Abstract
Energy harvesting is a key technology for future energy neutral ubiquitous wireless communication systems. Among the many available sources of energy, RF harvesting is a natural choice for wireless communications since the devices can be efficiently designed for RF harvesting operations. To achieve energy autonomy a rechargeable energy storage is needed. However, the bursty nature of energy arrival associated with wireless power transfer and the energy usage pattern induced by devices’ activity may cause considerable stress to the battery and reduce its life span. In fact, deep charging and discharging cycles degrade the battery state of health, that is, the maximum amount of energy that can be stored. In this paper, a framework for the optimization of wireless nodes’ transmission and charging strategy is presented, where the battery aging rate is made explicit as a performance metric. The proposed framework is based on MDP theory, where the embedded stochastic model captures the energy arrival and data generation processes, and the control variable takes the form of a transmission power selection and energy acceptance/rejection. The tradeoff between the achievable throughput and the aging rate is explored for different parameters setting.
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