  A Markovian battery model is proposed to provide the variation of energy
states for energy harvesting (EH) secondary users (SUs) in the EH cognitive
radio networks (CRN). Based on the proposed battery model, we derive the packet
loss probability in the EH SUs due to sensing inaccuracy and energy outage.
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
simulations results.
