CN101695008A - Multi-user multi-antenna two-stage limited feedback method - Google Patents

Abstract

A multi-user multi-antenna two-stage limited feedback method in the field of wireless transmission technology, comprising: a user terminal quantizes channel state information into channel quality information and obtains low-order channel direction information through a small-size codebook, and performs first-stage feedback; The base station selects the optimal user group as the scheduling user, and notifies the scheduling user to feed back the high-order channel direction information, and uses the low-order channel direction information as the precoding matrix to start sending data to the scheduling user; the scheduling user obtains the high-order Channel direction information, and the second stage of feedback, the base station calculates the optimized precoding matrix according to the high-order channel direction information fed back by the scheduling user, and sends data to the scheduling user according to the optimized precoding matrix. The invention has the characteristics of high transmission rate and low limited feedback, and can provide a specific implementation method for the limited feedback strategy of the cellular cell in the third generation, super third generation, fourth generation cellular mobile communication systems and the like.

Description

Two-stage finite feedback method for multi-user and multi-antenna

technical field

The invention relates to a method in the technical field of wireless transmission, in particular to a multi-user multi-antenna two-stage limited feedback method.

Background technique

The multi-antenna (MIMO) system can increase the channel capacity of the wireless communication system through multiple antennas at the transmitting end and the receiving end. In the MIMO broadcast channel, the base station transmits information to multiple single-antenna users simultaneously through multiple antennas. The transmission performance of a multi-user MIMO system is related to channel state information. When the base station can obtain complete channel information and the total power is constant, the total transmission rate of the system increases with the increase of the number of users to achieve multi-user diversity gain. However, when the base station has no channel state information, the system performance is comparable to the TDMA system. In the actual system, the information fed back by each user is limited, and the base station can only receive part of the channel state information, that is, the limited feedback system. The multi-user MIMO limited feedback scheme is based on linear precoding. Compared with nonlinear precoding (such as the optimal DPC technology), linear precoding is simpler in design, has less transmission performance loss, and is easier to implement in practical systems.

Linear precoding methods are divided into Orthogonal Random Beamforming (ORBF) and Zero-Forcing Beamforming (ZFBF). ORBF contains randomly generated groups of precoding vectors and transmits them to users with the largest SINR respectively. Therefore, each user does not need to feed back its own channel information, but only needs to feed back channel quality information (CQI): the largest SINR and channel direction information (CDI): corresponding to the optimal vector number. This scheme is widely used due to its simple steps. There are two feedback schemes based on ORBF technology: (1) Orthogonal Space Division Multiplexing (OSDMA): The base station transmits a random set of precoding vector groups to each user, and the user feeds back the maximum SINR and corresponding vector. Theory proves that the system can get multi-user diversity. (2) Selective Orthogonal Space Division Multiplexing (OSDMA-S): The base station randomly generates multiple sets of precoding vectors each time, and the user feeds back the maximum signal-to-interference and noise ratio (SINR) and the corresponding vector number, which increases the limited feedback amount but Improved transfer performance. In practice, Selective Orthogonal Space Division Multiplexing, also known as PU2RC, has become a 3GPP-LTE standard. When using ZFBF, the base station uses the feedback channel direction information and channel quality information to determine the channel vector, which is used for user scheduling and precoding matrix design of zero-forcing beamforming to eliminate inter-user interference. When there is complete channel state information, inter-user interference can be completely eliminated, and its performance is close to the optimal scheme. However, in order to make the system throughput continuously increase with the increase of SNR and avoid the ceiling effect, the feedback amount must have a linear relationship with the signal-to-noise ratio (SNR, in dB). There are two feedback schemes based on ZFBF: (1) Exhaustive method: select the user group with the same number of transmitting antennas each time, calculate the total transmission rate that can be achieved by using zero-forcing beamforming technology, and finally select the total transmission rate The user group with the highest rate is the best user group. (2) Zero-Forcing Orthogonal Space Division Multiplexing (ZF-OSDMA): After determining the user CSI, the base station selects the user with the optimal correlation coefficient and channel gain with each selected user through each iteration. In each iteration, Firstly, users whose correlation coefficient with the selected user group is greater than the threshold value are screened out from the user group to be selected, and then the user with the largest orthogonal component with the selected user group is selected to obtain the precoding matrix. This method takes into account the correlation between users and obtains the optimal user group after multiple iterations. Feedback resources for providing CSIT information using Orthogonal Random Beamforming (ORBF) and Zero-Forcing Beamforming (ZFBF) are only used once in scheduling and precoding vector design, although both can achieve multi-user diversity, but both have their own advantages. defect.

