Abstract
A Markovian battery model for energy harvesting (EH) secondary users (SUs) is proposed to derive the probability of packet loss due to sensing inaccuracy and energy outage in the EH cognitive radio network (CRN). With the proposed analysis, the packet loss probability can easily be predicted and utilized to optimize the transmission policy (i.e., opportunities for successful transmission and EH) of EH SUs to improve their throughput. Especially, the proposed method can be applied to upper layer (scheduling and routing) optimization. To this end, we validate the proposed analysis through Monte-Carlo simulation and show an agreement between the analysis and simulation results.
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