wlanVHTDataRecover

Recover bits from VHT-Data field

Syntax

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT)

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT,userIdx)

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT,userIdx,numSTS)

dataBits = wlanVHTDataRecover(___,Name,Value)

[dataBits,crcBits] = wlanVHTDataRecover(___)

[dataBits,crcBits,eqSym] = wlanVHTDataRecover(___)

[dataBits,crcBits,eqSym,cpe] = wlanVHTDataRecover(___)

Description

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT) recovers dataBits, a column vector of bits, from rxDataSig, the received VHT-Data field of a very-high-throughput (VHT) single-user transmission. The function recovers dataBits by using chEst, a channel estimate for the occupied subcarriers, noiseVarEst, an estimate of noise variance, and cfgVHT, a configuration object that contains VHT transmission parameters.

For more information about the VHT-Data field, see VHT-Data Field.

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT,userIdx) recovers dataBits for one user, specified by user index userIdx, in a VHT multi-user transmission.

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT,userIdx,numSTS) recovers dataBits for one user in a VHT multi-user transmission for numSTS, the number of space-time streams in the transmission.

dataBits = wlanVHTDataRecover(___,Name,Value) specifies algorithm options by using one or more name-value pair arguments, in addition to any input argument combination from previous syntaxes. For example, 'LDPCDecodingMethod','layered-bp' specifies the layered belief propagation low-density parity-check (LDPC) decoding algorithm.

[dataBits,crcBits] = wlanVHTDataRecover(___) returns the VHT-SIG-B checksum bits, crcBits, using any input argument combination from previous syntaxes.

[dataBits,crcBits,eqSym] = wlanVHTDataRecover(___) returns eqSym, the equalized OFDM symbols that comprise the data subcarriers of the VHT-Data field, using any input argument combination from the previous syntaxes.

[dataBits,crcBits,eqSym,cpe] = wlanVHTDataRecover(___) returns cpe, the common phase error between the received and expected OFDM symbols, using any input argument combination from the previous syntaxes.

Examples

Recover Bits from VHT Signal Transmitted Through 2x2 Fading Channel

Recover bits from the VHT-Data field of a VHT waveform transmitted though a 2x2 fading channel by using channel estimation on the VHT long training field (VHT-LTF).

Configure a VHT transmission with a channel bandwidth of 160 MHz, two transmit antennas, and two transmission paths.

cfgVHT = wlanVHTConfig('ChannelBandwidth','CBW160','NumTransmitAntennas',2,'NumSpaceTimeStreams',2,'APEPLength',512);

Generate VHT-LTF and VHT-Data fields signals.

psduLength = 8*cfgVHT.PSDULength;
bits = randi([0 1],psduLength,1);
txLTF  = wlanVHTLTF(cfgVHT); 
txDataSig = wlanVHTData(bits,cfgVHT);

Pass the transmitted waveform through a 2x2 quasi-static fading channel with additive white Gaussian noise (AWGN).

snr = 10;
H = complex(randn(2,2),randn(2,2))/sqrt(2);
rxLTF  = awgn(txLTF*H,snr);
rxDataSig = awgn(txDataSig*H,snr);

Calculate the received signal power and estimate the noise variance.

powerDB = 10*log10(var(rxDataSig));
noiseVarEst = mean(10.^(0.1*(powerDB-snr)));

Perform channel estimation based on the VHT-LTF.

sym = wlanVHTLTFDemodulate(rxLTF,cfgVHT,1);
chEst = wlanVHTLTFChannelEstimate(sym,cfgVHT);

Recover the bits from the received VHT-Data field and confirm that the received bits match the transmitted bits.

dataBits = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT);
numErr = biterr(bits,dataBits)

numErr = 0

Recover Bits from VHT Signal Transmitted through MU-MIMO Channel

Recover bits from the VHT-Data field of a VHT multi-user transmission recovered from a fading MU-MIMO channel by using channel estimation on the VHT-LTF.