The complete limited feedback scheme is divided into two parts: user scheduling and precoding. The precoding vector of ORBF is determined in advance, but due to the small number of vectors, accurate user scheduling cannot be performed; the precoding vector of ZFBF is obtained by calculation. In order to reduce interference between users, each user must feed back more accurate channel direction information. Increased feedback volume. Therefore, it is necessary to find a more efficient limited feedback scheme.

After a literature search of the prior art, it was found that the "E-UTRA Precoding FeedbackOverhead" (E-UTRA precoding feedback mechanism) published by Motorolar on the proposal R1-072175 of the 49th meeting of 3GPP TSG RAN WG1 (May 2007) In , it is considered that the amount of feedback resources required for scheduling and precoding vector design is different. In the scheduling phase, all users need to feed back channel information, but the amount of feedback for each user is very small; on the contrary, in the precoding phase, only a small number of scheduled users need to feed back more accurate channel information. Therefore, it is entirely possible to divide the feedback resources into two stages and use them separately.

Contents of the invention

Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a multi-user multi-antenna two-stage limited feedback method. Through the two-stage limited feedback method, each user feeds back coarse quantized channel information in the first stage to help base station user scheduling. In the second stage, the base station requires the scheduled users to feed back the refined channel information to obtain the precoding vector. The invention improves the transmission rate and has low feedback amount and is easy to realize.

The present invention is achieved through the following technical solutions, and the present invention comprises the following steps:

Step 1: The base station sends a pilot signal to the user terminal, and the user terminal receives the pilot signal and channel state information;

The channel state information refers to a channel vector, and each element in the channel vector is a channel fading coefficient from the corresponding antenna of the base station to the antenna of the user terminal;

Step 2: The UE quantizes the channel state information into channel quality information and obtains low-order channel direction information through a small-size codebook, and performs the first-stage feedback to send the channel quality information and low-order channel direction information to the base station;

The channel quality information refers to the signal-to-interference-noise ratio calculated from the channel state information and the total transmission signal-to-noise ratio.

The number of codewords in the small-size codebook is 2 ³ -2 ⁴ .

The low-order channel direction information refers to the codeword sequence number that best matches the channel vector in the small-size codebook, wherein the low-order channel direction information uses a small-size codebook, and the channel quantization is rough, and the result uses the low-order channel direction Information ID.

Step 3: The base station performs user scheduling based on the channel quality information and low-order channel direction information fed back by users, selects the optimal user group as the scheduling user, and notifies the scheduling user to feed back the high-order channel direction information, and uses the low-order channel direction information as the pre-set Encoding matrix, start sending data to dispatching users;

The user scheduling refers to that the base station classifies all users according to the low-order channel direction information and selects the user with the largest channel quality information, and then groups the selected users, and selects the channel quality information and the largest user group;

The optimal user group refers to the user channel quality information and the largest user group in the group;

Step 4: The scheduling user obtains the high-order channel direction information from the large-size codebook, and performs the second-stage feedback, and sends the high-order channel direction information to the base station, and the base station calculates the optimized precoding according to the high-order channel direction information fed back by the scheduling user Matrix, and send data to the scheduling user according to the optimized precoding matrix;

The number of codewords in the large-size codebook is 2 ¹⁰ -2 ¹⁸ ;

The optimized precoding matrix refers to a pseudo-inverse matrix of high-order channel direction information of scheduling users.

The present invention divides the feedback resources into two stages, the first stage is used for user scheduling, and the second stage is used for precoding. Compared with existing schemes, this scheme effectively increases the throughput of the system while reducing the amount of feedback. Therefore, the scheme proposed by the present invention has the characteristics of high transmission rate and low limited feedback, and can be a limited feedback strategy for cells in systems such as third generation (3G), super third generation (S3G), and fourth generation (4G) cellular mobile communications. Provide specific implementation methods.

