mirror of https://github.com/pvnis/srsRAN_4G.git
ZF/MMSE equalizer for single antenna and diversity working correctly
ismagom
10 years ago
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%% PDSCH Transmit Diversity Throughput Conformance Test
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% This example demonstrates the throughput performance under conformance
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% test conditions as defined in TS36.101[ <#9 1> ]: single codeword,
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% transmit diversity 4Tx-2Rx with medium correlation, EPA5 (Extended
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% Pedestrian A) channel. The example also introduces the use of Parallel
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% Computing Toolbox(TM) to provide improvements in the simulation time.
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% Copyright 2009-2013 The MathWorks, Inc.
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%% Introduction
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% In this example, Hybrid Automatic Repeat Request(HARQ) is used in line
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% with conformance test requirements. A total of 8 HARQ processes are used
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% with a maximum of 4 retransmissions permitted. This example uses the R.12
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% Reference Measurement Channel (RMC).
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%
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% This example also uses <matlab:doc('parfor') parfor> loop instead of the
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% <matlab:doc('for') for> loop for SNR calculation. <matlab:doc('parfor')
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% parfor>, as part of the Parallel Computing Toolbox, executes the SNR loop
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% in parallel to reduce the total simulation time.
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%% Simulation Settings
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% The default simulation length is set to 10 frames at a number of |SNR|
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% values including 0.2dB (as per TS36.101 (Section 8.2.1.2.2-Test1)[ <#9
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% 1> ]).
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NFrames = 50; % Number of frames
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SNRdB = [4 5 6]; % SNR range
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% eNodeB Configuration
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enb = struct; % eNodeB config structure
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enb.TotSubframes = 1; % Total subframes RMC will generate
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enb.RC = 'R.10'; % RMC number
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% Channel Configuration
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channel = struct; % Channel config structure
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channel.Seed = 2; % Random channel seed
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channel.NRxAnts = 1; % 2 receive antennas
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channel.DelayProfile ='EVA'; % Delay profile
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channel.DopplerFreq = 5; % Doppler frequency
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channel.MIMOCorrelation = 'Low'; % Multi-antenna correlation
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channel.NTerms = 16; % Oscillators used in fading model
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channel.ModelType = 'GMEDS'; % Rayleigh fading model type
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channel.InitPhase = 'Random'; % Random initial phases
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channel.NormalizePathGains = 'On'; % Normalize delay profile power
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channel.NormalizeTxAnts = 'On'; % Normalize for transmit antennas
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% Channel Estimator Configuration
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cec = struct; % Channel estimation config structure
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cec.PilotAverage = 'UserDefined'; % Type of pilot symbol averaging
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cec.FreqWindow = 9; % Frequency window size
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cec.TimeWindow = 9; % Time window size
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cec.InterpType = 'Linear'; % 2D interpolation type
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cec.InterpWindow = 'Centered'; % Interpolation window type
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cec.InterpWinSize = 1; % Interpolation window size
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% PDSCH Configuration
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enb.PDSCH.TxScheme = 'TxDiversity'; % Transmission scheme
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enb.PDSCH.RNTI = 1; % 16-bit User Equipment (UE) mask
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enb.PDSCH.Rho = 0; % PDSCH RE power adjustment factor
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enb.PDSCH.CSI = 'Off'; % No CSI scaling of soft bits
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% Simulation Variables
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totalBLKCRC = []; % Define total block CRC vector
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bitThroughput = []; % Define total bit throughput vector
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%% System Processing
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% Working on a subframe by subframe basis and using the LTE System
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% Toolbox(TM) a populated resource grid is generated and OFDM modulated to
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% create a transmit waveform. The generated waveform is transmitted through
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% a propagation channel and AWGN is added. Channel estimation, equalization
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% and the inverse of transmission chain are performed at receiver. The
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% throughput performance of the PDSCH is determined using the block CRC
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% result.
