PUCCH3 ACK Missed Detection Probability Conformance Test
This example measures the ACK missed detection probability using the LTE System Toolbox™ under the single user Physical Uplink Control Channel (PUCCH3) conformance test conditions as defined in TS 36.104 Section 22.214.171.124 [ 1 ].
This example uses a simulation length of 10 subframes. This value has been chosen to speed up the simulation. A larger value should be chosen to obtain more accurate results. The target defined in TS36.104 Section 126.96.36.199 [ 1 ] for 10 MHz bandwidth (50 resource blocks) and a single transmit antenna is an Acknowledgment (ACK) missed detection probability not exceeding 1% at an SNR of -3.7 dB. The test is defined for 1 transmit antenna.
numSubframes = 10; % Number of subframes SNRdB = [-9.7 -7.7 -5.7 -3.7 -1.7]; % SNR range NTxAnts = 1; % Number of transmit antennas
ue = struct; % UE config structure ue.NULRB = 50; % 50 resource blocks (10 MHz) ue.CyclicPrefixUL = 'Normal'; % Normal cyclic prefix ue.NTxAnts = NTxAnts; ue.NCellID = 9; ue.RNTI = 1; % Radio network temporary id ue.Hopping = 'Off'; % No frequency hopping ue.Shortened = 0; % No SRS transmission
PUCCH 3 Configuration
% Vector of PUCCH resource indices, one per transmission antenna. This is % the n3pucch parameter. pucch = struct; pucch.ResourceIdx = 0:ue.NTxAnts-1;
Propagation Channel Configuration
Configure the channel model with the parameters specified in the tests described in TS36.104 Section 188.8.131.52 [ 1 ].
channel = struct; % Channel config structure channel.NRxAnts = 2; % Number of receive antennas channel.DelayProfile = 'EPA'; % Channel delay profile channel.DopplerFreq = 5.0; % Doppler frequency in Hz channel.MIMOCorrelation = 'Low'; % Low MIMO correlation channel.NTerms = 16; % Oscillators used in fading model channel.ModelType = 'GMEDS'; % Rayleigh fading model type channel.Seed = 4; % Random number generator seed channel.InitPhase = 'Random'; % Random initial phases channel.NormalizePathGains = 'On';% Normalize delay profile power channel.NormalizeTxAnts = 'On'; % Normalize for transmit antennas % SC-FDMA modulation information: required to get the sampling rate info = lteSCFDMAInfo(ue); channel.SamplingRate = info.SamplingRate;
Channel Estimator Configuration
The channel estimator is configured using a structure cec. Here cubic interpolation will be used with an averaging window of 12-by-1 Resource Elements (REs). This configures the channel estimator to use a special mode which ensures the ability to despread and orthogonalize the different overlapping PUCCH transmissions.
cec = struct; % Channel estimation config structure cec.PilotAverage = 'UserDefined'; % Type of pilot averaging cec.FreqWindow = 12; % Frequency averaging window in REs (special mode) cec.TimeWindow = 1; % Time averaging window in REs (Special mode) cec.InterpType = 'cubic'; % Cubic interpolation
Simulation Loop for Configured SNR Points
For each SNR point the loop below calculates the probability of successful ACK detection using information obtained from NSubframes consecutive subframes. The following operations are performed for each subframe and SNR values:
- Create an empty resource grid
- Generate and map PUCCH 3 and its Demodulation Reference Signal (DRS) to the resource grid
- Apply SC-FDMA modulation
- Send the modulated signal through the channel
- Receiver synchronization
- Apply SC-FDMA demodulation
- Estimate the channel
- Minimum Mean Squared Error (MMSE) equalization
- PUCCH 3 demodulation/decoding
- Record decoding failures
