Paper ID | D7-S3-T1.1 |
Paper Title |
Multi-Class Unsourced Random Access via Coded Demixing |
Authors |
Vamsi Krishna Amalladinne, Texas A&M University, College Station, United States; Allen Hao, Stefano Rini, National Chiao Tung University, Taiwan; Jean-Francois Chamberland, Texas A&M University, College Station, United States |
Session |
D7-S3-T1: Topics in Multiple Access II |
Chaired Session: |
Tuesday, 20 July, 22:40 - 23:00 |
Engagement Session: |
Tuesday, 20 July, 23:00 - 23:20 |
Abstract |
Unsourced random access (URA) is a recently proposed communication paradigm attuned to machine-driven data transfers. In the original URA formulation, all the active devices share the same number of bits per packet. The scenario where several classes of devices transmit concurrently has so far received little attention. An initial solution to this problem takes the form of group successive interference cancellation, where codewords from a class of devices with more resources are recovered first, followed by the decoding of the remaining messages. This article introduces a joint iterative decoding approach rooted in approximate message passing. This framework has a concatenated coding structure borrowed from the single class coded compressed sensing and admits a solution that offers performance improvement at little added computational complexity. Our findings point to new connections between multi-class URA and compressive demixing. The performance of the envisioned algorithm is validated through numerical simulations.
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