MIMO.rar_简单MIMO

% Again we start by defining the common simulation parameters frmLen = 100; % frame length maxNumErrs = 300; % maximum number of errors maxNumPackets = 3000; % maximum number of packets EbNo = 0:2:12; % Eb/No varying to 12 dB 七个点 N = 2; % number of Tx antennas M = 2; % number of Rx antennas pLen = 8; % number of pilot symbols per frame W = hadamard(pLen); %阿达玛H = hadamard(n) returns the Hadamard matrix of order n N阶阿达玛矩阵H=[1 1;-1 1]通原 pilots = W(:, 1:N); % orthogonal set per transmit antenna正交集 hStr = RandStream('mt19937ar', 'Seed', 55408);%Create a local random stream to be used by random number generators for repeatability.作为MALAB %Create BPSK mod-demod objects P=2; %modulate order bpskmod = modem.pskmod('M', P, 'SymbolOrder', 'Gray');%产生一个调制器对象，进制数M为P，码元星座映射类型为灰度映射 bpskdemod = modem.pskdemod(bpskmod);%解调对象的值取自PSK %% % and set up the simulation. % Pre-allocate variables for speed tx2 = zeros(frmLen, N); r = zeros(pLen + frmLen, M); H = zeros(pLen + frmLen, N, M); H_e = zeros(frmLen, N, M); z_e = zeros(frmLen, M); z1_e = zeros(frmLen/N, M); z2_e = z1_e; BER22_e = zeros(1, length(EbNo)); %% % Set up a figure for visualizing BER results h=gcf; grid on; hold on; %Clear current figure window set(gca,'yscale','log','xlim',[EbNo(1), EbNo(end)],'ylim',[1e-4 1]); xlabel('Eb/No (dB)'); ylabel('BER'); set(h,'NumberTitle','off'); set(h,'Name','Orthogonal Space-Time Block Coding'); set(h, 'renderer', 'zbuffer'); title('G2-coded 2x2 System'); % Loop over several EbNo points for idx = 1:length(EbNo) %index索引 numPackets = 0; totNumErr22_e = 0; % Loop till the number of errors exceed 'maxNumErrs'直到超出最大误码数or the % maximum number of packets have been simulated for zct_i = 1:3000 if totNumErr22_e < maxNumErrs data = randi(hStr, [0 P-1], frmLen, 1); % data vector per user %randi产生均匀分布伪随机整数r = randi(s,[imin,imax],...)取值范围在imin imax之间，randi使那些值取自s % per channel tx = modulate(bpskmod, data); % BPSK modulation % Alamouti Space-Time Block Encoder, G2, full rate % G2 = [s1 s2; -s2* s1*] s1 = tx(1:N:end); s2 = tx(2:N:end); tx2(1:N:end, :) = [s1 s2]; tx2(2:N:end, :) = [-conj(s2) conj(s1)]; % Prepend pilot symbols for each frame transmit = [pilots; tx2];%分号表不同行 调制编码后加入导频符号，频域数据加导频 基于空频域的导频结构 %参课本P21MIMO多天线。。。 %平坦瑞利衰落信道移动台接收到的信号为g（t）=gc(t)+jgs(t);当入射波数N比较大时，gc(t)gs(t)近似高斯分布 % Create the Rayleigh distributed channel response matrix H(1, :, :) = (randn(hStr, N, M) + 1i*randn(hStr, N, M))/sqrt(2);%a =randn(),H(1,:,:)=[a+ia]/sqrt(2)]很有可能为正弦叠加法的Jakes模型 %sqrt(1/2)是用来将能量进行归一化的。因为实部和虚部都是方差为1的高斯变量，其模就是sqrt(2)了。 % assume held constant for the whole frame and pilot symbols保持为常数 H = H(ones(pLen + frmLen, 1), :, :); % Received signal for each Rx antenna % with pilot symbols transmitted for i = 1:M % with normalized（ 归一化） Tx power r(:, i) = awgn(sum(H(:, :, i).*transmit, 2)/sqrt(N), ... EbNo(idx), 0, hStr); end % Channel Estimation % For each link => N*M estimates for n = 1:N %设置一帧中的第一时隙中H的值 H_e(1, n, :) = (r(1:pLen, :).' * pilots(:, n))./pLen; end % assume held constant for the whole frame H_e = H_e(ones(frmLen, 1), :, :); % Combiner合成器 using estimated channel %用信道估计得到的H的估计值用于解码，使解码更精确 heidx = 1:N:length(H_e); for i = 1:M z1_e(:, i) = r(pLen+1:N:end, i).* conj(H_e(heidx, 1, i)) + ... conj(r(pLen+2:N:end, i)).* H_e(heidx, 2, i); z2_e(:, i) = r(pLen+1:N:end, i).* conj(H_e(heidx, 2, i)) - ... conj(r(pLen+2:N:end, i)).* H_e(heidx, 1, i); end z_e(1:N:end, :) = z1_e; z_e(2:N:end, :) = z2_e; % ML Detector (minimum Euclidean distance) demod22_e = demodulate(bpskdemod, sum(z_e, 2)); % estimated % Determine errors numPackets = numPackets + 1; totNumErr22_e = totNumErr22_e + biterr(demod22_e, data); end end % end of FOR loop for numPacket % Calculate BER for current idx % for estimated channel BER22_e(idx) = totNumErr22_e/(numPackets*frmLen); % Plot results semilogy(EbNo(1:idx), BER22_e(1:idx), 'ro'); legend(['Channel estimated with ' num2str(pLen) ' pilot symbols/frame']); drawnow; end % end of for loop for EbNo % Perform curve曲线 fitting and replot the results fitBER22_e = berfit(EbNo, BER22_e); semilogy(EbNo, fitBER22_e, 'r'); hold off;%曲线倾斜度表示分集增益