An Enhanced Decoding Algorithm for Coded Compressed Sensing with Applications to Unsourced Random Access

TL;DR

This paper introduces an improved decoding algorithm for concatenated coding in unsourced random access, enhancing error performance and reducing computational complexity in distributed sensor networks.

Contribution

It presents a novel enhanced decoding algorithm applicable to a wide range of inner codes and outer tree-based codes, improving performance and efficiency.

Findings

Improved error performance demonstrated through simulations.

Reduced computational complexity of decoding process.

Applicable to existing URA algorithms with measurable benefits.

Abstract

Unsourced random access (URA) has emerged as a pragmatic framework for next-generation distributed sensor networks. Within URA, concatenated coding structures are often employed to ensure that the central base station can accurately recover the set of sent codewords during a given transmission period. Many URA algorithms employ independent inner and outer decoders, which can help reduce computational complexity at the expense of a decay in performance. In this article, an enhanced decoding algorithm is presented for a concatenated coding structure consisting of a wide range of inner codes and an outer tree-based code. It is shown that this algorithmic enhancement has the potential to simultaneously improve error performance and decrease the computational complexity of the decoder. This enhanced decoding algorithm is applied to two existing URA algorithms and the performance benefits of the algorithm are characterized. Findings are supported by numerical simulations.