% Preallocate memory for missed detection probability vector PMISS = zeros(size(SNRdB)); for nSNR = 1:length(SNRdB) % Detection failures counter missCount = 0; falseCount = 0; % Noise configuration SNR = 10^(SNRdB(nSNR)/20); % Convert dB to linear % The noise added before SC-FDMA demodulation will be amplified by the % IFFT. The amplification is the square root of the size of the IFFT. % To achieve the desired SNR after demodulation the noise power is % normalized by this value. In addition, because real and imaginary % parts of the noise are created separately before being combined into % complex additive white Gaussian noise, the noise amplitude must be % scaled by 1/sqrt(2*ue.NTxAnts) so the generated noise power is 1. N = 1/(SNR*sqrt(double(info.Nfft)))/sqrt(2.0*ue.NTxAnts); % Set the type of random number generator and its seed to the default % value rng('default'); % Loop for subframes offsetused = 0; for nsf = 1:numSubframes % Create resource grid ue.NSubframe = mod(nsf-1,10); % Subframe number reGrid = lteULResourceGrid(ue); % Resource grid % Generate PUCCH 3 and its DRS N_ACK = 4; % 4 ACK bits ACK = randi([0 1], N_ACK, 1); % Generate N_ACK random bits coded = lteUCI3Encode(ACK); % PUCCH 3 coding pucch3Sym = ltePUCCH3(ue, pucch, coded); % PUCCH 3 modulation pucch3DRSSym = ltePUCCH3DRS(ue, pucch, ACK); % PUCCH 3 DRS creation % Generate indices for PUCCH 3 and its DRS pucch3Indices = ltePUCCH3Indices(ue, pucch); pucch3DRSIndices = ltePUCCH3DRSIndices(ue, pucch); % Map PUCCH 3 and its DRS to the resource grid reGrid(pucch3Indices) = pucch3Sym; reGrid(pucch3DRSIndices) = pucch3DRSSym; % SC-FDMA modulation txwave = lteSCFDMAModulate(ue, reGrid); % Channel state information: set the init time to the correct value % to guarantee continuity of the fading waveform after each % subframe channel.InitTime = (nsf-1)/1000; % Channel modeling % The additional 25 samples added to the end of the waveform % are to cover the range of delays expected from the channel % modeling (a combination of implementation delay and % channel delay spread) rxwave = lteFadingChannel(channel, [txwave; zeros(25, ue.NTxAnts)]); % Add noise at receiver noise = N*complex(randn(size(rxwave)), randn(size(rxwave))); rxwave = rxwave + noise; % Receiver % Synchronization % An offset within the range of delays expected from the channel % modeling (a combination of implementation delay and channel % delay spread) indicates success offset = lteULFrameOffsetPUCCH3(ue, pucch, rxwave); if (offset<25) offsetused = offset; end % SC-FDMA demodulation rxgrid = lteSCFDMADemodulate(ue, rxwave(1+offsetused:end, :)); % Channel estimation [H, n0] = lteULChannelEstimatePUCCH3(ue, pucch, cec, rxgrid); % Extract REs corresponding to the PUCCH 3 from the given subframe % across all receive antennas and channel estimates [pucch3Rx, pucch3H] = lteExtractResources(pucch3Indices, rxgrid, H); % PUCCH 3 MMSE Equalization eqgrid = lteULResourceGrid(ue); eqgrid(pucch3Indices) = lteEqualizeMMSE(pucch3Rx, pucch3H, n0); % PUCCH 3 demodulation rxBits = ltePUCCH3Decode(ue, pucch, eqgrid(pucch3Indices)); % PUCCH 3 decoding rxACK = lteUCI3Decode(rxBits, N_ACK); % Detect missed (empty rxACK) or incorrect Hybrid Automatic Repeat % Request (HARQ)-ACK % (compare against transmitted ACK) if (isempty(rxACK) || any(rxACK ~= ACK)) missCount = missCount + 1; end end PMISS(nSNR) = missCount/numSubframes; end
plot(SNRdB, PMISS, 'b-o', 'MarkerSize', 7, 'LineWidth', 2); hold on; plot(-3.7, 0.01, 'rx', 'MarkerSize', 7, 'LineWidth', 2); xlabel('SNR (dB)'); ylabel('Probability of ACK missed detection'); title(['PUCCH format 3 ACK missed detection test' ... ' (TS36.104 Section 184.108.40.206)']); axis([SNRdB(1)-0.1 SNRdB(end)+0.1 -0.05 0.25]); legend('simulated performance', 'target');
- 3GPP TS 36.104 "Base Station (BS) radio transmission and reception"