Optimizing AoI in RIS-Aided Wireless Powered Backscatter-Active Communication Networks

In this paper, we investigate the average age of information (AoI) in wireless powered backscatter-active communication networks (WPBACN) assisted by a reconfigurable intelligent surface (RIS). To minimize the average AoI, we jointly optimize the phase shift of the RIS, the backscatter-active communication time allocation factor, and the transmitted power of IoT devices. Since the optimization problem is composed of coupled variables, the optimization variables are implicit in the objective function and the problem is non-convex, which makes it challenging to solve. To address this challenge, we decompose the problem into an RIS phase shift optimization subproblem and a joint power and time allocation subproblem. Simulation results indicate that the proposed scheme has a significant performance advantage in reducing the average AoI compared to the scheme using random RIS phase shifts and the scheme without RIS and supports the challenging quality of service required by real-time information update applications.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-04-29
DOI
https://doi.org/10.1109/tvt.2025.3565588
Citations
6
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
4.38
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article

Optimizing AoI in RIS-Aided Wireless Powered Backscatter-Active Communication Networks

Zhiguo Ding, Ruihong Jiang, Ruichen Zhang, Fan Jiang et al.
6 citations
IEEE Transactions on Vehicular Technology
Energy Harvesting in Wireless Networks
4.38
article

Optimizing AoI in RIS-Aided Wireless Powered Backscatter-Active Communication Networks

Zhiguo Ding, Ruihong Jiang, Ruichen Zhang, Fan Jiang, Dusit Niyato, Huimin Hu
article en
6 citations

Abstract

In this paper, we investigate the average age of information (AoI) in wireless powered backscatter-active communication networks (WPBACN) assisted by a reconfigurable intelligent surface (RIS). To minimize the average AoI, we jointly optimize the phase shift of the RIS, the backscatter-active communication time allocation factor, and the transmitted power of IoT devices. Since the optimization problem is composed of coupled variables, the optimization variables are implicit in the objective function and the problem is non-convex, which makes it challenging to solve. To address this challenge, we decompose the problem into an RIS phase shift optimization subproblem and a joint power and time allocation subproblem. Simulation results indicate that the proposed scheme has a significant performance advantage in reducing the average AoI compared to the scheme using random RIS phase shifts and the scheme without RIS and supports the challenging quality of service required by real-time information update applications.

IEEE Transactions on Vehicular TechnologyVol. 74(9)
Beijing University of Posts and Telecommunications (CN), Nanyang Technological University (SG), Khalifa University of Science and Technology (AE), Xi’an University of Posts and Telecommunications (CN)
Affordable and clean energy
Openalex Percentile: Top 6%
Energy Harvesting in Wireless Networks
4.38
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Optimizing AoI in RIS-Aided Wireless Powered Backscatter-Active Communication Networks — Zhiguo Ding, Ruihong Jiang, et al. · IEEE Transactions on Vehicular Technology (2025) | TGRS Research Map | TGRS