Description of drawings

Fig. 1 is a schematic diagram of the present invention.

Fig. 2 is a timing diagram of the embodiment.

Fig. 3 is a diagram illustrating an example of designing a codebook orthogonal codeword group.

Fig. 4 is a simulation diagram of transmission performance of different finite feedback schemes.

Detailed ways

The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

The system block diagram of the two-stage limited feedback scheme in the multi-user MIMO downlink involved in this embodiment is shown in FIG. 1 . The entire system consists of a multi-antenna base station, a single-antenna user terminal, an infinite channel, and a limited feedback channel. The multi-antenna base station contains M transmitting antennas. The base station receives the information fed back by the user through the limited feedback channel, performs user scheduling, and precodes the information to be sent by the scheduled user, and finally transmits it to the wireless channel through the antenna; K independent The user receives the information from the base station through the wireless channel, obtains the part he needs, and at the same time performs channel processing according to the information, quantizes the channel vector value and feeds it back to the base station through a limited feedback channel. The wireless channel and the finite feedback channel are independent of each other in the frequency domain.

The sequence of the entire process of this embodiment is shown in Figure 3, specifically including the following steps:

(1) The base station sends a pilot signal to the user end

The base station sends a pilot signal, which is known to the base station and the transmitting end when the pilot signal is offline, and is used for channel processing.

(2) The user end receives the pilot signal and processes the channel state information

Since the UE knows the pilot signal sent by the base station in advance, after receiving the pilot signal transmitted by the channel, the channel vector h _k ∈ □ ^1×M can be obtained through comparison and various channel processing methods, that is, the channel state information.

(3) The UE quantizes the channel state information into channel quality information and low-order channel direction information

The user end uses a small-sized codebook C based on the FFT matrix structure, and each codeword c _n is a row of an N×M FFT matrix,

$\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; =</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="c"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">c</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ <span\; class="notranslate">\; \&Center\; Dot;</span>\\ <span\; class="notranslate">\; \&Center\; Dot;</span>\\ <span\; class="notranslate">\; \&Center\; Dot;</span>\\ {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}\end{array}\right]<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\sqrt{\mathrm{<span\; class="notranslate">\; m</span>}}}\left[\begin{array}{cccc}{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& <span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span>& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}\\ {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& <span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span>& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}\\ <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>\\ <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>& <span\; class="notranslate">\; \&CenterDot;</span>& <span\; class="notranslate">\; \&Center\; Dot;</span>\\ {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}& <span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span>& {\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">e</figure-callout></span><figure-callout\; id="2"\; label="e\; j"\; filenames="H2009101975154E0000022.png"\; state="\{\{state\}\}">\; </figure-callout>}}^{\mathrm{<span\; class="notranslate">\; </span>}}\end{array}\right]<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In formula (1), let u=[u ₁ ... u _M ] be undetermined coefficients. The correlation coefficient between any two different codewords c _m and c _m' (m≠m') is |c _m c _m' ^H |. The codebook based on the FFT matrix structure can make the correlation coefficient between codewords very small by choosing an appropriate u, so that the codewords are evenly distributed in the vector space. During the simulation verification process, when N=8, u=[1235].

The low-order channel direction information fed back by the user is the codeword d _k with the largest cross-correlation coefficient with the channel vector h _k in the small-size codebook C,

${\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arg</span>}\underset{{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; C</span>}}{\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \backslash </span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

The channel quality information q _k fed back by the user is the processing value of the achievable transmission rate of user k. Since the scheduled user groups are orthogonal to the low-order channel direction information. When the number of scheduled users |S _opt |=M, these codewords constitute a set of complete orthogonal bases of M-dimensional vectors. User k ∈ S can reach the transmission rate processing value q _k to satisfy,

${\mathrm{<span\; class="notranslate">\; q</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; log</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; \&rho;</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&rho;</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; opt</span>}}<span\; class="notranslate">\; \backslash </span><span\; class="notranslate">\; \{</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; \}</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; log</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; \&rho;</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&rho;</span>}<span\; class="notranslate">\; (</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

(4) The UE feeds back channel quality information and low-order channel direction information to the base station

The user feeds back channel quality information and low-order channel direction information to the base station in time slot 1 through the uplink limited feedback channel. The uplink limited feedback channel and the downlink data transmission channel are separated in the frequency domain.

