Effect of Inter-Cell Interference on PDSCH Throughput with MMSE-IRC Receiver
This example demonstrates the effect of inter-cell interference on PDSCH throughput with minimum mean square error (MMSE) and minimum mean square error - interference rejection combining (MMSE-IRC) receiver. A serving cell and two interfering eNodeBs are considered. The conditions specified in TS 36.101, Section 8.2.1.4.1B [ 1 ] are used.
Introduction
This example measures the achieved throughput for a user equipment (UE) in the serving cell with inter-cell interference from two dominant interfering cells. The serving cell uses RMC R.47 in FDD mode. The parameters for the serving and interfering cells including power levels and noise levels are described in TS 36.101, Section 8.2.1.4.1B [ 1 ].
Simulation Settings
The default simulation length is set to four frames to keep the simulation time low. Increase NFrames
to increase the simulation time and produce statistically significant throughput results. Use the variable eqMethod
to set the receiver equalization, which can take the values 'MMSE' and 'MMSE_IRC'.
NFrames = 4; % Number of frames eqMethod = 'MMSE_IRC'; % MMSE, MMSE_IRC
The signal, interferers, and noise power levels are specified in the test (TS 36.101, Section 8.2.1.4.1B [ 1 ]) using the following parameters: signal-to-interference-plus-noise ratio (SINR), dominant interferer proportion (DIP) and noise power spectral density.
SINR = 0.8; % SINR in dB DIP2 = -1.73; % DIP in dB for cell 2 DIP3 = -8.66; % DIP in dB for cell 3 Noc = -98; % dBm/15kHz average power spectral density
The DIP characterizes each of the interfering cells and is defined as:
where and are the average received power spectral density from cells 2 and 3, respectively. is the average power spectral density of a white noise source (average power per resource element normalized with respect to the subcarrier spacing).
Serving eNodeB Configuration
The test considered uses reference channel R.47 in FDD mode. The parameters associated with this reference channel are specified in (TS 36.101, Table A.3.3.2.1-2 [ 1 ]). The structure enb1
characterizes the serving cell.
% Set the random number generator seed rng('default'); % Set cell 1 eNodeB configuration according to R.47 simulationParameters = struct; simulationParameters.NDLRB = 50; simulationParameters.CellRefP = 2; simulationParameters.NCellID = 0; simulationParameters.CFI = 2; simulationParameters.DuplexMode = 'FDD'; simulationParameters.TotSubframes = 1; % This is not the total number of % subframes used in the simulation, just the number of subframes we % generate per call to the waveform generator. % Specify PDSCH configuration substructure simulationParameters.PDSCH.TxScheme = 'SpatialMux'; simulationParameters.PDSCH.Modulation = {'16QAM'}; simulationParameters.PDSCH.NLayers = 1; simulationParameters.PDSCH.Rho = -3; simulationParameters.PDSCH.PRBSet = (0:49)'; % Table A.3.3.2.1-2, TS 36.101 simulationParameters.PDSCH.TrBlkSizes = [8760 8760 8760 8760 8760 0 8760 8760 8760 8760]; % Table A.3.3.2.1-2, TS 36.101 simulationParameters.PDSCH.CodedTrBlkSizes = [24768 26400 26400 26400 26400 0 26400 26400 26400 26400]; simulationParameters.PDSCH.CSIMode = 'PUCCH 1-1'; simulationParameters.PDSCH.PMIMode = 'Wideband'; simulationParameters.PDSCH.CSI = 'On'; simulationParameters.PDSCH.W = []; simulationParameters.PDSCH.CodebookSubset = '1111'; % Specify PDSCH OCNG configuration simulationParameters.OCNGPDSCHEnable = 'On'; % Enable OCNG fill simulationParameters.OCNGPDSCHPower = -3; % OCNG power same as PDSCH Rho simulationParameters.OCNGPDSCH.RNTI = 0; % Virtual UE RNTI simulationParameters.OCNGPDSCH.Modulation = 'QPSK'; % OCNG symbol modulation simulationParameters.OCNGPDSCH.TxScheme = 'TxDiversity'; % OCNG transmission mode 2
Call lteRMCDLTool
to generate the default eNodeB parameters not specified in simulationParameters
.
enb1 = lteRMCDL(simulationParameters);
Interfering eNodeBs Configurations
The two interfering cells are characterized by the structures enb2
and enb3
. These have the same field values as the serving cell (enb1
) with the following exceptions:
Cell Id takes the values 1 and 2 for
enb2
andenb3
, respectively.
The PDSCH modulation scheme is specified by the transmission mode 4 (TM4) interference model (TS 36.101, B.5.3 [ 1 ]). This value changes on a subframe-by-subframe basis and is modified in the main processing loop.
