 111}

3. Setting an initial value of a feedback threshold gamma as a statistical mean value E [ h ] of the maximum subchannel gain of a channel²]。

4. Setting a feedback target value Kn (e.g. transmitting antenna N) of the selected user_TWhen 3, Kn is 20, N_TWhen 4, Kn is 30).

The second step is that: singular value decomposition of channel matrix by each user <math><mrow> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <msubsup> <mi>B</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Obtaining the maximum subchannel gain h_k ²And an optimal pre-beam vector b_k. E.g. in the number of transmitting antennas N_TUser 1 subchannel gain for 4 mimo systems $h_{}^{}$ ${}_1^2=2.6558,$ The optimal pre-beam vector is b₁＝[05272 -04817+02855₁ 00594 -01263₁ 03803-04945₁]^TThe subchannel gain of user 2 is ${\mathrm{<figure-callout\; id="1"\; label="h"\; filenames="C20051003766600281.png,C20051003766600282.png"\; state="\{\{state\}\}">h</figure-callout>}}_1^2=4.1632,$ The optimal pre-beam vector is b₁＝[03283 -03818+03123₁-01457-03202₁ -04055-06007₁]^T。

The third step: selecting a subchannel gain h_K ²And the users more than or equal to the feedback threshold gamma feed back. For example, if the current feedback threshold Γ is 3.5, user 2 is selected for feedback and user 1 waits.

The fourth step: selection of pre-beam vector codeword by selected user $f^{n_k}=\underset{f^i,i=1,,N}{\arg \min }{\left|\right|b_k{b}_k^H-f^i{\left(f^i\right)}^H\left|\right|}_F^2$ And incremental codebook selection <math><mrow> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <mo>-</mo> <mi>&Gamma;</mi> <mo>:</mo> <mo>&RightArrow;</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <mi>m</mi> </msup> <mo>:</mo> <mo>&RightArrow;</mo> <msup> <mi>C</mi> <mi>m</mi> </msup> <mo>,</mo> </mrow></math> E.g., the user 2 selected pre-beam vector codeword is $f^{n_2}={\left[\begin{array}{cccc}0.5093& -0.2962+0.1331i& 0.2629-0.6912i& -0.0640-0.2903i\end{array}\right]}^T,$ When N is 8, the vector codeword is numbered 001, and when N is 16, the vector codeword is numbered 0010. Gain increment of <math><mrow> <msubsup> <mi>h</mi> <mi>k</mi> <mn>2</mn> </msubsup> <mo>-</mo> <mi>&Gamma;</mi> <mo>=</mo> <mn>0.66</mn> <mo>,</mo> </mrow></math> The delta codeword selected is 100. Then, these codewords are fed back to the transmitting end together,

the fifth step: and the sending end performs user selection according to the feedback information obtained in the step five, and if 32 users feedback, N is selected from the 32 users_T4 users, i.e.

1. Selecting a first user $\mathrm{use}1=\arg \underset{i}{\min }1/{\mathrm{SNR}}_i,$ i is 1, …, 32, wherein, <math><mrow> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>P</mi> <mo>/</mo> <mn>4</mn> <mo>)</mo> </mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mi>i</mi> <mn>2</mn> </msubsup> <mo>/</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>,</mo> </mrow></math> here, the <math><mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <mn>1</mn> <mn>2</mn> </msubsup> <mo>=</mo> <mi>&Gamma;</mi> <mo>+</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <msub> <mi>m</mi> <mi>i</mi> </msub> </msup> <mo>=</mo> <mn>3.5</mn> <mo>+</mo> <mn>0.6</mn> <mo>=</mo> <mn>4.1</mn> <mo>.</mo> </mrow></math> P/δ²For the overall average signal-to-noise ratio of the system, values between 0dB and 20dB may be taken, for example.

