Abstract: Low-Density Parity-Check (LDPC) codes offer error correction at rates approaching the link channel capacity and reliable and efficient information transfer over bandwidth or return-channel constrained links with data-corrupting noise present. LDPC codes also offer error correction performance approaching channel capacity exponentially fast in terms of the code length, linear processing complexity, and parallelism that scales with the code length. They also offer challenges relating to the decoding complexity of the binary error-correction codes themselves and error floors limiting achievable bit-error rates. A new Relaxed Half-Stochastic (RHS) decoding algorithm is presented that reduces decoding complexity for high decoding throughput applications. The RHS algorithm uses an approach based on stochastic decoding algorithms but differs significantly from the conventional approaches of LDPC decoder implementation.

Abstract: Low-Density Parity-Check (LDPC) codes offer error correction at rates approaching the link channel capacity and reliable and efficient information transfer over bandwidth or return-channel constrained links with data-corrupting noise present. They also offer performance approaching channel capacity exponentially fast in terms of the code length, linear processing complexity, and parallelism that scales with code length. They also offer challenges relating to decoding complexity and error floors limiting achievable bit-error rates.

Abstract: Low-Density Parity-Check (LDPC) codes offer error correction at rates approaching the link channel capacity and reliable and efficient information transfer over bandwidth or return-channel constrained links with data-corrupting noise present. They also offer performance approaching channel capacity exponentially fast in terms of the code length, linear processing complexity, and parallelism that scales with code length. They also offer challenges relating to decoding complexity and error floors limiting achievable bit-error rates.

Abstract: Low-Density Parity-Check (LDPC) codes offer error correction at rates approaching the link channel capacity and reliable and efficient information transfer over bandwidth or return-channel constrained links with data-corrupting noise present. LDPC codes also offer error correction performance approaching channel capacity exponentially fast in terms of the code length, linear processing complexity, and parallelism that scales with the code length. They also offer challenges relating to the decoding complexity of the binary error-correction codes themselves and error floors limiting achievable bit-error rates. A new Relaxed Half-Stochastic (RHS) decoding algorithm is presented that reduces decoding complexity for high decoding throughput applications. The RHS algorithm uses an approach based on stochastic decoding algorithms but differs significantly from the conventional approaches of LDPC decoder implementation.