Efficient STAR-RIS Mode for Energy Minimization in WPT-FL Networks with NOMA

2025-09-16

AI Summary

This work addresses the joint uplink-downlink energy consumption minimization problem in a STAR-RIS-aided multi-antenna WPT-FL-NOMA system for massive IoT in 6G. To tackle the non-convex, highly coupled optimization, we propose—*for the first time*—a mode selection mechanism for STAR-RIS in WPT-FL-NOMA, jointly optimizing phase-shift configurations (energy-splitting vs. time-switching modes), AP beamforming, wireless resource allocation, and user local computation policies. Leveraging a block coordinate descent framework, we integrate semidefinite relaxation, Rayleigh quotient optimization, one-dimensional search, and bisection for efficient computation. Simulation results demonstrate that the proposed scheme significantly reduces total system energy consumption, enhances energy efficiency and network sustainability. Quantitative analysis further validates the operational regimes: energy-splitting mode excels under high-SNR conditions, whereas time-switching mode better suits ultra-low-power IoT devices.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

With the massive deployment of IoT devices in 6G networks, several critical challenges have emerged, such as large communication overhead, coverage limitations, and limited battery lifespan. FL, WPT, multi-antenna AP, and RIS can mitigate these challenges by reducing the need for large data transmissions, enabling sustainable energy harvesting, and optimizing the propagation environment. Compared to conventional RIS, STAR-RIS not only extends coverage from half-space to full-space but also improves energy saving through appropriate mode selection. Motivated by the need for sustainable, low-latency, and energy-efficient communication in large-scale IoT networks, this paper investigates the efficient STAR-RIS mode in the uplink and downlink phases of a WPT-FL multi-antenna AP network with non-orthogonal multiple access to minimize energy consumption, a joint optimization that remains largely unexplored in existing works on RIS or STAR-RIS. We formulate a non-convex energy minimization problem for different STAR-RIS modes, i.e., energy splitting (ES) and time switching (TS), in both uplink and downlink transmission phases, where STAR-RIS phase shift vectors, beamforming matrices, time and power for harvesting, uplink transmission, and downlink transmission, local processing time, and computation frequency for each user are jointly optimized. To tackle the non-convexity, the problem is decoupled into two subproblems: the first subproblem optimizes STAR-RIS phase shift vectors and beamforming matrices across all WPT-FL phases using block coordinate descent over either semi-definite programming or Rayleigh quotient problems, while the second one allocates time, power, and computation frequency via the one-dimensional search algorithms or the bisection algorithm.

Problem

• Minimizing energy consumption in WPT-FL networks using STAR-RIS
• Optimizing STAR-RIS modes for full-space coverage and energy efficiency
• Jointly managing resources across uplink/downlink transmissions and energy harvesting

Innovation

• STAR-RIS mode selection for full-space coverage
• Joint optimization of phase shift and beamforming matrices
• Time-power-computation allocation via search algorithms