2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | W.3.2 | ||
| Paper Title | On Approximate Message Passing for Unsourced Access with Coded Compressed Sensing | ||
| Authors | Vamsi Amalladinne, Asit Kumar Pradhan, Texas A&M University, College Station, United States; Cynthia Rush, Columbia University, United States; Jean-Francois Chamberland, Krishna Narayanan, Texas A&M University, College Station, United States | ||
| Session | W.3: Random Access I | ||
| Presentation | Lecture | ||
| Track | Wireless Communications | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | Sparse regression codes with approximate message passing (AMP) decoding have gained much attention in recent times. The concepts underlying this coding scheme extend to unsourced access with coded compressed sensing (CCS), as first pointed out by Fengler, Jung, and Caire. More specifically, their approach uses a concatenated coding framework with an inner AMP decoder followed by an outer tree decoder. In the original implementation, these two components work independently of each other, with the tree decoder acting on the static output of the AMP decoder. This article introduces a novel framework where the inner AMP decoder and the outer tree decoder operate in tandem, dynamically passing information back and forth to take full advantage of the underlying CCS structure. The enhanced architecture exhibits significant performance benefit over a range of system parameters. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
