nrEqualizeMMSE
Minimum mean-squared error (MMSE) equalization
Description
[
applies MMSE equalization to the extracted resource elements of a physical channel
eqSym
,csi
]
= nrEqualizeMMSE(rxSym
,hest
,nVar
)rxSym
and returns the equalized symbols in
eqSym
. The equalization process uses the estimated channel information
hest
and the estimate of the received noise variance
nVar
. The function also returns the soft channel state information
csi
.
Examples
Perform MMSE Equalization for PBCH
Perform MMSE equalization on extracted resource elements of the physical broadcast channel (PBCH).
Create symbols and indices for a PBCH transmission.
ncellid = 146; v = 0; E = 864; cw = randi([0 1],E,1); pbchTxSym = nrPBCH(cw,ncellid,v); pbchInd = nrPBCHIndices(ncellid);
Generate an empty resource array for one transmitting antenna. Populate the array with the PBCH symbols by using the generated PBCH indices.
carrier = nrCarrierConfig('NSizeGrid',20);
P = 1;
txGrid = nrResourceGrid(carrier,P);
txGrid(pbchInd) = pbchTxSym;
Perform OFDM modulation.
txWaveform = nrOFDMModulate(carrier,txGrid);
Create channel matrix and apply channel to transmitted waveform.
R = 4; H = dftmtx(max([P R])); H = H(1:P,1:R); H = H / norm(H); rxWaveform = txWaveform * H;
Create channel estimate.
hEstGrid = repmat(permute(H.',[3 4 1 2]),[240 4]); nEst = 0.1;
Perform OFDM demodulation.
rxGrid = nrOFDMDemodulate(carrier,rxWaveform);
To prepare for PBCH decoding, use nrExtractResources
to extract symbols from received and channel estimate grids. Plot the received PBCH constellation.
[pbchRxSym,pbchHestSym] = nrExtractResources(pbchInd,rxGrid,hEstGrid); scatterplot(pbchRxSym(:),[],[],'y+'); title('Received PBCH Constellation');
Decode the PBCH with the extracted resource elements. Plot the equalized PBCH constellation.
[pbchEqSym,csi] = nrEqualizeMMSE(pbchRxSym,pbchHestSym,nEst); pbchBits = nrPBCHDecode(pbchEqSym,ncellid,v); scatterplot(pbchEqSym(:),[],[],'y+'); title('Equalized PBCH Constellation');
Input Arguments
rxSym
— Extracted resource elements
2-D numeric matrix
Extracted resource elements of a physical channel, specified as an NRE-by-R numeric matrix. NRE is the number of resource elements extracted from each K-by-L plane of the received grid. K is the number of subcarriers and L is the number of OFDM symbols. R is the number of receive antennas.
Data Types: double
Complex Number Support: Yes
hest
— Estimated channel information
3-D numeric array
Estimated channel information, specified as an NRE-by-R-by-P numeric array. NRE is the number of resource elements extracted from each K-by-L plane of the received grid. K is the number of subcarriers and L is the number of OFDM symbols. R is the number of receive antennas. P is the number of layers.
Data Types: double
Complex Number Support: Yes
nVar
— Estimated noise variance
real nonnegative scalar
Estimated noise variance, specified as a real nonnegative scalar.
Data Types: double
Output Arguments
eqSym
— Equalized symbols
2-D numeric matrix
Equalized symbols, returned as an NRE-by-P numeric matrix. NRE is the number of resource elements extracted from each K-by-L plane of the received grid. K is the number of subcarriers and L is the number of OFDM symbols. P is the number of layers.
Data Types: double
Complex Number Support: Yes
csi
— Soft channel state information
2-D numeric matrix
Soft channel state information, returned as an NRE-by-P numeric matrix. NRE is the number of resource elements extracted from each K-by-L plane of the received grid. K is the number of subcarriers and L is the number of OFDM symbols. P is the number of layers. This output is a log-likelihood ratio (LLR) scaling factor that accounts for the SNR in each RE.
Data Types: double
Complex Number Support: Yes
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. (since R2024a)
The nrEqualizeMMSE
function
fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray
(Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced in R2018bR2024a: GPU array support
The nrEqualizeMMSE
function now supports GPU arrays. For more
information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
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