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% Generate the RMC configuration structure for RMC R.12
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rmc = lteRMCDL(enb);
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rvSeq = rmc.PDSCH.RVSeq;
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% Transport block sizes for each subframe in a frame
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trBlkSizes = rmc.PDSCH.TrBlkSizes;
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codedTrBlkSizes = rmc.PDSCH.CodedTrBlkSizes;
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% Determine resource grid dimensions
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dims = lteDLResourceGridSize(rmc);
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p = dims(3);
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% Set up channel model sampling rate
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ofdmInfo = lteOFDMInfo(rmc);
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channel.SamplingRate = ofdmInfo.SamplingRate;
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% Generation HARQ table for 8-HARQ processes
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harqTable = hHARQTable();
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% Initializing state of all HARQ processes
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for i=1:9
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harqProcess_init(i) = hTxDiversityNewHARQProcess ...
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(trBlkSizes(i),codedTrBlkSizes(i),rvSeq); %#ok<SAGROW>
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end
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% Display the SNR points being simulated
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for s=1:numel(SNRdB)
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fprintf('\nSimulating at %gdB SNR for a total %d Frame(s)\n', ...
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SNRdB(s),NFrames);
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end
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% The temporary variables 'rmc_init' and 'channel_init' are used to create
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% the temporary variables 'rmc' and 'channel' within the SNR loop to create
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% independent simulation loops for the parfor loop
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rmc_init = rmc;
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channel_init = channel;
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% 'parfor' will default to the normal 'for' when executed without Parallel
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% Computing Toolbox.
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parfor index = 1:numel(SNRdB)
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% Set the random number generator seed depending to the loop variable
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% to ensure independent random streams
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rng(index,'combRecursive');
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% Set up variables for the SNR loop
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offsets = 0; % Initialize overall frame offset value for the SNR
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offset = 0; % Initialize frame offset value for the radio frame
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rmc = rmc_init; % Initialize RMC configuration
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channel = channel_init; % Initialize channel configuration
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blkCRC = []; % Define intermediate block CRC vector
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bitTput = []; % Intermediate bit throughput vector
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% Initializing state of all HARQ processes
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harqProcess = harqProcess_init;
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for subframeNo = 0:(NFrames*10-1)
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% Updating subframe number
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rmc.NSubframe = subframeNo;
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% HARQ index table
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harqIdx = harqTable(mod(subframeNo,length(harqTable))+1); %#ok<PFBNS>
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% Update HARQ process
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harqProcess(harqIdx) = hTxDiversityHARQScheduling( ...
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harqProcess(harqIdx));
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% Updating the RV value for correct waveform generation
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rmc.PDSCH.RV = harqProcess(harqIdx).rvSeq ...
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(harqProcess(harqIdx).rvIdx);
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rmc.PDSCH.RVSeq = harqProcess(harqIdx).rvSeq ...
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(harqProcess(harqIdx).rvIdx);
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[txWaveform txGrid] = lteRMCDLTool(rmc, ...
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{harqProcess(harqIdx).dlschTransportBlk});
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txWaveform = [txWaveform; zeros(25,p)];
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% Initialize at time zero
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channel.InitTime = subframeNo/1000;
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% Pass data through the fading channel model
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rxWaveform = lteFadingChannel(channel,txWaveform);
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% Noise setup including compensation for downlink power allocation
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SNR = 10^((SNRdB(index)-rmc.PDSCH.Rho)/20); % Linear SNR
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% Normalize noise power to take account of sampling rate, which is
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% a function of the IFFT size used in OFDM modulation, and the
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% number of antennas
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N0 = 1/(sqrt(2.0*rmc.CellRefP*double(ofdmInfo.Nfft))*SNR);
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% Create additive white Gaussian noise
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noise = N0*complex(randn(size(rxWaveform)), ...
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randn(size(rxWaveform)));
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% Add AWGN to the received time domain waveform
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rxWaveform = rxWaveform + noise;
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% Receiver
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% Perform synchronization
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% An offset within the range of delays expected from the channel
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% modeling(a combination of implementation delay and channel delay
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% spread) indicates success
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if (mod(subframeNo,10)==0)
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[offset] = lteDLFrameOffset(rmc,rxWaveform);
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if (offset > 25)
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offset = offsets(end);
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end
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offsets = [offsets offset];
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end
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rxWaveform = rxWaveform(1+offset:end,:);
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% Perform OFDM demodulation on the received data to recreate the
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% resource grid
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rxSubframe = lteOFDMDemodulate(rmc,rxWaveform);
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% Equalization and channel estimation
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[estChannelGrid,noiseEst] = lteDLChannelEstimate(rmc,cec, ...
