Massive MIMO Unsourced Random Access

TL;DR

This paper extends massive unsourced random access to massive MIMO systems with no channel state information, introducing a non-Bayesian activity detection algorithm that outperforms existing Bayesian methods and enables reliable communication at very low energy levels as antennas increase.

Contribution

It proposes a novel non-Bayesian activity detection algorithm for massive MIMO unsourced random access, improving over Bayesian VAMP schemes and enabling reliable communication at low energy levels.

Findings

The proposed algorithm outperforms Bayesian VAMP in activity detection.

Reliable communication is achievable at arbitrarily low energy levels with many antennas.

The method does not require accurate prior statistics or suffer from numerical instabilities.

Abstract

We consider an extension of the massive unsourced random access originally proposed by Polyanskiy to the case where the receiver has a very large number of antennas (a massive MIMO base station) and no channel state information is given to the receiver (fully non-coherent detection). Our coding approach borrows the concatenated coding idea from Amalladinne et. al., combined with a novel non-Bayesian `activity detection' algorithm for massive MIMO random access channels, that outperforms currently proposed Bayesian vector AMP (VAMP) schemes currently proposed for activity detection, and does not suffer from the numerical instabilities and requirement for accurate a priori statistics as VAMP. We show that the required transmit $E_b/N_0$ for reliable communication can be made arbitrarily small as the number of receiver antennas M grows sufficiently large.