cfgVHT = wlanVHTConfig;%创建包配置cfgVHT。ChannelBandwidth =“CBW80”;% 80 MHzcfgVHT。NumTransmitAntennas = 1;%一个传输天线cfgVHT。NumSpaceTimeStreams = 1;%一个时空流cfgVHT。摘要= false;%没有摘要一个空间流cfgVHT。MCS = 8;%调制:256 - qamcfgVHT。APEPLength = 3000;% A-MPDU长度pre-EOF填充字节

osf = 3;% 3倍过采样的因素numPackets = 20;%生成20包idleTime = 10 e-6;% 10微秒数据包之间的空闲时间

%建立随机数据;PSDULength在字节savedState = rng (0);%设置随机状态data =兰迪([0,1],cfgVHT.PSDULength * 8 * numPackets, 1);%多包波形生成txWaveform = wlanWaveformGenerator(数据、cfgVHT…“OversamplingFactor”osf,“NumPackets”numPackets,“IdleTime”,idleTime);fs = wlanSampleRate (cfgVHT);%基带波形的采样率

modelIQImbalance = true;%设置为true来添加智商增益和相位不平衡如果modelIQImbalance iqGaindB = 1;%的智商在dB获得不平衡,指定的范围[1]iqPhaseDeg = 1;%的智商相不平衡度,指定的范围(2 - 2)iqGainLin = db2mag (iqGaindB);%获得数据库转换为线性值txWaveform =实际(txWaveform) + 1我*图像放大(txWaveform) * iqGainLin * exp (1 j * iqPhaseDeg *π/ 180);%的等式一指定[5]结束

pSaturation = 25;%功率放大器的饱和功率dBmhpaBackoff = 13;%功率放大器倒扣在dB%创建和配置一个无记忆非线性放大器的模型非线性= comm.MemorylessNonlinearity;非线性。方法=“拉普模式”;非线性。平滑度= 3;% p参数非线性。LinearGain = -hpaBackoff;非线性。OutputSaturationLevel = db2mag (pSaturation-30);%将模型应用于每一个发送天线txWaveform =非线性(txWaveform);

thNoise = comm.ThermalNoise (“NoiseMethod”,“噪声图”,“SampleRate”fs * osf,“NoiseFigure”6);为我= 1:cfgVHT。NumTransmitAntennas txWaveform (:, i) = thNoise (txWaveform(:,我));结束

aStop = 40;%阻带衰减ofdmInfo = wlanVHTOFDMInfo (“VHT-Data”,cfgVHT);% OFDM参数SCS = fs / ofdmInfo.FFTLength;%副载波间距txbw = max (abs (ofdmInfo.ActiveFrequencyIndices)) * 2 * SCS;%占有带宽(L, M) =鼠(1 / osf);maxLM = max (L [M]);R = (fs-txbw) / fs;TW = 2 * R / maxLM;%过渡宽度firdec = designMultirateFIR (L, M、TW aStop,“SystemObject”,真正的);

rxWaveform = firdec (txWaveform);

%设置维生素与测量[EVMPerPkt, EVMPerSC] = vhtEVMSetup (cfgVHT);

%得到访问时域数据包中的每个字段的索引印第安纳州= wlanFieldIndices (cfgVHT);rxWaveformLength =大小(rxWaveform, 1);pktLength =双(ind.VHTData (2));%定义数据的最小长度我们可以检测;L-STF长度%样本minPktLen =双(ind.LSTF (2) -ind.LSTF (1) + 1;%设置测量的情节[据hSF, hCon, hEVM] = vhtTxSetupPlots (cfgVHT);rmsEVM = 0 (numPackets, 1);pktOffsetStore = 0 (numPackets, 1);rng (savedState);%恢复随机状态

