Level crossing rate analysis for optimal single-user RIS systems

Amy S. Inwood, Peter Smith, Philippa A. Martin, Graeme K. Woodward

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We analyse the level crossing rate (LCR) of an uplink single-user (SU) reconfigurable intelligent surface (RIS) aided system. It is assumed that the RIS to base station (RIS-BS) channel is deployed as line-of-sight (LoS), and the user (UE)-RIS and UE-BS channels are correlated Rayleigh. For the optimal RIS reflection matrix, we derive a novel and exact analytical LCR expression for when the direct (UE-BS) channel is blocked, i.e. the RIS-only channel. Also, the existing exact expression for the direct-only channel (equivalent to classical maximal-ratio-combining (MRC)) suffers from extreme numerical precision problems when the BS has many elements. Therefore, we propose a new stable and accurate approximation to the LCR of the direct channel. The approximation is based on replacing any small similar eigenvalues of the channel correlation matrix by their average. We show that increasing the number of elements at the RIS or BS and decreasing channel correlation makes the LCR drop more rapidly for thresholds away from the mean SNR. Crucially, we find that RIS systems do not significantly amplify temporal variations in the channel. This is particularly beneficial for RIS systems considering the difficulty in acquiring channel state information (CSI).
Original languageEnglish
Title of host publicationGLOBECOM 2024 - 2024 IEEE Global Communications Conference: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2545-2550
Number of pages6
DOIs
Publication statusPublished - 11 Mar 2025
Externally publishedYes

Publication series

NameGLOBECOM IEEE Global Communications Conference: Proceedings
PublisherIEEE
ISSN (Print)1930-529X
ISSN (Electronic)2576-6813

Fingerprint

Dive into the research topics of 'Level crossing rate analysis for optimal single-user RIS systems'. Together they form a unique fingerprint.

Cite this