tpcdec

Turbo product code (TPC) decoder

Description

example

decoded = tpcdec(llr,N,K) performs 2-D TPC decoding on input log likelihood ratios, llr, using two linear block codes specified by codeword length N and message length K. For a description of 2-D TPC decoding, see Turbo Product Code Decoding.

example

decoded = tpcdec(llr,N,K,S) performs 2-D TPC decoding on the shortened llr using a 2-D TPC decoder specified by codeword length (NK+S) and message length S.

decoded = tpcdec(llr,N,K,S,maxnumiter) performs 2-D TPC decoding for maxnumiter iterations. To use maxnumiter with full-length messages, specify S as empty, [ ].

decoded = tpcdec(llr,N,K,S,maxnumiter,earlyterm) performs 2-D TPC decoding and terminates early if the calculated syndrome or parity-check of the component code evaluates to zero before maxnumiter decoding iterations. To use maxnumiter and earlyterm with full-length messages, specify S as empty, [ ].

example

[decoded,actualnumiter] = tpcdec(___)also returns the actual number of decoding iterations after performing 2-D TPC decoding using any of the prior syntaxes.

Examples

collapse all

Decode an approximate log-likelihood ratio output signal from 16-QAM demodulation.

Begin by encoding a random bit vector using 2-D turbo product coding (TPC) with extended Hamming codes and extended BCH codes.

Specify the (N,K) code pairs to use for TPC encoding.

N = [32;16]; 
K = [21;11]; 

Generate a column vector of random message bits and TPC-encode the message. Specify the message bits as a vector with length equal to the product of the elements in K.

msg = randi([0 1],prod(K),1);
code = tpcenc(msg,N,K);

Apply 16-QAM modulation. Add AWGN to the signal. Demodulate the signal, outputting approximate LLRs.

M = 16;
snr = 10;

txsig = qammod(code,M,'InputType','bit', ...
    'UnitAveragePower',true);

rxsig = awgn(txsig,snr,'measured');

llr = qamdemod(rxsig,M,'OutputType','approxllr', ...
    'UnitAveragePower',true,'NoiseVariance',10.^(-snr/10));

Perform TPC decoding using three iterations. Because the demodulator output is negative bipolar mapped and TPC decoder expects positive bipolar mapped input, the demodulated signal output must be negated at the decoder input. Check the number of bit errors in the decoded signal.

iterations = 3;
decoded = tpcdec(-llr,N,K,[],iterations);

numerr = biterr(msg,decoded)
numerr = 0

Decode a shortened TPC code. Apply QPSK modulation and output the approximate log-likelihood ratio signal obtained from QPSK demodulation.

Begin by encoding a random bit vector using 2-D turbo product coding (TPC) with extended Hamming codes and extended BCH codes.

Specify (N,K) code pairs and S for TPC encoding.

N = [32;32];
K = [21;26];
S = [19;24];

Generate a column vector of random message bits and TPC-encode the message. Specify the shortened message bits as a vector with length equal to the product of the elements in S.

msg = randi([0 1],prod(S),1);
code = tpcenc(msg,N,K,S);

Apply QPSK modulation. Add AWGN to the signal. Demodulate the signal and output approximate LLRs.

M = 4;
snr = 3;

txsig = qammod(code,M,'InputType','bit', ...
    'UnitAveragePower',true);

rxsig = awgn(txsig,snr,'measured');

llr = qamdemod(rxsig,M,'OutputType','approxllr', ...
    'UnitAveragePower',true,'NoiseVariance',10.^(-snr/10));

Perform TPC decoding using two iterations. Because the demodulator output is negative bipolar mapped and TPC decoder expects positive bipolar mapped input, the demodulated signal output must be negated at the decoder input. Check the bit error rate of the decoded signal.

iterations = 2;
decoded = tpcdec(-llr,N,K,S,iterations);

[~,ber] = biterr(msg,decoded)
ber = 0.0066

Decode a shortened TPC code and specify early termination of decoding. Apply QPSK modulation and output the approximate log-likelihood ratio signal obtained from QPSK demodulation.

Begin by encoding a random bit vector using 2-D turbo product coding (TPC) with extended Hamming codes and extended BCH codes. Specify (N,K) code pairs and S for TPC encoding, and a maximum of 10 decoding iterations. Perform QPSK modulation on the signal.

n = [64; 32];
k = [51; 26];
s = [49; 24];
maxnumiter = 10;
M = 4;

msg = randi([0 1],prod(s),1);  % Random bits
code = tpcenc(msg,n,k,s);

txsig = qammod(code,M,'InputType','bit', ...
    'UnitAveragePower',true);

Add noise to the transmitted signal.

snr = 5;
rxsig = awgn(txsig,snr,'measured');

Demodulate the received signal using approximate LLR demapping.

llr = qamdemod(rxsig,M,'OutputType', ...
    'approxllr','UnitAveragePower',true, ...
    'NoiseVariance',10.^(-snr/10));

Specify the maximum number of TPC decoding iterations and return the actual number of iterations performed. Early termination of the TPC decoding is on by default. Display the number of errors and the number of iterations performed.

