A Compressive Sensing Based Multi-user Detection Algorithm for SIMa-NOMA Systems

Abstract

Multi-User Detection (MUD) for uplink grant-free Non-orthogonal Multiple Access (NOMA) has received much attention recently. In this paper, we consider the scenario in which a Base Station (BS) is equipped with multiple antennas, and propose a Compressive Sensing-based Hard Fusion Algorithm (CS-HFA) to realize MUD. More explicitly, we detect the user activity information by a conventional CS algorithm at each antenna, and then amalgamate the detected user activity information to derive an active user set. Finally, we can use the obtained active user set to estimate the active users' data. The proposed CS- HFA with low complexity for uplink grant-free Single-Input Multiple-Output Non-Orthogonal Multiple Access (SIMO-NOMA) systems can achieve better BER performance than traditional CS-based MUD in the NOMA system with single antenna at the BS.