code.rar_csi_mimo检测_zf mimo_信道反馈

function [max_rate, B_opt, B_vector, rate_vector] = mud_vs_csi(T, Nt, SNR_dB, BFType, QuantizType, CQIType, SelectionMethod, MaxIter, BStart, BEnd) % [rate_vector, B_vector, max_rate, B_opt] = mud_vs_csi(T, Nt, SNR_dB, BFType, QuantizType, CQIType, SelectionMethod, MaxIter, BStart, BEnd) %% Input Arguments: % T - Total feedback budget in bits(返回总比特数) % Nt - Number of base station antennas(基站天线数) % SNR_dB - The system SNR in dB(信噪比dB) % BFType - The type of beamforming, can be '0-ZF', '1-PU2RC' or '2-SUBF'(波束成形类型) % QuantizType - The type of channel quantization used, can be '0-None', '1-RVQ', '2-QUB', or '3-Scalar' (ignored by PU2RC) % For perfect CSI, use 'None'(量化类型) % CQIType - The type of channel quality indicator used, can be '0-Norm' or '1-SINR' (ignored for PU2RC and SUBF) % SelectionMethod - The type of user selection employed can be '0-Greedy' or '1-Norm' (ignored by PU2RC and SUBF) % MaxIter - 【Optional】. Number of Monte-carlo iterations(defaults to 100)(蒙塔卡罗迭代次数) % BStart/BEnd - 【Optional】. Range of values of B to simulate, omit for automatic calculation (ignored if QuantizType is 'None') % %% Output Variables: % max_rate - The maximum optimized sum rate (bps/hz) % B_opt - The feedback load per user that maximizes the sum rate (bits) % B_vector - The values of feedback load per user corresponding to the rates in rate_vector (bits) % rate_vector - A vector with sum rate values for each per-user feedback load in B_vector (bps/hz) % % % Part of mud_vs_csi package. % % Reference: "Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels" % by Niranjay Ravindran and Nihar Jindal, Submitted to IEEE Transactions on Communications, 2009. % % Dependencies: quantiz_channels.m, user_selection_ZF_greedy.m, compute_pu2rc_rate.m %% Check input arguments if strcmpi(BFType, 'ZF') BFType = 0; %Zero-forcing elseif strcmpi(BFType, 'PU2RC'); BFType = 1; %RBF/PU2RC else BFType = 2; %Single-user beamforming，SUBF end if strcmpi(QuantizType, 'None') QuantizType = 0; %Perfect CSI elseif strcmpi(QuantizType, 'RVQ'); QuantizType = 1; %Random vector quantization elseif strcmpi(QuantizType, 'QUB'); QuantizType = 2; %Quantization upper bound else QuantizType = 3; %Scalar quantization end if strcmpi(CQIType, 'Norm') CQIType = 0; %channel norm else CQIType = 1; %SINR feedback end if strcmpi(SelectionMethod, 'Greedy') SelectionMethod = 0; else SelectionMethod = 1; %Selection of users with largest channel norms end if nargin < 8 %若未输入MaxIter值，默认为100 MaxIter = 100; %Use a larger number for smoother curves end %% Compute range of B values to simulate (automatically, if not specified) if BFType == 0 %ZF，根据用户向量决定B的范围,B=T./K if nargin < 10 %输入参数没有BStart,BEnd，用户向量的选取 K_vector = max(ceil(T/50), Nt):1:min(150, T); else %输入参数有BStart,BEnd，用户向量的选取 K_vector = unique(round(T./(BStart:BEnd))); %unique(a)：去掉a中的重复值，K=T/B end B_vector = T./K_vector; %B=T/K [dummy, indices] = unique(floor(B_vector));%indices为所选值得序号 K_vector = K_vector(indices); B_vector = B_vector(indices);%根据序号，决定所需的K向量与B向量 elseif BFType == 1 %PU2RC，根据B的范围决定用户向量,K=T./B if nargin < 10 B_vector = [log2(Nt):1:7+log2(Nt)];%B=log2(Nt)时为RBF，即码本中只有一个正交向量集 else B_vector = [BStart:1:BEnd]; end K_vector = ceil(T./B_vector); else %SUBF，根据用户向量决定B的范围，B=T./K if nargin < 10 K_vector = max(1, ceil(T/50)):1:min(200, T); else K_vector = unique(round(T./(BStart:BEnd))); end B_vector = T./K_vector; [dummy, indices] = unique(floor(B_vector)); K_vector = K_vector(indices); B_vector = B_vector(indices); end P = 10^(SNR_dB/10);%转换snr的单位,dB→比值 rate_vector = zeros(1, length(B_vector));%初始化rate_vector为全零向量 %% Display friendly status information %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% disp(['Feedback budget = ' num2str(T) ' bits, SNR = ' num2str(SNR_dB) ' dB, BS Antennas = ' num2str(Nt,'%02d') ', Beamforming type = ' num2str(BFType)]); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Compute rate vector for B_its = 1:length(B_vector); B = B_vector(B_its); K = ceil(K_vector(B_its)); regions = 2^B; if (QuantizType ==3 && BFType ~= 1 && B<2*2*(Nt-1) ) continue; %Too small a codebook for scalar quantization %如果if中条件为真，B_its=B_its+1，即执行下一个for循环，直到B的值满足【B>2*2*(Nt-1)】时，if条件为假，跳过continue，开始执行之后的语句 %continue功能为省略continue之后的循环语句，开始执行for/while循环的下一次循环 end rate_temp = 0; for its = 1:MaxIter %构建下行链路信道矩阵 H = 1/sqrt(2) * (randn(K, Nt) + i * randn(K, Nt)); %Downlink channels if BFType == 0 %ZF QuantH = quantiz_channels(H, regions, P, QuantizType, CQIType); rate_temp = rate_temp + user_selection_ZF_greedy(H, QuantH, P, SelectionMethod); elseif BFType == 1 %PU2RC NumBeams = Nt; NumOrthSets = ceil(2^(log2(regions)-log2(NumBeams)));%正交集数：2^(B-log2(Nt)) BFCodebook = zeros(Nt, NumBeams, NumOrthSets); for OrthSet = 1:NumOrthSets BFCodebook(:, :, OrthSet) = orth(randn(Nt, NumBeams) + i*randn(Nt, NumBeams));%构建BFCodebook，其中有NumOrthSets个正交集 end rate_temp = rate_temp + compute_pu2rc_rate(H, BFCodebook, P); else %SUBF QuantH = quantiz_channels(H, regions, P, QuantizType, 0);%CQIType=0 temp_rate = 0; for k = 1:K SNR_eff = abs(H(k, :)*QuantH(k, :)')^2/norm(QuantH(k, :))^2;%|hk*hQk'|/norm(hQk)^2 if log2(1 + P*SNR_eff) > temp_rate %找出temp_rate的最大值 temp_rate= log2(1 + P*SNR_eff); end end rate_temp = rate_temp + temp_rate; end end; %for MaxIter if QuantizType == 0 && BFType ~= 1 rate_vector = rate_temp/MaxIter; B_vector = inf; break; %Quit of perfect CSI simulation, no need to cycle through B_vector else rate_vector(B_its) = rate_temp/MaxIter; % Display friendly status information %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% disp([' Feedback load per user = ' num2str(floor(B),'%03d') ' bits, Users = ' num2str(K, '%03d') ', Sum Rate = ' num2str(rate_vector(B_its)) ' bps/hz']); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% end end %% Compute optimal B and throughput [max_rate B_opt] = max(rate_vector); B_opt = B_vector(B_opt) %__EOF__