Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

TL;DR

This paper proposes a novel joint multi-user communication and environment sensing scheme for 6G networks that leverages sparsity in signals and environment, enabling simultaneous data transmission and environment mapping.

Contribution

It introduces an iterative, sliding-window, graph-based algorithm that interweaves multi-user detection with environment sensing using sparsity, a novel approach for integrated communication and sensing.

Findings

Algorithm converges and is effective in simulations.

Exploits sparsity for joint detection and sensing.

Supports continuous environment sensing with user signals.

Abstract

As a potential technology feature for 6G wireless networks, the idea of sensing-communication integration requires the system not only to complete reliable multi-user communication but also to achieve accurate environment sensing. In this paper, we consider such a joint communication and sensing (JCAS) scenario, in which multiple users use the sparse code multiple access (SCMA) scheme to communicate with the wireless access point (AP). Part of the user signals are scattered by the environment object and reflected by an intelligent reflective surface (IRS) before they arrive at the AP. We exploit the sparsity of both the structured user signals and the unstructured environment and propose an iterative and incremental joint multi-user communication and environment sensing scheme, in which the two processes, i.e., multi-user information detection and environment object detection, interweave with each other thanks to their intrinsic mutual dependence. The proposed algorithm is sliding-window based and also graph based, which can keep on sensing the environment as long as there are illuminating user signals. The trade-off relationship between the key system parameters is analyzed, and the simulation result validates the convergence and effectiveness of the proposed algorithm.