LAUSR

In this aticle, an optimal policy is presented to maximize the secondary user's (SU's) throughput in an energy harvesting cognitive radio network with multiple SUs and single primary user (PU). The SU can access the PU's channel in a hybrid interweave/underlay channel access mode using time division multiple access (TDMA) technique. This hybrid access mode combines the benefits of interweave channel access mode of accessing the PU's channel opportunistically with high transmission power to gain high throughput and that of the underlay channel access mode of transmission at any time regardless of the PU's activity with controlled power. Moreover, energy harvesting from ambient sources promotes the SU's device to be portable and self sustainable. To deal with the random environment, the system is modeled as a mixed (full/partial) observable Markov decision process (MOMDP). Moreover, to reduce the solution complexity, the point-based value iteration (PBVI) algorithm is used to solve the proposed model. The simulation results show the superiority of the proposed model compared to other related models in terms of throughput. Based on an insight on the optimal policy of the proposed model and the time complexity comparison with the related models, a couple of suboptimal policies are proposed, namely, a myopic policy, an interweave only policy, and a combined-policy approach.