This article introduces a novel paradigm for the unsourced multiple-access communication problem. This divide-and-conquer approach leverages recent advances in compressive sensing and forward error correction to produce a computationally efficient algorithm. Within the proposed framework, every active device first partitions its data into several sub-blocks, and subsequently adds redundancy using a systematic linear block code. Compressive sensing techniques are then employed to recover sub-blocks, and the original messages are obtained by connecting pieces together using a low-complexity tree-based algorithm. Numerical results suggest that the proposed scheme outperforms other existing practical coding schemes. Measured performance lies approximately 4.3~dB away from the Polyanskiy achievability limit, which is obtained in the absence of complexity constraints.
@article{arxiv.1806.00138,
title = {A Coupled Compressive Sensing Scheme for Unsourced Multiple Access},
author = {Vamsi K. Amalladinne and Avinash Vem and Dileep Kumar Soma and Krishna R. Narayanan and Jean-Francois Chamberland},
journal= {arXiv preprint arXiv:1806.00138},
year = {2018}
}