English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Reconfigurable intelligent surfaces (RISs) empowered high-frequency (HF)wireless systems are expected to become the supporting pillar for severalreliability and data rate hungry applications. Such systems are, however,sensitive to misalignment and atmospheric phenomena including turbulence. Mostof the existing studies on the performance assessment of RIS-empowered wirelesssystems ignore the impact of the aforementioned phenomena. Motivated by this,the current contribution presents a theoretical framework for analyzing theperformance of multi-RIS empowered HF wireless systems. More specifically, westatistically characterize the cascaded composite turbulence and misalignmentchannels in terms of probability density and cumulative distribution functions.Building upon the derived analytical expressions, we present novel closed-formformulas that quantify the joint impact of turbulence and misalignment on theoutage performance for two scenarios of high interest namely cascadedmulti-RIS-empowered free space optics (FSO) and terahertz (THz) wirelesssystems. In addition, we provide an insightful outage probability upper-boundfor a third scenario that considers parallel multi-RIS-empowered FSO systems.Our results highlight the importance of accurately modeling both turbulence andmisalignment when assessing the performance of such systems.

Cascaded Composite Turbulence and Misalignment: Statistical  Characterization and Applications to Reconfigurable Intelligent  Surface-Empowered Wireless Systems