2. The selection of the user k is performed by selecting, <math><mrow> <mi>usek</mi> <mo>=</mo> <munder> <mi>arg</mi> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mn>1</mn> </mrow> </munder> <munder> <mi>min</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> here, the <math><mrow> <msub> <mi>&eta;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>|</mo> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>k</mi> </msub> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>i</mi> </msub> </msup> <mo>|</mo> </mrow> <mn>2</mn> </msup> <mo>.</mo> </mrow></math>

3. Repeat step 2 until 4 user selections are completed.

And a sixth step: directly making the precoding of the user selected in the step six as $f_k=\sqrt{P/N_T}{f}^{n_k},$ k＝1，…，N_TFor example, if the information symbol to be transmitted by user 2 is x₂If 1+ i, the transmission signal of user 2 is $X_2=\sqrt{P/4}{f}^{n_2}{x}_2=\sqrt{P/4}{\left[\begin{array}{cccc}0.5093+0.5093i& -0.4293-0.1631i& 0.9541-0.4283i& 02263-03543i\end{array}\right]}^T,$ The system sends a signal of <math><mrow> <mi>Tx</mi> <mo>=</mo> <msub> <mi>f</mi> <mn>1</mn> </msub> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>f</mi> <mn>2</mn> </msub> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>+</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>+</mo> <msub> <mi>f</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <msub> <mi>x</mi> <msub> <mi>N</mi> <mi>T</mi> </msub> </msub> <mo>,</mo> </mrow></math> Wherein x_kIs the information symbol of user k.

The seventh step: in the current transmission period, the system sets a feedback threshold value gamma, and broadcasts to all users by using a system broadcast channel so as to allow the system to select the users in the next period. The feedback threshold value gamma is set as follows

1. MeterCalculating the average value h of the gain of the sub-channels of all feedback users in the current period²E.g. of <math><mrow> <msup> <mover> <mi>h</mi> <mo>&OverBar;</mo> </mover> <mn>2</mn> </msup> <mo>=</mo> <mn>3.5</mn> <mo>+</mo> <mfrac> <mn>1</mn> <mn>32</mn> </mfrac> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>32</mn> </munderover> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <msub> <mi>m</mi> <mi>i</mi> </msub> </msup> <mo>.</mo> </mrow></math>

2. Calculating the maximum value and the difference between the number of actual feedback users and Kn, calculating the quotient of the difference and the maximum value, and multiplying the quotient by the average value of the gain of the sub-channel to obtain the adjustment step length Deltagamma of the feedback threshold, for example <math><mrow> <mi>&Delta;&Gamma;</mi> <mo>=</mo> <mfrac> <mrow> <mn>32</mn> <mo>-</mo> <mn>30</mn> </mrow> <mn>32</mn> </mfrac> <msup> <mover> <mi>h</mi> <mo>&OverBar;</mo> </mover> <mn>2</mn> </msup> <mo>.</mo> </mrow></math>

3. The next period feedback threshold is the current feedback threshold value minus the adjustment step size, for example Γ ═ 3.5- Δ Γ.

Claims (1)

1. An orthogonal pre-beamforming transmission method based on transmission-assisted selection user feedback, characterized in that: the first step is as follows: the system is initialized by adopting the following steps:

a. determining system user channel correlation matrix R according to channel physical parameters and system parameters, and further determining user channel state matrix H distribution function, H maximum characteristic sub-channel gain distribution function and statistical mean E [ H ] by R²]，

b. Counting the total number K of system users, and calculating the normalized user number kl as K/N_I，N_IFor transmitting antennaThe number of the first and second groups is,

c. setting the target feedback number Kn of system users as a transmitting antenna N_T6 to 10 times of the total weight of the composition,

d. giving an initial feedback threshold gamma required by the system to start working, and enabling the initial feedback threshold to be E [ h²]，

e. The method for setting the pre-beam vector codebook required by constructing the transmission signal comprises the following steps:

a) the channel power degradation coefficient target value ζ due to quantization of the beam vector for a given system,

b) determining the number N of code words in a pre-beam vector codebook, wherein N is the minimum positive integer meeting the following two conditions:

firstly, ensuring that the power degradation coefficient is larger than a target value zeta, and enabling <math><mrow> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>=</mo> <mi>&zeta;</mi> <mo>/</mo> <mi>E</mi> <mo>[</mo> <msup> <mi>h</mi> <mn>2</mn> </msup> <mo>]</mo> </mrow></math> To normalize the power degradation system

