On Achievable Rates and Complexity of LDPC Codes for Parallel Channels with Application to Puncturing

TL;DR

This paper analyzes the achievable rates and decoding complexity of LDPC codes over parallel channels, deriving bounds that inform code design and puncturing strategies for reliable communication.

Contribution

It introduces new bounds on achievable rates and decoding complexity for LDPC codes over parallel channels, including punctured codes, under ML and iterative decoding.

Findings

Derived upper bounds on achievable rates for LDPC codes over parallel channels.

Provided a lower bound on decoding complexity per iteration.

Demonstrated the applicability of bounds to various communication scenarios.

Abstract

This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the transmitted codeword given the received sequence at the output of the parallel channels; the component channels are considered to be memoryless, binary-input, and output-symmetric (MBIOS). These results serve for the derivation of an upper bound on the achievable rates of ensembles of LDPC codes under optimal maximum-likelihood (ML) decoding when their transmission takes place over parallel MBIOS channels. The paper relies on the latter bound for obtaining upper bounds on the achievable rates of ensembles of randomly and intentionally punctured LDPC codes over MBIOS channels. The paper also provides a lower bound on the decoding complexity (per iteration) of ensembles of LDPC codes under message-passing iterative decoding over parallel MBIOS channels; the bound is given in terms of the gap between the rate of these codes for which reliable communication is achievable and the channel capacity. The paper presents a diagram which shows interconnections between the theorems introduced in this paper and some other previously reported results. The setting which serves for the derivation of the bounds on the achievable rates and decoding complexity is general, and the bounds can be applied to other scenarios which can be treated as different forms of communication over parallel channels.