Massive Unsourced Random Access Based on Bilinear Vector Approximate Message Passing

Abstract

This paper introduces a new algorithmic solution to the massive unsourced random access (mURA) problem. The proposed uncoupled compressed sensing (UCS)-based scheme relies on slotted transmissions and takes advantage of the inherent coupling provided by the users' spatial signatures in the form of channel correlations across slots to completely eliminate the need for concatenated coding. As opposed to all existing methods, the proposed solution combines the steps of activity detection, channel estimation, and data decoding into a unified mURA framework. It capitalizes on the bilinear vector approximate message passing (Bi-VAMP) algorithm, tailored to fit the inherent constraints of mURA. Exhaustive computer simulations demonstrate that the proposed scheme outperforms recent coupled and uncoupled mURA schemes in massive connectivity/MIMO setup.