% Cell 2 enb2 = enb1; enb2.NCellID = 1; enb2.OCNGPDSCHEnable = 'Off'; % Cell 3 enb3 = enb1; enb3.NCellID = 2; enb3.OCNGPDSCHEnable = 'Off';
Propagation Channel and Channel Estimator Configurations
This section sets up the parameters for three propagation channels
Serving cell to UE
First interfering cell to UE
Second interfering cell to UE
As specified in (TS 36.101, Table 8.2.1.4.1B-2 [ 1 ]) EVA5 channel conditions are used.
% eNodeB1 to UE propagation channel channel1 = struct; % Channel config structure channel1.Seed = 20; % Channel seed channel1.NRxAnts = 2; % 2 receive antennas channel1.DelayProfile ='EVA'; % Delay profile channel1.DopplerFreq = 5; % Doppler frequency channel1.MIMOCorrelation = 'Low'; % Multi-antenna correlation channel1.NTerms = 16; % Oscillators used in fading model channel1.ModelType = 'GMEDS'; % Rayleigh fading model type channel1.InitPhase = 'Random'; % Random initial phases channel1.NormalizePathGains = 'On'; % Normalize delay profile power channel1.NormalizeTxAnts = 'On'; % Normalize for transmit antennas
The channel sampling rate depends on the FFT size used in the OFDM modulator. This can be obtained using the function lteOFDMInfo
.
ofdmInfo = lteOFDMInfo(enb1); channel1.SamplingRate = ofdmInfo.SamplingRate; % eNodeB2 (interference) to UE propagation channel channel2 = channel1; channel2.Seed = 122; % Channel seed % eNodeB3 (interference) to UE propagation channel channel3 = channel1; channel3.Seed = 36; % Channel seed
The variable perfectChanEstimator
controls channel estimator behavior. Valid values are true
or false
. When set to true
a perfect channel estimate is used otherwise an imperfect estimate is used, based on the values of received pilot signals.
% Channel estimator behavior perfectChanEstimator = true; % The channel estimator configuration structure is defined below. The % frequency and time averaging window sizes are chosen to span a relatively % large number of resource elements. The large window sizes are chosen to % average as much as possible noise and interference in the resource % elements. Note that too large an averaging window in time and/or frequency % will cause loss of information due to averaging out the channel variations. % This produces an increasingly imperfect channel estimate which can affect % the performance of the equalizer. cec = struct; % Channel estimation config structure cec.PilotAverage = 'UserDefined'; % Type of pilot symbol averaging cec.FreqWindow = 31; % Frequency window size cec.TimeWindow = 23; % Time window size cec.InterpType = 'Cubic'; % 2D interpolation type cec.InterpWindow = 'Centered'; % Interpolation window type cec.InterpWinSize = 1; % Interpolation window size
Signal, Interference and Noise Power Levels
From the SINR, DIP and Noc
values we can calculate the scaling factors to apply to the signals from the serving and interfering cells, as well as the noise level.
The function hENBscalingFactors.m calculates the scaling factors K1
, K2
and K3
to apply to the channel filtered waveforms from the three cells considered. The scaling factor No
to apply to the white Gaussian noise is also calculated. These values ensure that the signal power, interference power and noise power are as per the specified SINR and DIP values.
% Channel noise setup nocLin = 10.^(Noc/10)*(1e-3); % linear in Watts % Take into account FFT (OFDM) scaling No = sqrt(nocLin/(2*double(ofdmInfo.Nfft))); % Signal and interference amplitude scaling factors calculation [K1, K2, K3] = hENBscalingFactors(DIP2, DIP3, Noc, SINR, enb1, enb2, enb3);
Main Loop Initialization
Before the main processing loop we need to set up the hybrid automatic repeat request (HARQ) processes and initialize intermediate variables. A HARQ process ID sequence corresponding to the configuration is output by the lteRMCDLTool
function. A HARQ process (with IDs 1 to 8) is associated to each subframe that has data scheduled. A value of 0 in the sequence indicates that data is not transmitted in the corresponding subframe. This can be because it is an uplink subframe or because no data is scheduled in a downlink subframe (similar to subframe 5 in this example).
