Exact statistics and tight approximations for RIS-assisted communications in generalized fading environments

Maria Cecilia Luna Alvarado, Carlos Rafael Nogueira Da Silva, Nidhi Simmons, Paschalis C. Sofotasios, Simon L. Cotton, Michel Daoud Yacoub

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

Abstract

Reconfigurable Intelligent Surfaces (RISs) are considered a key candidate technology for next-generation 6G wireless systems, promising to extend network coverage, enhance spectral efficiency, and effectively mitigate interference. RISs will achieve this by controlling the propagation environment, enabled by carefully altering the reflective properties of their elements. In this context, this work presents a general framework for deriving the exact probability density function (PDF) and higher-order moments of the signal-to-ratio (SNR) in a RIS system, considering the direct transmission and RIS-assisted links from source to destination. Recognizing the analytical challenges associated with obtaining exact statistics for RIS-assisted systems, which persist in both common and more generalized fading models, the proposed contribution is realized with the aid of the suitable α-μ fading model. To that end, we derive accurate approximations for the κ-μ and the extended η-μ distributions, which constitute effective and versatile multipath fading models. Based on this, the achieved results are virtually indistinguishable from those obtained through simulations for various environmental settings. This renders the proposed framework a valuable tool for evaluating the performance of RIS systems, particularly in terms of the corresponding average symbol error rate (ASER). Tractable closed-form asymptotic expressions are also derived and utilized to provide a deeper understanding of the system's behavior.
Original languageEnglish
Title of host publication2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall): Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331517786
ISBN (Print)9798331517793
DOIs
Publication statusPublished - 28 Nov 2024

Publication series

NameIEEE Vehicular Technology Conference: Proceedings
ISSN (Print)1550-2252
ISSN (Electronic)2577-2465

Keywords

  • cascaded channels
  • product distribution
  • reconfigurable intelligent surfaces
  • α-μ distribution

Fingerprint

Dive into the research topics of 'Exact statistics and tight approximations for RIS-assisted communications in generalized fading environments'. Together they form a unique fingerprint.

Cite this