Joint Localization and Beamforming for Reconfigurable Intelligent Surface Aided 5G mmWave Communication Systems

TL;DR

This paper introduces a joint localization and beamforming optimization algorithm for RIS-assisted 5G mmWave systems, demonstrating improved user localization accuracy and system performance through simulations.

Contribution

It proposes a novel JLBO algorithm for joint localization and beamforming in RIS-aided mmWave systems, addressing the challenge of unknown UE position and CSI.

Findings

RIS improves localization accuracy.

Proposed scheme outperforms traditional methods.

Algorithm convergence is proven.

Abstract

Reconfigurable intelligent surface (RIS) is an attractive technology to improve the transmission rate of millimetre-wave (mmWave) communication systems. The previous {research} on RIS technology mainly focused on improving the transmission rate and security rate of the mmWave communication systems. Since the emergence of RIS technology creates the conditions for generating an intelligent radio environment, it also has potential advantages on improving the localization accuracy of the mmWave communication systems. Deployed on walls and objects, RISs are capable of significantly improving communications and positioning coverage by controlling the multi-path reflection. This paper considers the RIS-aided mmWave localization system and proposes a joint beamforming and localization problem. However, since the objective function depends on the unknown UE's position and instantaneous channel state information (CSI), this beamforming and localization technology based on RIS assistance is challenging. To solve this problem, we propose a new joint localization and beamforming optimization (JLBO) algorithm, and give the proof of its convergence. The simulation results show that the RIS can improve the user localization accuracy of the system and the proposed scheme has a significant performance improvement compared with the traditional schemes.