This example can return high bit error rates because the transmission does not include precoding to mitigate the interference between space-time streams. However, the example shows a typical VHT signal recovery workflow and appropriate syntax use for the functions involved.

Configure a VHT transmission with a channel bandwidth of 160 MHz, two users, and four transmit antennas. Assign one space-time stream to the first user and three space-time streams to the second user.

cbw = 'CBW160';
numSTS = [1 3];
cfgVHT = wlanVHTConfig('ChannelBandwidth',cbw,'NumUsers',2, ...
    'NumTransmitAntennas',4,'NumSpaceTimeStreams',numSTS);

Generate a payload of bits for each user. This payload must be in the a 1-by-N cell array, where N is the number of users.

psduLength = 8*cfgVHT.PSDULength;
numUsers = cfgVHT.NumUsers;
bits = cell(1,2);
for nu = 1:numUsers
    bits{nu} = randi([0 1],psduLength(nu),1);
end

Generate VHT-LTF and VHT-Data field signals.

txLTF  = wlanVHTLTF(cfgVHT); 
txDataSym = wlanVHTData(bits,cfgVHT);

Pass the VHT-Data field signal for the first user through a 4x1 channel because this signal consists of a single space-time stream. Pass the VHT-Data field for the second user data through a 4x3 channel because this signal consists of three space-time streams. Apply AWGN to each signal, assuming an SNR of 15 dB.

snr = 15; 
H{1} = complex(randn(4,1),randn(4,1))/sqrt(2);
H{2} = complex(randn(4,3),randn(4,3))/sqrt(2);
number = zeros(2,1);
ratio = zeros(2,1);
for userIdx = 1:numUsers
    rxDataSym = awgn(txDataSym*H{userIdx},snr,'measured');

Apply the same channel processing to the VHT-LTF for each user.

    rxLTF = awgn(txLTF*H{userIdx},snr,'measured');

Calculate the received signal power for each user and estimate the noise variance.

    powerDB = 10*log10(var(rxDataSym));
    noiseVarEst = mean(10.^(0.1*(powerDB-snr)));

Estimate the channel characteristics by using the VHT-LTF.

    demod = wlanVHTLTFDemodulate(rxLTF,cbw,numSTS);
    chEst = wlanVHTLTFChannelEstimate(demod,cbw,numSTS);

Recover the bits from the received VHT-Data field for each user and determine the bit error rate by comparing the recovered bits with the original payload bits.

    dataBits = wlanVHTDataRecover(rxDataSym,chEst,noiseVarEst,cfgVHT,userIdx);
    [number(userIdx),ratio(userIdx)] = biterr(bits{userIdx},dataBits);
    disp(number(userIdx))
    disp(ratio(userIdx))
end

        4269

    0.5082

        2444

    0.0968

Recover Bits from VHT-Data Field Using Zero-Forcing Equalization

Recover bits from the VHT-Data field signal of a VHT transmission recovered from a SISO AWGN channel by using a zero-forcing equalization algorithm.

Configure a VHT transmission and generate the VHT-Data field for a random payload of bits.

cfgVHT = wlanVHTConfig('APEPLength',512);
psduLength = 8*cfgVHT.PSDULength;
bits = randi([0 1],psduLength,1); 
txDataSig = wlanVHTData(bits,cfgVHT);

Pass the transmission through an AWGN channel.

snr = 10;
rxDataSig = awgn(txDataSig,snr);

Recover the payload bits using a perfect channel estimate of all ones and zero-forcing equalization.

chEst = ones(242,1);
noiseVarEst = 10^(-snr/10);
[dataBits,crcBits,eqSym,cpe] = wlanVHTDataRecover(rxDataSig,chEst,noiseVarEst,cfgVHT,'EqualizationMethod','ZF');

Verify that the recovered signal contains no bit errors.

number = biterr(bits,dataBits)

number = 0

Display the VHT-Data field CRC checksum bits.

disp(crcBits')

   1   1   0   1   0   1   1   0

Calculate and display the maximum common phase error.

max(abs(cpe))

ans = 0.2828

Input Arguments

rxDataSig — Received VHT-Data field

complex-valued array

Received VHT-Data field, specified as a complex-valued array of size N_S-by-N_R.

