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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In the realm of wireless communications in 5G, 6G and beyond, deployingunmanned aerial vehicle (UAV) has been an innovative approach to extend thecoverage area due to its easy deployment. Moreover, reconfigurable intelligentsurface (RIS) has also emerged as a new paradigm with the goals of enhancingthe average sum-rate as well as energy efficiency. By combining theseattractive features, an energy-efficient RIS-mounted multiple UAVs (aerialRISs: ARISs) assisted downlink communication system is studied. Due to theobstruction, user equipments (UEs) can have a poor line of sight to communicatewith the base station (BS). To solve this, multiple ARISs are implemented toassist the communication between the BS and UEs. Then, the joint optimizationproblem of deployment of ARIS, ARIS reflective elements on/off states, phaseshift, and power control of the multiple ARISs-assisted communication system isformulated. The problem is challenging to solve since it is mixed-integer,non-convex, and NP-hard. To overcome this, it is decomposed into threesub-problems. Afterwards, successive convex approximation (SCA), actor-criticproximal policy optimization (AC-PPO), and whale optimization algorithm (WOA)are employed to solve these sub-problems alternatively. Finally, extensivesimulation results have been generated to illustrate the efficacy of ourproposed algorithms.

Energy-Efficient Communication Networks via Multiple Aerial Reconfigurable Intelligent Surfaces: DRL and Optimization Approach