Numerical scaling, i.e. <math><mrow> <mi>N</mi> <mo>&GreaterEqual;</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msup> <mrow> <mo>(</mo> <mover> <mi>&zeta;</mi> <mo>~</mo> </mover> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>kl</mi> </mrow> </msup> </mrow> <mrow> <msup> <mrow> <mo>(</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <mn>4</mn> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>)</mo> </mrow> <mrow> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mrow> <mo>(</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>/</mo> <mn>4</mn> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> </mrow></math>

N is the number of transmitting antennas N_TAn integer multiple of the number of the first and second,

c) designing Nm groups of vector code words, Nm being N determined in step b) and the number of transmitting antennas N_TQuotient of (2), each group N_TThe vector code words are mutually orthogonal, and the specific process is as follows:

generating a sample H of the channel state matrix, and performing singular value decomposition H ═ A Λ B^HLet a first group N_TN of B pre-beam vector code words respectively_TA column vector, the set of code words being denoted as B¹，

Generating another sample H of the channel state matrix, and carrying out singular value decomposition H ═ A Λ B^HIf B is^HB¹，B^HB²，…，B^HB^n-1All elements in (A) are between 1/Nm and 1-1/Nm in absolute value,

let N group N_TN of B pre-beam vector code words respectively_IA column vector, the set of code words being denoted as BⁿOtherwise, the sample H is regenerated,

thirdly, repeating the step two until Nth group N is generated_TA pre-beam vector code word orthogonal to each other, the code word set being denoted as B^Nm，

f. Setting a subchannel gain increment codebook required by constructing a sending signal, wherein the subchannel gain increment refers to a difference value obtained by subtracting a feedback threshold from subchannel gain, and the method for setting the subchannel gain increment codebook comprises the following steps:

a) determining the gain increment range of the sub-channel according to the gain distribution function of the H maximum characteristic sub-channel, and setting the gain increment range to be 0-Mh²For all greater than Mh²All gain increments of (1) are made Mh²，

b) The number M of the constant gain increment codebooks is the minimum positive integer which meets the following two conditions:

meeting the system requirement given by the system,

② the logarithm of M with base 2 is a positive integer,

c) for 0 to Mh²And (3) dividing the gain increment range, wherein the specific process is as follows:

is to 0-Mh²Normalizing the gain increment range to make the gain increment range be in a distribution range of 0-1,

secondly, compressing the gain increment value between 0 and 1 according to the A rate,

(iii) dividing the compressed gain increment value into M sections on average, and setting Δ ═ Δ { (Δ {)¹，Δ²，…，Δ^M}，

Fourthly, coding the M intervals, wherein each log₂M binary numbers form a code word, and a gain increment codebook C ═ C is obtained corresponding to an interval¹，C²，…，C^M}，

The second step is that: the system sends signals according to periods, and the signal construction method in each sending period is as follows:

a. in the current sending period, the system selects part of users in the system to feed back according to a feedback threshold gamma in the previous sending period, and the specific process is as follows:

after channel state estimation is completed at a receiving end, singular value decomposition is performed on a channel matrix <math><mrow> <msub> <mi>H</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi>&Sigma;</mi> <mi>k</mi> </msub> <msubsup> <mi>B</mi> <mi>k</mi> <mi>H</mi> </msubsup> <mo>,</mo> </mrow></math> Obtaining the maximum subchannel gain value h_k ²，

Secondly, all users with the maximum subchannel gain value more than or equal to the feedback threshold are selected as feedback users, the information is fed back to the sending end, the other users wait, the total number of the feedback users is set to be K',

b. the feedback user selects the subchannel gain increment code word and feeds the subchannel gain increment code word back to the sending end through the feedback channel, and the selection process of the subchannel gain increment code word is as follows:

t 'user K', where K 'is 1, …, K', the maximum subchannel gain value h is calculated_k′ ²The difference with the feedback threshold is set to,

determining the increment interval delta corresponding to the difference value^m _k，

Selecting the code word corresponding to the increment interval as the code word to be fed back by the user, and setting the code word as C^m _k，

c. The user selected for feedback selects the quantized pre-beam vector, and feeds the quantized pre-beam vector back to the transmitting end together with the subchannel gain increment code word through a feedback channel, wherein the quantized pre-beam vector selection process is as follows:

(ii) user K ', where K ' is 1, …, K ', decomposed according to channel singular values <math><mrow> <msub> <mi>H</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <msub> <mi>A</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msub> <mi>&Sigma;</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>B</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> </mrow></math> Obtaining the optimal pre-beam vector b_k′，b_k′Is B_kThe first column of column vectors of (a),

② selecting quantized pre-beam vector codewords from the pre-beam vector codebook, i.e.

