Sparsity Learning Based Multiuser Detection in Grant-Free Massive-Device Multiple Access

TL;DR

This paper introduces sparsity learning-based multiuser detection schemes for grant-free massive-device multiple access systems, enabling blind detection of user activity, data, and channels without prior knowledge, thus reducing overhead and improving performance.

Contribution

The paper proposes two novel sparsity-based multiuser detection schemes, RSL-MUD and SSL-MUD, for time-slotted and non-time-slotted grant-free MaDMA systems, respectively, with blind detection capabilities.

Findings

Significant reduction in transmission overhead.

Improved error performance compared to existing schemes.

Effective blind detection of user activity and data.

Abstract

In this work, we study the multiuser detection (MUD) problem for a grant-free massive-device multiple access (MaDMA) system, where a large number of single-antenna user devices transmit sporadic data to a multi-antenna base station (BS). Specifically, we put forth two MUD schemes, termed random sparsity learning multiuser detection (RSL-MUD) and structured sparsity learning multiuser detection (SSL-MUD) for the time-slotted and non-time-slotted grant-free MaDMA systems, respectively. In the time-slotted RSL-MUD scheme, active users generate and transmit data packets with random sparsity. In the non-time-slotted SSL-MUD scheme, we introduce a sliding-window-based detection framework, and the user signals in each observation window naturally exhibit structured sparsity. We show that by exploiting the sparsity embedded in the user signals, we can recover the user activity state, the channel, and the user data in a single phase, without using pilot signals for channel estimation and/or active user identification. To this end, we develop a message-passing based statistical inference framework for the BS to blindly detect the user data without any prior knowledge of the identities and the channel state information (CSI) of the active users. Simulation results show that our RSL-MUD and SSL-MUD schemes significantly outperform their counterpart schemes in both reducing the transmission overhead and improving the error behavior of the system.