[decoded,actualNumIter] = tpcdec(-llr,n,k,s,maxnumiter);
numErr = biterr(msg,decoded);
disp(['Terminated after ' num2str(actualNumIter) ' iterations.' ...
    ' Number of errors = ' num2str(numErr) '.']);
Terminated after 4 iterations. Number of errors = 0.

Input Arguments

collapse all

Log likelihood ratios, specified as a column vector.

  • For full-length codes, the length of the input column vector is the product of the elements in N.

  • For shortened codes, the length of the input column vector is the product of the elements in (NK+S).

Data Types: double | single

Codeword length, specified as a two-element integer vector, [NR; NC]. NR represents the number of rows in the product code matrix. NC represents the number of columns in the product code matrix. For more information about NR and NC, see Turbo Product Code Decoding. For a list of valid (N(i), K(i)) code pairs, see More About.

Data Types: double

Message length, specified as a two-element integer vector, [KR; KC]. For a full-length message, the input column vector containing the input LLRs is arranged into a KR-by-KC matrix. KR represents the number of rows in the message matrix. KC represents the number of columns in the message matrix. For more information about KR and KC, see Turbo Product Code Decoding. For a list of valid (N(i), K(i)) code pairs, see More About.

Data Types: double

Shortened message length, specified as a two-element integer vector, [SR; SC]. For a shortened message, the input column vector containing the input LLRs is arranged into an SR-by-SC matrix. SR represents the number of rows in the matrix. SC represents the number of columns in the matrix. For more information about SR and SC, see Turbo Product Code Decoding.

When you specify this parameter, specify N and K vectors for the full-length TPC codes that are shortened to (N(i) – K(i) + S(i), S(i)) codes.

Data Types: double

Maximum number of decoding iterations, specified as a positive integer.

Data Types: double

Enable early termination of decoding, specified as a logical. When earlyterm is true the decoding terminates early if the calculated syndrome or parity-check of the component code evaluates to zero before maxnumiter decoding iterations.

Data Types: double

Output Arguments

collapse all

TPC decoded message, returned as a column vector.

  • For full-length codes, the length of the returned column vector is the product of the elements in K.

  • For shortened codes, the length of the returned column vector is the product of the elements in S.

Data Types: logical

Actual number of decoding iterations performed, returned as a positive integer.

Data Types: double

More About

collapse all

Component Codes

This table lists the supported component code pairs for the row (NR,KR) and column (NC,KC) parameters.

  • NR and KR represent the number of rows in the product code matrix and message matrix, respectively.

  • NC and KC represent the number of columns in the product code matrix and message matrix, respectively.

Within each code type, any two component code pairs can form a 2-D TPC code. The table also includes the error-correction capability for each code pair.

Code typeComponent Code Pairs(NR,KR) and (NC,KC)Error-Correction Capability (T)
Hamming code(255,247)1
(127,120)1
(63,57)1
(31,26)1
(15,11)1
(7,4)1
Extended Hamming code (256,247)1
(128,120)1
(64,57)1
(32,26)1
(16,11)1
(8,4)1
BCH code(255,239)2
(127,113)2
(63,51)2
(31,21)2
(15,7)2
Extended BCH code(256,239)2
(128,113)2
(64,51)2
(32,21)2
(16,7)2
Parity check code(256,255)-
(128,127)-
(64,63)-
(32,31)-
(16,15)-
(8,7)-
(4,3)-

Turbo Product Code Decoding

Turbo product codes (TPC) are a form of concatenated codes used as forward error correcting (FEC) codes. Two or more component block codes, such as systematic linear block codes, are used to construct TPCs. The TPC decoder achieves near-optimum decoding of product codes using Chase decoding and the Pyndiah algorithm to perform iterative soft input, soft output decoding. For a detailed description, see [1] and [2]. This decoder implements an iterative soft input, soft output 2-D product code decoding, as described in [2], using two Linear Block Codes. The decoder expects the soft bit log likelihood ratios (LLRs) obtained from digital demodulation as the input signal.

Note

The TPC decoder expects a positive bipolar mapped input, specifically –1 mapped to 0 and +1 mapped to 1. The output from demodulators in the Communications Toolbox™ is negative bipolar mapping, specifically +1 mapped to 0 and –1 mapped to +1. Therefore, the LLR output from demodulators must be negated to provide the positive bipolar mapped input expected by the TPC decoder.

The TPC decoder decodes either full-length or shortened codes.

 TPC Decoding Full-Length Messages

 TPC Decoding Shortened Messages

References

[1] Chase, D. "Class of Algorithms for Decoding Block Codes with Channel Measurement Information." IEEE Transactions on Information Theory, Volume 18, Number 1, January 1972, pp. 170–182.

[2] Pyndiah, R. M. "Near-Optimum Decoding of Product Codes: Block Turbo Codes." IEEE Transactions on Communications. Volume 46, Number 8, August 1998, pp. 1003–1010.

Extended Capabilities

See Also

Functions

Objects

Blocks

Introduced in R2018a