<math><mrow> <msup> <mi>f</mi> <msub> <mi>n</mi> <mi>k</mi> </msub> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>,</mo> <mi>N</mi> </mrow> </munder> <msubsup> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <msubsup> <mi>b</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mi>H</mi> </msubsup> <mo>-</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <msup> <mrow> <mo>(</mo> <msup> <mi>f</mi> <mi>i</mi> </msup> <mo>)</mo> </mrow> <mi>H</mi> </msup> <mo>|</mo> <mo>|</mo> </mrow> <mi>F</mi> <mn>2</mn> </msubsup> <mo>,</mo> </mrow></math> f¹For the i-th vector codeword, f, in the pre-beam vector codebookⁿ _k’Feeding back a pre-beam vector for a user k';

d. the sending end selects N from all users performing feedback according to a quasi-orthogonal design method_TThe specific process of each user is as follows:

calculating the maximum subchannel gain of user k <math><mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>=</mo> <mi>&Gamma;</mi> <mrow> <mo>+</mo> <msup> <mover> <mi>&Delta;</mi> <mo>&OverBar;</mo> </mover> <msub> <mi>m</mi> <mi>k</mi> </msub> </msup> <mo>,</mo> </mrow> </mrow></math> Where K '═ 1, …, K',

calculating the signal-to-noise ratio of the user k' receiving end <math><mrow> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>T</mi> </msub> <mo>)</mo> </mrow> <msubsup> <mover> <mi>h</mi> <mo>~</mo> </mover> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> <mn>2</mn> </msubsup> <mo>/</mo> <msup> <mi>&delta;</mi> <mn>2</mn> </msup> <mo>,</mo> </mrow></math> P is the total power of the transmitting end, and delta is small-angle expansion;

selecting the first user <math><mrow> <mi>use</mi> <mn>1</mn> <mo>=</mo> <mi>arg</mi> <munder> <mi>min</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </munder> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <msup> <mi>k</mi> <mo>&prime;</mo> </msup> </msub> <mo>,</mo> </mrow></math>

Selecting the kth user <math><mrow> <mi>use</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mo>&NotEqual;</mo> <mn>1</mn> <mo>,</mo> <mo>,</mo> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>SNR</mi> <mi>i</mi> </msub> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>&eta;</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow></math> Where eta_j，i＝|(fⁿ _i)^Hfⁿ _j|²，

Repeating the step (iv) until k ″, N_T，

e. Structure N_TThe signal of the selected subscriber is first given to the subscriber k ", where k ═ 1, …, N_TThe pre-beam vector of <math><mrow> <msub> <mi>f</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> <mo>=</mo> <msqrt> <mi>P</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>I</mi> </msub> </msqrt> <msup> <mi>f</mi> <msub> <mi>n</mi> <msup> <mi>k</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msup> </msub> </msup> <mo>,</mo> </mrow></math> Obtaining the signal f sent by user k ″_k″x_k″Where x_k″Information to be communicated for a userThe number of the symbols is such that,

f. constructing a total transmission signal of the system by directly superimposing N_TThe signal of a selected subscriber, i.e. Tx ═ f₁x₁+f₂x₂+…+f_NTx_NT，

g. In the current sending period, the system sets a feedback threshold value gamma, and broadcasts to all users by using a system broadcast channel so as to be used by the system to select the users in the next period, wherein the setting process of the feedback threshold value gamma is as follows:

calculating the gain average value h of all sub-channels of all feedback users in the current period₂，

Calculating the maximum value and the difference value of K' and Kn, calculating the quotient of the difference value and the maximum value, multiplying the quotient by the gain average value of the sub-channel to obtain the adjustment step length of the feedback threshold,

and the next period feedback threshold is the current feedback threshold value minus the adjustment step length.

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