% Initialize state of all HARQ processes harqProcesses = hNewHARQProcess(enb1); % Initialize HARQ process IDs to 1 as the first non-zero transport % block will always be transmitted using the first HARQ process. This % will be updated with the full sequence output by lteRMCDLTool after % the first call to the function harqProcessSequence = 1; % Set up variables for the main loop lastOffset = 0; % Initialize frame timing offset from previous frame frameOffset = 0; % Initialize frame timing offset nPMI = 0; % Initialize the number of precoder matrix indication % (PMI) set calculated blkCRC = []; % Block CRC for all considered subframes bitTput = []; % Number of successfully received bits per subframe txedTrBlkSizes = []; % Number of transmitted bits per subframes % Vector of total number of bits transmitted, calculated for each subframe. runningMaxThPut = []; % Vector storing the number of successfully received bits, calculated for % each subframe. runningSimThPut = []; % Obtain the number of transmit antennas. dims = lteDLResourceGridSize(enb1); P = dims(3); % Assign the redundancy version sequence for each codeword and transport % block sizes for each subframe rvSequence = enb1.PDSCH.RVSeq; trBlkSizes = enb1.PDSCH.TrBlkSizes; % Set the PMI delay for the closed-loop spatial multiplexing pmiDelay = 8; % As specified in TS 36.101, Table 8.2.1.4.1B-1 % Initialize PMIs for the first 'pmiDelay' subframes pmiDims = ltePMIInfo(enb1,enb1.PDSCH); txPMIs = zeros(pmiDims.NSubbands, pmiDelay); % Flag to indicate if a valid PMI feedback is available from the UE pmiReady = false;
Main Loop
The main loop iterates over the specified number of subframes. For each downlink subframe with data the following operations are performed:
Check the HARQ processes and determine whether to send a new packet or if a retransmission is required
Generate downlink waveforms from serving cell and interfering cells
Filter waveforms with propagation channels and add white Gaussian noise
Synchronize and OFDM demodulate the signal from the serving cell
Estimate the propagation channel for the serving cell
Equalize and decode the PDSCH
Decode the DL-SCH
Determine throughput performance using the block CRC obtained
fprintf('\nSimulating %d frame(s)\n',NFrames); % Main for loop: for all subframes for subframeNo = 0:(NFrames*10-1) % Reinitialize channel seed for each subframe to increase variability channel1.Seed = 1+subframeNo; channel2.Seed = 1+subframeNo+(NFrames*10); channel3.Seed = 1+subframeNo+2*(NFrames*10); % Update subframe number enb1.NSubframe = subframeNo; enb2.NSubframe = subframeNo; enb3.NSubframe = subframeNo; duplexInfo = lteDuplexingInfo(enb1); if duplexInfo.NSymbolsDL ~= 0 % target only downlink subframes % Get HARQ process ID for the subframe from HARQ process sequence harqID = harqProcessSequence(mod(subframeNo, length(harqProcessSequence))+1); % If there is a transport block scheduled in the current subframe % (indicated by non-zero 'harqID'), perform transmission and % reception. Otherwise, continue to the next subframe. if harqID == 0 continue; end % Update current HARQ process harqProcesses(harqID) = hHARQScheduling( ... harqProcesses(harqID), subframeNo, rvSequence); % Extract the current subframe transport block size(s) trBlk = trBlkSizes(:, mod(subframeNo, 10)+1).'; % Update the PDSCH transmission config with HARQ process state enb1.PDSCH.RVSeq = harqProcesses(harqID).txConfig.RVSeq; enb1.PDSCH.RV = harqProcesses(harqID).txConfig.RV; dlschTransportBlk = harqProcesses(harqID).data; % Set the PMI to the appropriate value in the delay queue if strcmpi(enb1.PDSCH.TxScheme,'SpatialMux') pmiIdx = mod(subframeNo, pmiDelay); % PMI index in delay queue enb1.PDSCH.PMISet = txPMIs(:, pmiIdx+1); % Set PMI end % Create transmit waveform [tx,~,enbOut] = lteRMCDLTool(enb1, dlschTransportBlk); % Pad 25 samples to cover the range of delays expected from channel % modeling (a combination of implementation delay and channel delay % spread) txWaveform1 = [tx; zeros(25, P)]; % Get the HARQ ID sequence from 'enbOut' for HARQ processing harqProcessSequence = enbOut.PDSCH.HARQProcessSequence; % Generate interferer model as per as per TS 36.101, B.5.3. The % function hTM4InterfModel generates the interferer transmit signal. txWaveform2 = [hTM4InterfModel(enb2); zeros(25,P)]; txWaveform3 = [hTM4InterfModel(enb3); zeros(25,P)]; % Specify channel time for the present subframe channel1.InitTime = subframeNo/1000; channel2.InitTime = channel1.InitTime; channel3.InitTime = channel1.InitTime; % Pass data through the channel rxWaveform1 = lteFadingChannel(channel1,txWaveform1); rxWaveform2 = lteFadingChannel(channel2,txWaveform2); rxWaveform3 = lteFadingChannel(channel3,txWaveform3); % Generate noise noise = No*complex(randn(size(rxWaveform1)), ... randn(size(rxWaveform1))); % Add AWGN to the received time domain waveform rxWaveform = K1*rxWaveform1 + K2*rxWaveform2 + K3*rxWaveform3 + noise; % Receiver % Once every frame, on subframe 0, calculate a new synchronization % offset if (mod(subframeNo,10) == 0) frameOffset = lteDLFrameOffset(enb1, rxWaveform); if (frameOffset > 25) frameOffset = lastOffset; end lastOffset = frameOffset; end % Synchronize the received waveform rxWaveform = rxWaveform(1+frameOffset:end, :); % Scale rxWaveform by 1/K1 to avoid numerical issues with % channel decoding stages rxWaveform = rxWaveform/K1; % Perform OFDM demodulation on the received data to obtain the % resource grid rxSubframe = lteOFDMDemodulate(enb1, rxWaveform); % Perform channel estimation if(perfectChanEstimator) estChannelGrid = lteDLPerfectChannelEstimate(enb1, channel1, frameOffset); noiseInterf = K2*rxWaveform2 + K3*rxWaveform3 + noise; noiseInterf = noiseInterf/K1; noiseGrid = lteOFDMDemodulate(enb1, noiseInterf(1+frameOffset:end ,:)); noiseEst = var(noiseGrid(:)); else [estChannelGrid, noiseEst] = lteDLChannelEstimate( ... enb1, enb1.PDSCH, cec, rxSubframe); end % Get PDSCH indices pdschIndices = ltePDSCHIndices(enb1,enb1.PDSCH,enb1.PDSCH.PRBSet); % Get PDSCH resource elements. Scale the received subframe by % the PDSCH power factor Rho. [pdschRx, pdschHest] = lteExtractResources(pdschIndices, ... rxSubframe*(10^(-enb1.PDSCH.Rho/20)), estChannelGrid); % Perform equalization and deprecoding if strcmp(eqMethod,'MMSE') % MIMO equalization and deprecoding (MMSE based) [rxDeprecoded,csi] = lteEqualizeMIMO(enb1,enb1.PDSCH,... pdschRx,pdschHest,noiseEst); else % MIMO equalization and deprecoding (MMSE-IRC based) [rxDeprecoded,csi] = hEqualizeMMSEIRC(enb1,enb1.PDSCH,... rxSubframe,estChannelGrid,noiseEst); end % Perform layer demapping, demodulation and descrambling cws = ltePDSCHDecode(enb1,setfield(enb1.PDSCH,'TxScheme',... 'Port7-14'),rxDeprecoded); % The PDSCH transmission scheme is % modified into port7-14, in order to skip the deprecoding operation % Scaling LLRs by CSI cws = hCSIscaling(enb1.PDSCH,cws,csi); % Decode DL-SCH [decbits, harqProcesses(harqID).blkerr,harqProcesses(harqID).decState] = ... lteDLSCHDecode(enb1, enb1.PDSCH, trBlk, cws, ... harqProcesses(harqID).decState); % Store values to calculate throughput % Only for subframes with data and valid PMI feedback if any(trBlk) && pmiReady blkCRC = [blkCRC harqProcesses(harqID).blkerr]; txedTrBlkSizes = [txedTrBlkSizes trBlk]; bitTput = [bitTput trBlk.*(1-harqProcesses(harqID).blkerr)]; end runningSimThPut = [runningSimThPut sum(bitTput,2)]; runningMaxThPut = [runningMaxThPut sum(txedTrBlkSizes,2)]; % Provide PMI feedback to the eNodeB if strcmpi(enb1.PDSCH.TxScheme,'SpatialMux') PMI = ltePMISelect(enb1, enb1.PDSCH, estChannelGrid, noiseEst); txPMIs(:, pmiIdx+1) = PMI; nPMI = nPMI+1; if nPMI>=pmiDelay pmiReady = true; end end end end
Simulating 4 frame(s)
Results
This section calculates the achieved throughput. A figure with the running measured throughput for all simulated subframes is also provided.
maxThroughput = sum(txedTrBlkSizes); % Maximum possible throughput simThroughput = sum(bitTput,2); % Simulated throughput % Display achieved throughput percentage disp(['Achieved throughput ' num2str(simThroughput*100/maxThroughput) '%']) % Plot running throughput figure;plot(runningSimThPut*100./runningMaxThPut) ylabel('Throughput (%)'); xlabel('Simulated subframe'); title('Throughput');
Achieved throughput 78.5714%
For statistically valid results, the simulation should be run for a larger number of frames. The figure below shows the throughput results when simulating 1000 frames.
Appendix
This example uses the following helper functions:
Selected Bibliography
3GPP TS 36.101 "User Equipment (UE) radio transmission and reception"
3GPP TR 36.829 "Enhanced performance requirement for LTE User Equipment (UE)"