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rxSubframe);
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addpath('../../debug/lte/phy/lib/ch_estimation/test')
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[est, ~, output] = liblte_chest(rmc.NCellID,rmc.CellRefP,rxSubframe,[0.25 0.5 0.25],[0.1 0.9],mod(rmc.NSubframe,10));
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%estChannelGrid=reshape(est,size(estChannelGrid));
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% Perform deprecoding, layer demapping, demodulation and
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% descrambling on the received data using the estimate of
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% the channel
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rxEncodedBits = ltePDSCHDecode2(rmc,rmc.PDSCH,rxSubframe,estChannelGrid,noiseEst);
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% Decode DownLink Shared Channel (DL-SCH)
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[decbits,harqProcess(harqIdx).crc,harqProcess(harqIdx).decState] = ...
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lteDLSCHDecode(rmc,rmc.PDSCH,harqProcess(harqIdx).trBlkSize, ...
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rxEncodedBits{1},harqProcess(harqIdx).decState);
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if(harqProcess(harqIdx).trBlkSize ~= 0)
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blkCRC = [blkCRC harqProcess(harqIdx).crc];
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bitTput = [bitTput harqProcess(harqIdx).trBlkSize.*(1- ...
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harqProcess(harqIdx).crc)];
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end
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end
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% Record the block CRC and bit throughput for the total number of
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% frames simulated at a particular SNR
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totalBLKCRC(index,:) = blkCRC;
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bitThroughput(index,:) = bitTput;
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end
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%%
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% |totalBLKCRC| is a matrix where each row contains the results of decoding
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% the block CRC for a defined value of SNR. |bitThroughput| is a matrix
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% containing the total number of bits per subframe at the different SNR
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% points that have been successfully received and decoded.
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%% Results
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% First graph shows the throughput as total bits per second against the
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% range of SNRs
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% figure;
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% plot(SNRdB,mean(bitThroughput,2),'-*');
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% %axis([-5 3 200 400])
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% title(['Throughput for ', num2str(NFrames) ' frame(s)'] );
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% xlabel('SNRdB'); ylabel('Throughput (kbps)');
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% grid on;
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% hold on;
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% plot(SNRdB,mean([trBlkSizes(1:5) trBlkSizes(7:10)])*0.7*ones ...
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% (1,numel(SNRdB)),'--rs');
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% legend('Simulation Result','70 Percent Throughput','Location','SouthEast');
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%
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% % Second graph shows the total throughput as a percentage of CRC passes
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% % against SNR range
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% figure;
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plot(SNRdB,100*(1-mean(totalBLKCRC,2)),'-*');
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%axis([-5 3 50 110])
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title(['Throughput for ', num2str(NFrames) ' frame(s)'] );
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xlabel('SNRdB'); ylabel('Throughput (%)');
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grid on;
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hold on;
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plot(SNRdB,70*ones(1,numel(SNRdB)),'--rs');
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legend('Simulation Result','70 Percent Throughput','Location','SouthEast');
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%% Further Exploration
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%
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% You can modify parts of this example to experiment with different number
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% of |NFrames| and different values of SNR. SNR can be a vector of
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% values or a single value. Following scenarios can be simulated.
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%%
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% * Allows control over the total number of frames to run the demo at an
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% SNR of 0.2dB (as per TS 36.101).
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%
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% * Allows control over the total number of frames to run the demo, as well
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% as defining a set of desired SNR values. |SNRIn| can be a single value
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% or a vector containing a range of values.
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%
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% * For simulations of multiple SNR points over a large number of frames,
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% the use of Parallel Computing Toolbox provides significant improvement in
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% the simulation time. This can be easily verified by changing the |parfor|
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% in the SNR loop to |for| and re-running the example.
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%% Appendix
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% This example uses the following helper functions:
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%
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% * <matlab:edit('hHARQTable.m') hHARQTable.m>
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% * <matlab:edit('hTxDiversityHARQScheduling.m') hTxDiversityHARQScheduling.m>
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% * <matlab:edit('hTxDiversityNewHARQProcess.m') hTxDiversityNewHARQProcess.m>
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%% Selected Bibliography
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% # 3GPP TS 36.101
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displayEndOfDemoMessage(mfilename)
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