matlab MMSE均衡RMC R.4

函数：lteEqualizeMMSE

用法:

[out,csi] = lteEqualizeMMSE(rxgrid,channelest,noiseest)

[out,csi] = lteEqualizeMMSE(rxgrid,channelest,noiseest) 返回多维数组中的均衡数据。利用信道矩阵中的信道信息，将MMSE均衡应用于所述矩阵、Rx网格中的接收数据资源网格。噪声是对接收到的噪声功率谱密度的估计。或者，输入通道可以作为大小为NRE-by-NRxAnts-by-P的三维数组提供，输入的rxGrid可以作为大小NRE-by-NRxAnts的矩阵提供。在这种情况下，通过对感兴趣的资源元素(通常是单个物理通道)的频率和时间位置进行适当的索引，将前两个维度简化为一维。输出为(N×M)×P.

例子1：

enb = lteRMCDL('R.4');
[txSignal,~,info] = lteRMCDLTool(enb,[1;0;0;1]);

chcfg.DelayProfile = 'EPA';
chcfg.NRxAnts = 1;
chcfg.DopplerFreq = 70;
chcfg.MIMOCorrelation = 'Low';
chcfg.SamplingRate = info.SamplingRate;
chcfg.Seed = 1;
chcfg.InitPhase = 'Random';
chcfg.InitTime = 0;

txSignal = [txSignal; zeros(15,1)];
N = length(txSignal);
noise = 1e-3*complex(randn(N,chcfg.NRxAnts),randn(N,chcfg.NRxAnts));
rxSignal = lteFadingChannel(chcfg,txSignal)+noise;
offset = lteDLFrameOffset(enb,rxSignal);
rxGrid = lteOFDMDemodulate(enb,rxSignal(1+offset:end,:));
cec.FreqWindow = 9;
cec.TimeWindow = 9;
cec.InterpType = 'Cubic';
cec.PilotAverage = 'UserDefined';
cec.InterpWinSize = 3;
cec.InterpWindow = 'Causal';
[hest,noiseEst] = lteDLChannelEstimate(enb, cec, rxGrid);
eqGrid = lteEqualizeMMSE(rxGrid, hest, noiseEst);
subplot(2,1,1)
surf(abs(rxGrid))
title('Received grid')
xlabel('OFDM symbol')
ylabel('Subcarrier')

subplot(2,1,2)
surf(abs(eqGrid))
title('Equalized grid')
xlabel('OFDM symbol')
ylabel('Subcarrier')

结果：

matlab MMSE均衡RMC R.4

例子2：

enb = lteRMCDL('R.5');
cec = struct('FreqWindow',9,'TimeWindow',9,'InterpType','cubic');
cec.PilotAverage = 'UserDefined';
cec.InterpWinSize = 1;
cec.InterpWindow = 'Causal';
txWaveform = lteRMCDLTool(enb,[1;0;0;1]);
n = length(txWaveform);
rxWaveform = repmat(txWaveform,1,2)+complex(randn(n,2),randn(n,2))*1e-3;
rxGrid = lteOFDMDemodulate(enb,rxWaveform);
[hest,n0] = lteDLChannelEstimate(enb,cec,rxGrid);
out = lteEqualizeMMSE(rxGrid,hest,n0);
scatterplot(out(:,1))

结果：

matlab MMSE均衡RMC R.4

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参考文献：https://www.mathworks.com/help/lte/ref/lteequalizemmse.html