pktNum = 0;searchOffset = 0;%从第一个样品(没有抵消)而(searchOffset + minPktLen) < = rxWaveformLength%包检测pktOffset = wlanPacketDetect (rxWaveform cfgVHT.ChannelBandwidth);%包抵消从波形的开始pktOffset = searchOffset + pktOffset;%如果没有包检测或给予补偿的波形然后停止如果isempty (pktOffset) | | (pktOffset < 0) | |…((pktOffset + ind.LSIG (2)) > rxWaveformLength)打破;结束%提取non-HT字段和执行粗频率偏移校正%时间允许可靠的象征nonht = rxWaveform (pktOffset + (ind.LSTF (1): ind.LSIG (2)),:);coarsefreqOff = wlanCoarseCFOEstimate (nonht cfgVHT.ChannelBandwidth);nonht = frequencyOffset (fs, nonht -coarsefreqOff);%确定偏移量之间的预期开始L-LTF和实际开始%的L-LTFlltfOffset = wlanSymbolTimingEstimate (nonht cfgVHT.ChannelBandwidth);%确定数据包抵消pktOffset = pktOffset + lltfOffset;%如果抵消没有波形的跳过样品和继续%在剩下的波形搜索如果(pktOffset < 0) | | ((pktOffset + pktLength) > rxWaveformLength) searchOffset = pktOffset +双(ind.LSTF (2) + 1;继续;结束%的时间同步完成;提取检测包rxPacket = rxWaveform (pktOffset + (1: pktLength):);pktNum = pktNum + 1;disp ([“包”num2str (pktNum)“在指数:”num2str (pktOffset + 1)]);%粗频率校正应用于提取的包rxPacket = frequencyOffset (fs, rxPacket -coarsefreqOff);%对提取的数据包执行好频率偏移校正lltf = rxPacket (ind.LLTF (1): ind.LLTF (2):);%提取L-LTFfineFreqOff = wlanFineCFOEstimate (lltf cfgVHT.ChannelBandwidth);rxPacket = frequencyOffset (fs, rxPacket -fineFreqOff);%提取VHT-LTF样本,解调和信道估计vhtltf = rxPacket (ind.VHTLTF (1): ind.VHTLTF (2):);vhtltfDemod = wlanVHTLTFDemodulate (vhtltf cfgVHT);%得到单一河道的估计chanEstSSPilots = vhtSingleStreamChannelEstimate (vhtltfDemod cfgVHT);%信道估计陈= wlanVHTLTFChannelEstimate (vhtltfDemod cfgVHT);%执行智商增益和相位不平衡的评估(增益、相位、α,β,γ,dataRot] =…helperIQImbalanceEstimate(成龙、cfgVHT);流(“测量智商增益和相位不平衡:% 2.2 f dB, % 2.2 f度\ n '、增益、相位);%对通道执行智商增益和相位不平衡校正%的估计陈=成龙。/(α+β。*γ);% Equation-29指定的[5]%谱平面度测试[通过,偏差,testsc] = wlanSpectralFlatness(陈,“VHT”,cfgVHT.ChannelBandwidth);如果通过disp (通过光谱平坦的);其他的disp (“谱平坦失败”);结束%的情节对极限偏差vhtTxPlotSpectralFlatness (hSF)偏差,testsc, pktNum;%从波形中提取VHT数据样本vhtdata = rxPacket (ind.VHTData (1): ind.VHTData (2):);%的噪声功率估计VHT数据字段noiseVarVHT = vhtNoiseEstimate (vhtdata chanEstSSPilots cfgVHT);%提取VHT数据样本和执行OFDM解调,均衡%和相位跟踪[~,~,eqSym] = wlanVHTDataRecover (vhtdata,成龙、noiseVarVHT cfgVHT,…“EqualizationMethod”,“ZF”,“PilotPhaseTracking”,“PreEQ”);%使用零迫使均衡算法%对VHT执行智商增益和相位不平衡校正数据eqSym = eqSym。* dataRot;%载体旋转副载波的数据eqSym =((连词(α)* eqSym) -(β*连词(eqSym(结束:1:1,:,))))/ ((abs(α)^ 2)——(abs(β)^ 2));% Equation-30指定的[5]%计算均方根维生素在包的所有空间流rmsEVM (pktNum) = EVMPerPkt (eqSym);流(“RMS维生素:% 2.2 f % %, % 2.2身上\ n”rmsEVM (pktNum), 20 * log10 (rmsEVM (pktNum) / 100));%计算均方根维生素与每副载波和空间流的数据包evmPerSC = evmPerSC (eqSym);% Nst-by-1-by-Nss%的阴谋RMS维生素与每副载波恢复的星座vhtTxEVMConstellationPlots (eqSym、evmPerSC cfgVHT、pktNum hCon, hEVM);%在波形存储每个数据包的抵消pktOffsetStore (pktNum) = pktOffset;%增加波形补偿和搜索包剩下的波形searchOffset = pktOffset + pktLength + minPktLen;结束

如果pktNum > 0流(挣值管理的平均都为% d包:% 2.2 f % %, % 2.2身上\ n ',…pktNum,意味着(rmsEVM (1: pktNum)), 20 * log10(平均(rmsEVM (1: pktNum)) / 100));其他的disp (没有完整的包检测);结束

%访问时域数据包中的每个字段的索引印第安纳州= wlanFieldIndices (cfgVHT,“OversamplingFactor”(osf);startIdx = ind.VHTData (1);%开始的数据endIdx = ind.VHTData (2);%的数据idleNSamps = idleTime * fs * osf;%空闲时间样本perPktLength = endIdx + idleNSamps;idx = 0 (endIdx-startIdx + 1, numPackets);为我= 1:numPackets%的包开始txWaveform,占过滤器延迟pktOffset =(张)* perPktLength;%的指数在txWaveform non-HT数据idx (:, i) = pktOffset + (startIdx: endIdx);结束gatedVHTData = txWaveform (idx (:):);

如果pktNum > 0 helperSpectralMaskTest (fs, gatedVHTData osf);结束