• N_S is an integer greater than or equal to the number of time-domain samples.

• N_R is the number of receive antennas.

Note

The function processes one PPDU data field per entry. If you specify N_S as a value greater than the field length, the function does not process additional samples at the end of rxDataSig. To process a concatenated stream of PPDU data fields, you must call the function multiple times.

Data Types: double
Complex Number Support: Yes

chEst — Channel estimate for occupied subcarriers

complex-valued array

Channel estimate for occupied subcarriers, specified as a complex-valued array of size N_ST-by-N_STS-by-N_R.

• N_ST is the number of occupied subcarriers, which depends on the ChannelBandwidth property of the cfgVHT input in accordance with this table.

  Value of ChannelBandwidth Property	Value of NST
  'CBW20'	56
  'CBW40'	114
  'CBW80'	242
  'CBW160'	484

• N_STS is the number of space-time streams, which must match the NumSpacetimeStreams property of the cfgVHT input. For multi-user transmissions, N_STS is the total number of space-time streams for all users.

• N_R is the number of receive antennas.

Data Types: double
Complex Number Support: Yes

noiseVarEst — Noise variance estimate

nonnegative scalar

Noise variance estimate, specified as a nonnegative scalar.

Data Types: double

cfgVHT — VHT transmission configuration

wlanVHTConfig object

VHT transmission configuration, specified as a wlanVHTConfig object.

userIdx — User index

integer in the interval [1, N_Users]

User index, specified as an integer in the interval [1, N_Users], where N_Users is the total number of users in the transmission.

numSTS — Number of space-time streams

integer in the interval [1, 4] | row vector of integers in the interval [1, 4]

Number of space-time streams.

• For a single-user transmission, specify this input as an integer in the interval [1, 4]

• for a multi-user transmission, specify this input as a row vector of integers in the interval [1, 4] of length N_Users, where N_Users is the total number of users in the transmission.

Example: [1 3 2] indicates the number of space-time streams in a three-user transmission. In this case, the transmission allocates one, three, and two space-time streams to the first, second, and third users, respectively.

Note

The sum of the elements of this property must not exceed eight.

Data Types: double

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'PilotPhaseTracking','None' disables pilot phase tracking.

'OFDMSymbolOffset' — OFDM symbol sampling offset

0.75 (default) | scalar in the interval [0, 1]

OFDM symbol sampling offset represented as a fraction of the cyclic prefix (CP) length, specified as the comma-separated pair consisting of 'OFDMSymbolOffset' and a scalar in the interval [0, 1]. The value you specify indicates the start location for OFDM demodulation relative to the beginning of the CP. The value 0 represents the start of the CP, and the value 1 represents the end of the CP.

Data Types: double

'EqualizationMethod' — Equalization method

'MMSE' (default) | 'ZF'

Equalization method, specified as the comma-separated pair consisting of 'EqualizationMethod' and one of these values.

• 'MMSE' — The receiver uses a minimum mean-square error equalizer.

• 'ZF' — The receiver uses a zero-forcing equalizer.

Note

Specify this argument as 'ZF' when either of these conditions applies.

• The NumSpaceTimeStreams property of the cfgVHT input is 1.

• The NumSpaceTimeStreams and STBC properties of the cfgVHT input are 2 and 1 (true), respectively.

Data Types: char | string

'PilotPhaseTracking' — Pilot phase tracking

'PreEQ' (default) | 'None'

Pilot phase tracking, specified as the comma-separated pair consisting of 'PilotPhaseTracking' and one of these values.

• 'PreEQ' — Enable pilot phase tracking, which the function performs before any equalization operation.

