Abstract
This article focuses on maximizing the anti-jamming sum throughput in a time division multiple access (TDMA)-based reconfigurable intelligent surfaces (RIS)-assisted Wireless-Powered Internet of Things (WP-IoT) network. In this setup, multiple Internet of Things (IoT) devices harvest energy from wireless energy stations (WES) and then utilize the collected energy to upload their own data to an information receiver (IR). The network also includes a jammer that sends jamming signals to the IR, and a RIS is deployed to mitigate this jamming effect and enhance the sum throughput. This study addresses both an upper bound design and a robust design with fractional nonlinear energy harvesting model. The primary optimization goal is to maximize the anti-jamming sum throughput, with the constraints of RIS phase shifts and time scheduling. For both designs, closed-form expressions for time scheduling are derived using the Lagrangian duality and Karush–Kuhn–Tucker (KKT) conditions. The quadratic transformation (QT) technique is used to handle fractional functions within the optimization. Furthermore, the phase shifts are optimized iteratively using the element-wise block coordinate decent (EBCD) and Riemannian manifold optimization (RMO) algorithms. Simulation results are presented to validate the effectiveness of the proposed approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 36730-36746 |
| Number of pages | 17 |
| Journal | IEEE Internet of Things Journal |
| Volume | 12 |
| Issue number | 17 |
| DOIs | |
| Publication status | Published - 2025 |
Keywords
- Anti-jamming design
- element-wise block coordinate decent (EBCD)
- reconfigurable intelligent surfaces (RIS)
- Riemannian manifold optimization (RMO)
- Wireless-Powered Internet of Things (WP-IoT)
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications