and vehicle-to-infrastructure (V2I); Deep neural network (DNN); multi-RIS; reconfigurable intelligent surfaces (RIS); simultaneous wireless information and power transfer (SWIPT); And vehicle-to-infrastructure (V2I); Deep neural network; Information and power transfers; Multi-reconfigurable intelligent surface; Neural-networks; Reconfigurable; Reconfigurable intelligent surface; Simultaneous wireless information and power transfer; Vehicle to infrastructure (V2I); Computer Networks and Communications; Electrical and Electronic Engineering
Abstract :
[en] This paper investigates the effectiveness of employing multiple reconfigurable intelligent surfaces (RIS) for simultaneous wireless information and power transfer (SWIPT) in a vehicle-to-infrastructure (V2I) system. The optimal RIS is selected for transmission based on instantaneous signal-to-noise ratio (SNR) values, with the objective of optimizing the SWIPT system employing the power-splitting (PS) protocol and nonlinear energy harvesting (NL-EH). A unified objective is proposed to maximize information rate and harvested energy via joint optimization of transmit power and power splitting factor. Nonconvexity is addressed via an iterative algorithm, supported by closed-form expressions obtained through Karush-Kuhn-Tucker (KKT) conditions. Monte-Carlo simulations are performed to validate the accuracy of the analytical expressions. Additionally, a deep neural network (DNN) framework is introduced for realtime optimization prediction, achieving superior SWIPT performance over single RIS configurations with reduced complexity and faster execution.
Disciplines :
Computer science
Author, co-author :
Kokare, Manojkumar B.; Indian Institute of Technology Indore, Department of Electrical Engineering, India
GAUTAM, Sumit ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust > SigCom > Team Symeon CHATZINOTAS ; Indian Institute of Technology Indore, Department of Electrical Engineering, India
Swaminathan, R.; Indian Institute of Technology Indore, Department of Electrical Engineering, India
Sharma, Neha; Indian Institute of Technology Indore, Department of Electrical Engineering, India
KAUSHIK, Aryan ; University of Luxembourg ; Manchester Met, Department of Computing and Mathematics, United Kingdom
CHATZINOTAS, Symeon ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
External co-authors :
yes
Language :
English
Title :
Optimizing SWIPT in Multi-RIS Aided V2I Networks: A Deep Learning Approach
Publication date :
26 September 2025
Event name :
ICC 2025 - IEEE International Conference on Communications
Event organizer :
IEEE
Event place :
Montreal, Can
Event date :
08-06-2025 => 12-06-2025
By request :
Yes
Audience :
International
Main work title :
ICC 2025 - IEEE International Conference on Communications
Editor :
Valenti, Matthew
Publisher :
Institute of Electrical and Electronics Engineers Inc.
IEEE Communications Society IEEE Montreal Section IEEE Ottawa Section
Funding text :
This work is supported in part by the Prime Minister's Research Fellows (PMRF) scheme and in part by CRG (CRG/2021/0008813) and MATRICS (MTR/2021/000553) schemes of SERB, Govt. of India.
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