• 'None' — Disable pilot phase tracking.

Data Types: char | string

'LDPCDecodingMethod' — LDPC decoding algorithm

'bp' (default) | 'layered-bp' | 'norm-min-sum' | 'offset-min-sum'

LDPC decoding algorithm, specified as the comma-separated pair consisting of 'LDPCDecodingMethod' and one of these values.

• 'bp' — Use the belief propagation (BP) decoding algorithm. For more information, see Belief Propagation Decoding.

• 'layered-bp' — Use the layered BP decoding algorithm, suitable for quasi-cyclic parity check matrices (PCMs). For more information, see Layered Belief Propagation Decoding.

• 'norm-min-sum' — Use the layered BP decoding algorithm with the normalized min-sum approximation. For more information, see Normalized Min-Sum Decoding.

• 'offset-min-sum' — Use the layered BP decoding algorithm with the offset min-sum approximation. For more information, see Offset Min-Sum Decoding.

Note

When you specify this input as 'norm-min-sum' or 'offset-min-sum', the function sets input log-likelihood ratio (LLR) values that are greater than 1e10 or less than -1e10 to 1e10 and -1e10, respectively. The function then uses these values when executing the LDPC decoding algorithm.

Dependencies

To enable this argument, set the ChannelCoding property of the cfgVHT input to 'LDPC' for the user corresponding to the userIdx input.

Data Types: char | string

'MinSumScalingFactor' — Scaling factor for normalized min-sum LDPC decoding

0.75 (default) | scalar in the interval (0, 1]

Scaling factor for normalized min-sum LDPC decoding, specified as the comma-separated pair consisting of 'MinSumScalingFactor' and a scalar in the interval (0, 1].

Dependencies

To enable this argument, specify the 'LDPCDecodingMethod' name-value pair argument as 'norm-min-sum'.

Data Types: double

'MinSumOffset' — Offset for offset min-sum LDPC decoding

0.5 (default) | nonnegative scalar

Offset for offset min-sum LDPC decoding, specified as the comma-separated pair consisting of 'MinSumOffset' and a nonnegative scalar.

Dependencies

To enable this argument, specify the 'LDPCDecodingMethod' name-value pair argument as 'offset-min-sum'.

Data Types: double

'MaximumLDPCIterationCount' — Maximum number of LDPC decoding iterations

12 (default) | positive integer

Maximum number of LDPC decoding iterations, specified as the comma-separated pair consisting of 'MaximumLDPCIterationCount' and a positive integer.

Dependencies

To enable this argument, set the ChannelCoding property of the cfgVHT input to 'LDPC' for the user corresponding to the userIdx input.

Data Types: double

'EarlyTermination' — Enable early termination of LDPC decoding

false or 0 (default) | true or 1

Enable early termination of LDPC decoding, specified as the comma-separated pair consisting of 'EarlyTermination' and 1 (true) or 0 (false).

• When you set this value to 0 (false), LDPC decoding completes the number of iterations specified by 'MaximumLDPCIterationCount' regardless of parity check status.

• When you set this value to 1 (true), LDPC decoding terminates when all parity checks are satisfied.

Dependencies

To enable this argument, set the ChannelCoding property of the cfgVHT input to 'LDPC' for the user corresponding to the userIdx input.

Data Types: logical

Output Arguments

dataBits — Bits recovered from VHT-Data field

binary-valued column vector

Bits recovered from the VHT-Data field, returned as a column vector of length 8×L_PSDU, where L_PSDU is the length of the PSDU in bytes.

Data Types: int8

crcBits — VHT-SIG-B checksum bits

binary-valued column vector

VHT-SIG-B checksum bits, returned as a binary-valued column vector of length 8.

Data Types: int8

eqSym — Equalized OFDM symbols

complex-valued array

Equalized OFDM symbols comprising the VHT-Data field, returned as a complex-valued array of size N_SD-by-N_Sym-by-N_SS.

