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

Autor:	Amalladinne, Vamsi K., Ebert, Jamison R., Chamberland, Jean-Francois, Narayanan, Krishna R.
Rok vydání:	2021
Předmět:	Computer Science - Information Theory
Druh dokumentu:	Working Paper
Popis:	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. Comment: Submitted to MDPI Sensors
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2112.00270 Zobrazit plný text záznamu View this record from Arxiv