Multi-Class Unsourced Random Access via Coded Demixing

TL;DR

This paper introduces a joint iterative decoding method based on approximate message passing for multi-class unsourced random access, improving performance with low complexity and revealing new links to compressive demixing.

Contribution

It presents a novel joint decoding algorithm for multi-class URA using coded demixing, extending existing single-class approaches with performance gains.

Findings

Performance improvements demonstrated through simulations.

Low computational complexity of the proposed decoding method.

New theoretical connections between multi-class URA and compressive demixing.

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.