• N_SD is the number of data subcarriers

• N_SYM is the number of OFDM symbols in the VHT-Data field

• N_SS is the number of spatial streams. When the STBC property of the cfgVHT input is 0 (false), N_SS is equal to N_STS, the number of space-time streams in the transmission. When the STBC property of the cfgVHT input is 0 (false), N_SS is equal to N_STS/2.

Data Types: double
Complex Number Support: Yes

cpe — Common phase error

real-valued column vector

Common phase error between the received and expected OFDM symbols, in radians, returned as a real-valued column vector. The length of this output is N_Sym, the number of OFDM symbols in the VHT-Data field.

Data Types: double

More About

VHT-Data Field

The VHT-Data field carries one or more frames from the medium access control (MAC) layer. This field follows the VHT-SIG-B field in a VHT PPDUs.

For a detailed description of the VHT-Data field, see section 21.3.10 of IEEE^® Std 802.11™-2016. The VHT Data field consists of four subfields.

• Service field — Contains a seven-bit scrambler initialization state, one bit reserved for future considerations, and eight bits for the VHT-SIG-B cyclic redundancy check (CRC) field

• PSDU — Variable-length field containing a PLCP service data unit

• PHY Pad — Variable number of bits passed to the transmitter to create a complete OFDM symbol

• Tail — Bits required to terminate a convolutional code (not required when the transmission uses LDPC channel coding)

Algorithms

This function supports these four LDPC decoding algorithms.

Belief Propagation Decoding

The function implements the BP algorithm based on the decoding algorithm presented in [2]. For transmitted LDPC-encoded codeword $$c=\left(c_0,c_1,\dots ,c_{n-1}\right)$$, the input to the LDPC decoder is the LLR given by

$$L\left(c_i\right)=\log \left(\frac{\mathrm{Pr}\left(c_i=0|\text{channel output for }{c}_i\right)}{\mathrm{Pr}\left(c_i=0|\text{channel output for }{c}_i\right)}\right)$$.

In each iteration, the function updates the key components of the algorithm based on these equations:

$$L\left(r_{ji}\right)=2\text{atanh}\left({\displaystyle \prod _{i^{\prime }\in V_j\backslash \left\{i\right\}}\tanh \left(\frac{1}{2}L\left(q_{i^{\prime }j}\right)\right)}\right)$$,

$$L\left(q_{ij}\right)=L\left(c_i\right)+{\displaystyle \sum _{j\text{'}\in C_i\backslash \left\{j\right\}}L\left(r_{j^{\prime }i}\right)}$$, initialized as $$L\left(q_{ij}\right)=L\left(c_i\right)$$ before the first iteration, and

$$L\left(Q_i\right)=L\left(c_i\right)+{\displaystyle \sum _{j^{\prime }\in C_i}L\left(r_{j^{\prime }i}\right)}$$.

At the end of each iteration, $$L\left(Q_i\right)$$ is an updated estimate of the LLR value for the transmitted bit, $$c_i$$. The value $$L\left(Q_i\right)$$ is the soft-decision output for $$c_i$$. If $$L\left(Q_i\right)$$ is negative, the hard-decision output for $$L\left(Q_i\right)$$ is 1. Otherwise, the output is 0.

Index sets $$C_i\backslash \left\{j\right\}$$ and $$V_j\backslash \left\{i\right\}$$ are based on the PCM such that the sets $$C_i$$ and $$V_j$$ correspond to all nonzero elements in column i and row j of the PCM, respectively.

This figure demonstrates how to compute these index sets for PCM $$H$$ for the case i = 5 and j = 3.

To avoid infinite numbers in the algorithm equations, atanh(1) and atanh(–1) are set to 19.07 and –19.07, respectively. Due to finite precision, MATLAB^® returns 1 for tanh(19.07) and –1 for tanh(–19.07).

