Abstract

The energy-efficient and spectrum-efficient end-to-end transmission of different delay-sensitive data is crucial for the successful deployment of energy harvesting aided wireless mesh backhaul network. In this paper, considering the scenario with time-varying channel state, stochastic harvested energy arrival process and unknown traffic arrival process under grid power constraints, we propose a unified framework for utilizing both physical-layer and network-layer techniques to achieve the maximum data delivery ratio, bandwidth efficiency and harvested energy utilization. We assume the channel gains follow the finite-state Markov channel model, and model the traffic and the harvested energy arrival as Markov processes. We formulate the optimal problem of route selection and resource management as an ant colony optimization. Simulation results show that the proposed strategy achieves an improved performance in terms of average transmission delay, packet delivery ratio, bandwidth efficiency and harvested energy utilization under time-varying network environment.

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