(5) The base station performs user scheduling based on the information fed back by users, and selects the optimal user group

即正交，两节点间连线。最后遍历搜索整个拓扑图，任意M个两两都连线的节点即为一组准正交码字组S_r(r＝1，…，R)。图3为码本大小N＝8，u＝[1235]时的码本拓扑图，其中准正交码字共4组，分别为：{1-2-5-6}，{2-3-6-7}，{3-4-7-8}，{4-5-8-1}。Since the small-sized codebook C is known, multiple sets of M mutually orthogonal codeword groups can be obtained in advance according to the codebook. The specific method is: make a topological graph of the codebook, with codewords as nodes, when the correlation coefficient between any codewords

Orthogonal, the connection between two nodes. Finally, the entire topology graph is traversed and searched, and any M nodes that are connected in pairs are a group of quasi-orthogonal codeword groups S _r (r=1, . . . , R). Fig. 3 is the codebook topological diagram when the codebook size N=8, u=[1235], wherein there are 4 groups of quasi-orthogonal codewords, respectively: {1-2-5-6}, {2-3- 6-7}, {3-4-7-8}, {4-5-8-1}.

即For user scheduling, first, the base station refers to the low-order channel direction information fed back by the user, and classifies the user into the quantization area represented by the corresponding codeword. Let the code word c _n represent the set of users in the quantization area as G _n . For each user k, according to the value of its low-order channel direction information d _k into

Right now

${\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; \{</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&ForAll;</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; K</span>}<span\; class="notranslate">\; \}</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

Secondly, for the user whose channel quality information q _k is the largest in the quantization region _Gn represented by each codeword, the remaining users are screened out. Let the user number selected in the quantization area _Gn represented by each codeword be v(n), then v(n) satisfies

$\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arg</span>}\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{\mathrm{<span\; class="notranslate">\; max</span>}}{\mathrm{<span\; class="notranslate">\; q</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

Finally, compare the processing value of the total transmission rate sum of the codeword corresponding to the user in each codeword group, that is, the sum of q _k , and the group of users with the largest value is the scheduled user group S _opt ,

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; opt</span>}}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; R</span>}}{\mathrm{<span\; class="notranslate">\; max</span>}}\underset{\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; q</span>}}_{\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

(6) The base station notifies the scheduled user to feed back the high-order channel direction information and start sending data

The base station notifies the user k∈S _opt to feed back high-order channel direction information for precise precoding design.

At the same time, since the low-order channel direction information of scheduling users intersects in pairs, it can be directly used as a precoding matrix. The base station temporarily uses this precoding matrix to transmit data for the scheduled users.

(7) The scheduled users obtain high-order channel direction information from the large-size codebook

In the precoding stage, a large-size codebook C _RVQ based on Random Vector Quantization (RVQ) is used. Each codeword in the codebook is independently randomly generated and obeys a complex Gaussian distribution vector. It is worth noting that using any purpose-designed codebook outperforms random vector quantization based codebooks.

The user uses a large-size codebook C _RVQ , the high-order channel direction information fed back, D _k is the codeword with the largest cross-correlation coefficient with the channel vector h _k in the codebook C _RVQ ,

${\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arg</span>}\underset{{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; RVQ</span>}}}{\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; /</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

(8) The scheduled user feeds back the high-order channel direction information D _k

The scheduled user feeds back the high-order channel direction information D _k to the base station in time slot 2 through the uplink limited feedback channel.

(9) The base station calculates a more accurate precoding matrix based on the scheduling user feedback

则预编码矩阵W满足，make

Then the precoding matrix W satisfies,

W＝H ^H (HH ^H ) ^-1 (8)

Due to the use of high-order channel direction information, W is more accurate than the precoding matrix in (6), which can better eliminate inter-user interference and increase system throughput.

(10) The base station sends information to the scheduling user

The base station transmits the data of scheduled users to the users through the downlink channel through the M transmitting antennas after precoding processing. When the next cycle begins, the above steps are repeated to ensure the normal operation of the base station and all users of the wireless cell.