When you specify the 'EarlyTermination' name-value pair argument as 0 (false), the decoding terminates after the number of iterations specified by the 'MaximumLDPCIterationCount' name-value pair argument. When you specify the 'EarlyTermination' name-value pair argument as 1 (true), the decoding terminates when all parity checks are satisfied ($$H{c}^T=0$$) or after the number of iterations specified by the 'MaximumLDPCIterationCount' name-value pair argument.

Layered Belief Propagation Decoding

The function implements the layered BP algorithm based on the decoding algorithm presented in Section II.A of [3]. The decoding loop iterates over subsets of rows (layers) of the PCM.

For each row, m, in a layer and each bit index, j, the implementation updates the key components of the algorithm based on these equations.

(1) $$L\left(q_{mj}\right)=L\left(q_j\right)-R_{mj}$$

(2) $$\Psi (x)=\log \left(\left|\tanh \left(x/2\right)\right|\right)$$

(3) $$A_{mj}={\displaystyle \sum _{n\in N(m)\backslash \left\{j\right\}}\Psi }\left(L\left(q_{mn}\right)\right)$$

(4) $$s_{mj}={\displaystyle \prod _{n\in N(m)\backslash \left\{j\right\}}\mathrm{sgn}}\left(L\left(q_{mn}\right)\right)$$

(5) $$R_{mj}=-s_{mj}\Psi \left(A_{mj}\right)$$

(6) $$L\left(q_j\right)=L\left(q_{mj}\right)+R_{mj}$$

For each layer, the decoding equation (6) works on the combined input obtained from the current LLR inputs, $$L\left(q_{mj}\right)$$, and the previous layer updates, $$R_{mj}$$.

Because the layered BP algorithm updates only a subset of the nodes in a layer, this algorithm is faster than the BP algorithm. To achieve the same error rate as attained with BP decoding, use half the number of decoding iterations when using the layered BP algorithm.

Normalized Min-Sum Decoding

The function implements the normalized min-sum decoding algorithm by following the layered BP algorithm with equation (3) replaced by

$$A_{mj}={\min }_{n\in N(m)\backslash \left\{j\right\}}\left(\alpha \left|L\left(q_{mn}\right)\right|\right)$$,

where α is the scaling factor specified by the 'MinSumScalingFactor' name-value pair argument. This equation is an adaptation of equation (4) presented in [4].

Offset Min-Sum Decoding

The function implements the offset min-sum decoding algorithm by following the layered BP algorithm with equation (3) replaced by

$$A_{mj}=\max \left({\min }_{n\in N(m)\backslash \left\{j\right\}}\left(\left|L\left(q_{mn}\right)\right|-\beta \right), 0\right)$$,

where β is the offset specified by the 'MinSumOffset' name-value pair argument. This equation is an adaptation of equation (5) presented in [4].

References

[1] IEEE STD 802.11ac™-2013 (Amendment to IEEE Std 802.11-2012, as amended by IEEE Std 802.11ae™-2012, IEEE Std 802.11a™-2012, and IEEE Std 802.11ad™-2012). “Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Amendment 4: Enhancements for Very High Throughput Operation in Bands below 6 GHz.” IEEE Standard for Information technology — Telecommunications and information exchange between systems. Local and metropolitan area networks — Specific requirements.

[2] Gallager, Robert G. Low-Density Parity-Check Codes. Cambridge, MA: MIT Press, 1963.

[3] Hocevar, D.E. "A Reduced Complexity Decoder Architecture via Layered Decoding of LDPC Codes." In IEEE Workshop on Signal Processing Systems, 2004. SIPS 2004., 107-12. Austin, Texas, USA: IEEE, 2004. https://doi.org/10.1109/SIPS.2004.1363033.

[4] Jinghu Chen, R.M. Tanner, C. Jones, and Yan Li. "Improved Min-Sum Decoding Algorithms for Irregular LDPC Codes." In Proceedings. International Symposium on Information Theory, 2005. ISIT 2005., 449-53, 2005. https://doi.org/10.1109/ISIT.2005.1523374.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.