English

Tensor-Based Modulation for Unsourced Massive Random Access

Information Theory 2020-08-13 v2 math.IT

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 unsourced approaches.

Keywords

Cite

@article{arxiv.2006.06797,
  title  = {Tensor-Based Modulation for Unsourced Massive Random Access},
  author = {Alexis Decurninge and Ingmar Land and Maxime Guillaud},
  journal= {arXiv preprint arXiv:2006.06797},
  year   = {2020}
}
R2 v1 2026-06-23T16:15:21.239Z