Compared with the existing solutions, this embodiment effectively increases the throughput of the system while reducing the amount of feedback. These can be confirmed from simulations.

As shown in Fig. 4, the total transmission rate of various transmission strategies: two-stage limited feedback strategy, EU2RC is compared. Among them, the number of codewords N1 of the small-size codebook in the first stage of the two-stage limited feedback strategy is 8 (the first 8 codewords of the 4-antenna N=16 codebook using 3GPPTS 36.211 V8.30 Table 6.3.4.2.3-2), The value of the number N2 of the large-size codebook codewords in the second stage is 212, 214, 218 and inf (infinity, that is, the second-order channel direction information is ideal, and its value is equal to h _k /||h _k ||); The EU2RC (4-antenna N=16 codebook using 3GPP TS 36.211 V8.30 Table 6.3.4.2.3-2) codebook has 16 codewords. In the whole system, the number of antennas at the transmitting end is 4, the number of antennas at the user end is 1, and the signal-to-noise ratio at the transmitting end is P/N=10dB.

As the number of users increases, the system throughput of the three strategies also increases, realizing user diversity. The throughput of the two-stage limited feedback strategy increases continuously as the number of codewords in the second-stage codebook increases. Comparing the three strategies, the throughput of the system using the two-stage limited feedback strategy is greater.

Comparing the amount of feedback, in the first stage of the two-stage strategy, each user feeds back 3-bit low-order channel direction information, and in the second stage, only 4 users need to feed back 12-18-bit high-order channel direction information; while in EU2RC, each user must feed back 4-bit channel direction information information. Therefore, when the number of users is large (more than 100), the total feedback amount of the two-stage strategy is smaller.

Therefore, the two-stage limited feedback scheme in the multi-user MIMO downlink proposed in this embodiment is an optimization scheme, which effectively increases the throughput of the system while reducing the amount of feedback, and can provide a multi-user scheduling strategy for multi-antenna cells. Important basis and specific implementation methods.

Claims (9)

1. a multi-user multi-antenna two-stage limited feedback method is characterized in that, may further comprise the steps:

Step 1: the base station pilot signal transmitted is given user side, and user side receives pilot signal and channel condition information;

Step 2: user side is quantified as channel condition information channel quality information and obtains low order channel directional information by the small size code book, and carries out the phase I feedback, and channel quality information and low order channel directional information are sent to the base station;

Step 3: user's scheduling is carried out by channel quality information, the low order channel directional information of user feedback in the base station, choose optimal user group as dispatched users, and notice dispatched users feedback high-order channel directional information, and use low order channel directional information as pre-coding matrix, begin to send data to dispatched users;

Step 4: dispatched users obtains high-order channel directional information by the large scale code book, and carry out second stage and feed back, high-order channel directional information is sent to the base station, the base station calculates the optimization pre-coding matrix according to the high-order channel directional information of dispatched users feedback, and sends data to dispatched users according to optimizing pre-coding matrix.

2. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that described channel condition information refers to channel vector, and each element in this channel vector is the channel fading coefficient of base station respective antenna to the user side antenna.

3. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that, described channel quality information refers to by channel condition information and the letter that total transmission snr computation obtains and disturbs the ratio of making an uproar.

4. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that, described small size code book code word number is 2 ³-2 ⁴

5. multi-user multi-antenna two-stage limited feedback method according to claim 1, it is characterized in that, described low order channel directional information refers to the code word sequence number of mating most with channel vector in the small size code book, low order channel directional information is used the small size code book, with low order channel directional information sign.

6. multi-user multi-antenna two-stage limited feedback method according to claim 1, it is characterized in that, described user's scheduling refers to the base station is sorted out all users and therefrom choose the channel quality information maximum by low order channel directional information user, with the user grouping of choosing, therefrom choose channel quality information and maximum user's group again.

7. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that, described optimal user group refers to user channel quality information and maximum user's group in the group.

8. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that, described large scale code book code word number is 2 ¹⁰-2 ¹⁸Individual.

9. multi-user multi-antenna two-stage limited feedback method according to claim 1 is characterized in that, described optimization pre-coding matrix is meant: the pseudo inverse matrix of the high-order channel directional information of dispatched users.

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