Energy Management for Energy Harvesting Wireless Sensors with Adaptive Retransmission
Animesh Yadav, Mathew Goonewardena, Wessam Ajib, Octavia A. Dobre and, Halima Elbiaze

TL;DR
This paper proposes an adaptive energy management scheme for energy harvesting wireless sensors that optimizes retransmission and sampling based on available energy, improving communication reliability and efficiency.
Contribution
It introduces a selective sampling scheme combined with a Markov decision process to optimize energy use and retransmission strategies in energy harvesting sensor networks.
Findings
Significant reduction in packet drop probability with the proposed scheme.
Enhanced energy efficiency through adaptive sampling and power control.
Performance gains demonstrated via numerical simulations.
Abstract
This paper analyzes the communication between two energy harvesting wireless sensor nodes. The nodes use automatic repeat request and forward error correction mechanism for the error control. The random nature of available energy and arrivals of harvested energy may induce interruption to the signal sampling and decoding operations. We propose a selective sampling scheme where the length of the transmitted packet to be sampled depends on the available energy at the receiver. The receiver performs the decoding when complete samples of the packet are available. The selective sampling information bits are piggybacked on the automatic repeat request messages for the transmitter use. This way, the receiver node manages more efficiently its energy use. Besides, we present the partially observable Markov decision process formulation, which minimizes the long-term average pairwise error…
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