Log In Sign Up

Tensor-Based Modulation for Unsourced Massive Random Access

by   Alexis Decurninge, et al.

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 decoding. 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.


page 1

page 2

page 3

page 4


Tensor Decomposition Bounds for TBM-Based Massive Access

Tensor-based modulation (TBM) has been proposed in the context of unsour...

A Tensor Rank Theory, Full Rank Tensors and The Sub-Full-Rank Property

A matrix always has a full rank submatrix such that the rank of this mat...

A Bayesian Tensor Approach to Enable RIS for 6G Massive Unsourced Random Access

This paper investigates the problem of joint massive devices separation ...

Understanding Deflation Process in Over-parametrized Tensor Decomposition

In this paper we study the training dynamics for gradient flow on over-p...

Unsourced Random Access with a Massive MIMO Receiver Using Multiple Stages of Orthogonal Pilots

We study the problem of unsourced random access (URA) over Rayleigh bloc...

Constant Weight Codes with Gabor Dictionaries and Bayesian Decoding for Massive Random Access

This paper considers a general framework for massive random access based...