When Feedback Empowers the Uplink: Integrating Adaptive Coding with Wireless Power Transfer

2025-05-28

AI Summary

In battery-constrained IoT devices, there exists a fundamental trade-off between feedback accuracy and wireless energy harvesting (WEH), limiting system longevity. Method: This paper proposes FACET, the first framework to deeply integrate adaptive feedback channel coding with wireless power transfer, exploiting the saturation characteristic of feedback links to enable a single feedback signal to simultaneously convey uplink channel state information and deliver energy to the device. Leveraging theoretical analysis of the intrinsic accuracy–energy trade-off, we formulate a min-max net energy consumption optimization problem under fairness constraints; the solution combines saturation-aware feedback coding modeling, Lagrangian duality theory, and an alternating optimization algorithm. Contribution/Results: Experiments demonstrate that FACET extends device lifetime by nearly 3× over conventional schemes while maintaining robustness across a wide range of input power levels.

Technology Category

• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition
• Search and Optimization: Learning to Search
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

Energy consumption and device lifetime are critical concerns for battery-constrained IoT devices. This paper introduces the Feedback-Aided Coding and Energy Transfer (FACET) framework, which synergistically combines adaptive feedback channel coding with wireless power transfer. FACET leverages the saturation effect of feedback coding, where increasing downlink power yields diminishing returns, to design a dual-purpose feedback mechanism that simultaneously guides uplink coding and replenishes device energy. We characterize the inherent tradeoff between feedback precision and harvested power, and formulate a fairness-constrained min-max optimization problem to minimize worst-case net energy consumption. An efficient algorithm based on alternating optimization and Lagrangian duality is developed, with each subproblem admitting a closed-form solution. Simulations show that FACET nearly triples device lifetime compared to conventional feedback coding architectures, and remains robust across a wide range of power regimes. These results suggest that FACET not only improves communication efficiency but also redefines the role of feedback in energy-constrained IoT systems.

Problem

• Minimizes energy consumption in battery-constrained IoT devices
• Integrates adaptive feedback coding with wireless power transfer
• Balances feedback precision and harvested power tradeoff

Innovation

• Combines adaptive feedback coding with wireless power transfer
• Dual-purpose feedback for uplink coding and energy replenishment
• Optimizes feedback precision and harvested power tradeoff