MIMO是如何实现抗干扰的？我们都知道MIMO有两种方式，分集和复用；MIMO也有两个显著的特点——可靠性与有效性。MIMO采用多进多出的天线，来实现可靠性和有效性的提升。公网采用MIMO用来提升通信容量——有效性，专网通信用MIMO来提升系统的可靠性。今天主要来讲一讲MIMO是如何实现可靠性的提升。分集分集是在多条独立通道传输相同的数据，接收端通过分集 合并技术，抵抗信道衰落，提升信道传输的可靠性。复用复用是在多条独立信道传输不同的数据，提升频谱利用率，增加信道容量。在了解分集提升抗干扰性之前，我们先了解两个概念。瑞利衰落和多径效应。瑞利衰落是指信号在传输过程中，由于多普勒效应的影响使得信号的相位和幅度发生快速变化，这种变化被称为快速衰落。多径衰落则是指信号在传输过程中经历了多条路径，不同路径的信号到达时相位不同引起信号的叠加干扰，导致信号的衰落。瑞利衰落和多径衰落都是无线传输中不可避免的信道影响，但它们的产生机理不同。多径衰落是由于信号在传播时经历了不同路径的干涉导致信号衰减，而瑞利衰落则是由于信号振荡和干扰造成的快速衰落。在环境较为简单的开放区域，多径效应相对弱，主要由瑞利衰落引起；而在城市、山地等复杂环境下，多径效应很强，是主要的信道衰落因子。瑞利衰落和多径衰落都衰落的一种,衰落具有独立性，即只要接收距离足够大，则接收到的信号衰落不具备相关性，这就是MIMO分集抗衰落的设计原则。在信道中，使用1根发射天线n根接收天线，发送信号通过n个不同的路径。分集在天线设计时，都会保证各个天线之间无相关，所以天线之间的衰落是独立的，可以获得最大的分集增益为n，平均误差概率可以减小 。对于发射分集技术来说，同样是利用多条路径的增益来提高系统的可靠性。在一个具有m根发射天线n根接收天线的系统中，如果天线对之间的路径增益是独立均匀分布的瑞利衰落，可以获得的最大分集增益为mn。对比仿真从仿真结果看，2T1R的效果好于1T1R，1T2R的效果好于2T1R，这也能理解4G手机是1发多收，而不是多发1收。附仿真代码frmLen = 100; % frame lengthnumPackets = 1000; % number of packetsEbNo = 0:2:20; % Eb/No varying to 20 dBN = 2; % maximum number of Tx antennasM = 2; % maximum number of Rx antennas% Create comm.BPSKModulator and comm.BPSKDemodulator System objects(TM)P = 2; % modulation orderbpskMod = comm.BPSKModulator;bpskDemod = comm.BPSKDemodulator('OutputDataType','double');% Create comm.OSTBCEncoder and comm.OSTBCCombiner System objectsostbcEnc = comm.OSTBCEncoder;ostbcComb = comm.OSTBCCombiner;awgn1Rx = comm.AWGNChannel(...'NoiseMethod', 'Signal to noise ratio (Eb/No)', ...'SignalPower', 1);awgn2Rx = clone(awgn1Rx);errorCalc1 = comm.ErrorRate;errorCalc2 = comm.ErrorRate;errorCalc3 = comm.ErrorRate;s = rng(55408);H = zeros(frmLen, N, M);ber_noDiver = zeros(3,length(EbNo));ber_Alamouti = zeros(3,length(EbNo));ber_MaxRatio = zeros(3,length(EbNo));ber_thy2 = zeros(1,length(EbNo));fig = figure;grid on;ax = fig.CurrentAxes;hold(ax,'on');ax.YScale = 'log';xlim(ax,[EbNo(1), EbNo(end)]);ylim(ax,[1e-4 1]);xlabel(ax,'Eb/No (dB)');ylabel(ax,'BER');fig.NumberTitle = 'off';fig.Renderer = 'zbuffer';fig.Name = 'Transmit vs. Receive Diversity';title(ax,'Transmit vs. Receive Diversity');set(fig, 'DefaultLegendAutoUpdate', 'off');fig.Position = figposition([15 50 25 30]);for idx = 1:length(EbNo)reset(errorCalc1);reset(errorCalc2);reset(errorCalc3);% Set the EbNo property of the AWGNChannel System objectsawgn1Rx.EbNo = EbNo(idx);awgn2Rx.EbNo = EbNo(idx);% Loop over the number of packetsfor packetIdx = 1:numPackets% Generate data vector per framedata = randi([0 P-1], frmLen, 1);% Modulate datamodData = bpskMod(data);% Alamouti Space-Time Block EncoderencData = ostbcEnc(modData);% Create the Rayleigh distributed channel response matrix% for two transmit and two receive antennasH(1:N:end, :, :) = (randn(frmLen/2, N, M) + ...1i*randn(frmLen/2, N, M))/sqrt(2);% assume held constant for 2 symbol periodsH(2:N:end, :, :) = H(1:N:end, :, :);% Extract part of H to represent the 1x1, 2x1 and 1x2 channelsH11 = H(:,1,1);H21 = H(:,:,1)/sqrt(2);H12 = squeeze(H(:,1,:));% Pass through the channelschanOut11 = H11 .* modData;chanOut21 = sum(H21.* encData, 2);chanOut12 = H12 .* repmat(modData, 1, 2);% Add AWGNrxSig11 = awgn1Rx(chanOut11);rxSig21 = awgn1Rx(chanOut21);rxSig12 = awgn2Rx(chanOut12);% Alamouti Space-Time Block CombinerdecData = ostbcComb(rxSig21, H21);% ML Detector (minimum Euclidean distance)demod11 = bpskDemod(rxSig11.*conj(H11));demod21 = bpskDemod(decData);demod12 = bpskDemod(sum(rxSig12.*conj(H12), 2));% Calculate and update BER for current EbNo value% for uncoded 1x1 systember_noDiver(:,idx) = errorCalc1(data, demod11);% for Alamouti coded 2x1 systember_Alamouti(:,idx) = errorCalc2(data, demod21);% for Maximal-ratio combined 1x2 systember_MaxRatio(:,idx) = errorCalc3(data, demod12);end % end of FOR loop for numPackets% Calculate theoretical second-order diversity BER for current EbNober_thy2(idx) = berfading(EbNo(idx), 'psk', 2, 2);% Plot resultssemilogy(ax,EbNo(1:idx), ber_noDiver(1,1:idx), 'r*', ...EbNo(1:idx), ber_Alamouti(1,1:idx), 'go', ...EbNo(1:idx), ber_MaxRatio(1,1:idx), 'bs', ...EbNo(1:idx), ber_thy2(1:idx), 'm');legend(ax,'No Diversity (1Tx, 1Rx)', 'Alamouti (2Tx, 1Rx)',...'Maximal-Ratio Combining (1Tx, 2Rx)', ...'Theoretical 2nd-Order Diversity');drawnow;end % end of for loop for EbNo% Perform curve fitting and replot the resultsfitBER11 = berfit(EbNo, ber_noDiver(1,:));fitBER21 = berfit(EbNo, ber_Alamouti(1,:));fitBER12 = berfit(EbNo, ber_MaxRatio(1,:));semilogy(ax,EbNo, fitBER11, 'r', EbNo, fitBER21, 'g', EbNo, fitBER12, 'b');hold(ax,'off');% Restore default streamrng(s);总结当下对MIMO的主流应用主要在增加通信容量上。在专网领域，通信地形的复杂，采用MIMO分集技术可以提升通信系统的通信可靠性。祝好！来源：射频通信链
