Title
Tensor-Based Modulation for Unsourced Massive Random Access
Abstract
We introduce a modulation for unsourced massive random access whereby the transmitted symbols are rank-1 tensors constructed from Grassmannian sub-constellations. The use of a low-rank tensor structure, together with tensor decomposition in order to separate the users at the receiver, allows a convenient uncoupling between multi-user separation and single-user demapping. The proposed signaling scheme is designed for the block fading channel and multiple-antenna settings, and is shown to perform well in comparison to state-of-the-art approaches.
Year
DOI
Venue
2021
10.1109/LWC.2020.3037523
IEEE Wireless Communications Letters
Keywords
DocType
Volume
Multi-access communication,MIMO,modulation,binary codes,Internet of Things
Journal
10
Issue
ISSN
Citations 
3
2162-2337
6
PageRank 
References 
Authors
0.45
0
3
Name
Order
Citations
PageRank
Alexis Decurninge1317.78
Land Ingmar260.45
Maxime Guillaud331530.64