Adaptive Power Control for Dense RFID Networks

Abstract

Adaptive power control is a critical challenge in dense radio frequency identification (RFID) environments, where uncontrolled power levels can lead to excessive interference, energy inefficiency, and reduced system performance. This paper presents a robust and scalable adaptive power control framework that dynamically adjusts transmit power levels to optimize energy efficiency, minimize interference, and enhance system throughput. The proposed framework leverages an optimization-driven approach based on real-time environmental feedback, ensuring compliance with regulatory constraints while maintaining optimal performance. A multi-objective optimization strategy is employed to balance several key metrics, including throughput, energy consumption, and fairness, with a Pareto front analysis demonstrating superior trade-offs compared to fixed power strategies. The effectiveness of the proposed approach is validated through extensive simulations and real-world experiments using universal software radio peripheral (USRP) devices in dense RFID deployments. The results show that our framework achieves a 34% reduction in cumulative interference, a 15% improvement in energy efficiency, and a 20% increase in throughput compared to baseline fixed power methods. Furthermore, it converges rapidly, even in dynamic and high-density networks. These improvements make it highly scalable and adaptable to varying reader densities, ensuring reliable performance in large-scale RFID applications such as supply chain management and industrial automation.