No abstract

This article seeks to advance coded compressed sensing (CCS) as a practical scheme for unsourced random access. The CCS algorithm features a concatenated structure where an inner code is tasked with support recovery and an outer code conducts message disambiguation. Recently, the CCS scheme was improved through the use of approximate message passing (AMP) with a dynamic denoiser that shares soft information between the inner and outer decoders. This significantly improves performance at the cost of additional complexity. This work shows how the spatial coupling generated by the outer code is sufficiently strong to justify relaxing certain constraints on the inner code. It is shown that a block diagonal sensing matrix with the aforementioned dynamic denoiser forms an effective means to get good performance at reduced complexity. This novel architecture can be used to scale CCS to dimensions that were previously impractical. Findings are supported by numerical simulations.Index Terms-Unsourced random access, approximate message passing, coded compressed sensing, concatenated coding.

No 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.