We integrate a wireless powered communication network with a cooperative cognitive radio network,... more We integrate a wireless powered communication network with a cooperative cognitive radio network, where multiple secondary users (SUs) powered wirelessly by a hybrid access point (HAP) help a primary user relay the data. As a reward for the cooperation, the secondary network gains the spectrum access where SUs transmit to HAP using time division multiple access. To maximize the sum-throughput of SUs, we present a secondary sum-throughput optimal resource allocation (STORA) scheme. Under the constraint of meeting target primary rate, the STORA scheme chooses the optimal set of relaying SUs and jointly performs the time and energy allocation for SUs. Specifically, by exploiting the structure of the optimal solution, we find the order in which SUs are prioritized to relay primary data. Since the STORA scheme focuses on the sum-throughput, it becomes inconsiderate towards individual SU throughput, resulting in low fairness. To enhance fairness, we investigate three resource allocation schemes, which are (i) equal time allocation, (ii) minimum throughput maximization, and (iii) proportional time allocation. Simulation results reveal the trade-off between sum-throughput and fairness. The minimum throughput maximization scheme is the fairest one as each SU gets the same throughput, but yields the least SU sum-throughput.
An energy harvesting cognitive radio scenario is considered where a secondary user (SU) with fini... more An energy harvesting cognitive radio scenario is considered where a secondary user (SU) with finite battery capacity opportunistically accesses the primary user (PU) channels. The objective is to maximize the throughput of SU under energy neutrality constraint and fading channel conditions in a single-user multi-channel setting. Channel selection criterion based on the probabilistic availability of energy with SU, channel conditions, and primary network’s belief state is proposed, which chooses the best subset of channels for sensing, yielding higher throughput. We construct channel-aware optimal and myopic sensing strategies in a Partially Observable Markov Decision Process framework based on the proposed channel selection criterion. The effects of sensing errors and collisions between PU and SU on the throughput of latter are studied. It is shown that there exists a trade-off between the transmission duration and the energy lost in collisions.
We integrate a wireless powered communication network with a cooperative cognitive radio network,... more We integrate a wireless powered communication network with a cooperative cognitive radio network, where multiple secondary users (SUs) powered wirelessly by a hybrid access point (HAP) help a primary user relay the data. As a reward for the cooperation, the secondary network gains the spectrum access where SUs transmit to HAP using time division multiple access. To maximize the sum-throughput of SUs, we present a secondary sum-throughput optimal resource allocation (STORA) scheme. Under the constraint of meeting target primary rate, the STORA scheme chooses the optimal set of relaying SUs and jointly performs the time and energy allocation for SUs. Specifically, by exploiting the structure of the optimal solution, we find the order in which SUs are prioritized to relay primary data. Since the STORA scheme focuses on the sum-throughput, it becomes inconsiderate towards individual SU throughput, resulting in low fairness. To enhance fairness, we investigate three resource allocation schemes, which are (i) equal time allocation, (ii) minimum throughput maximization, and (iii) proportional time allocation. Simulation results reveal the trade-off between sum-throughput and fairness. The minimum throughput maximization scheme is the fairest one as each SU gets the same throughput, but yields the least SU sum-throughput.
An energy harvesting cognitive radio scenario is considered where a secondary user (SU) with fini... more An energy harvesting cognitive radio scenario is considered where a secondary user (SU) with finite battery capacity opportunistically accesses the primary user (PU) channels. The objective is to maximize the throughput of SU under energy neutrality constraint and fading channel conditions in a single-user multi-channel setting. Channel selection criterion based on the probabilistic availability of energy with SU, channel conditions, and primary network’s belief state is proposed, which chooses the best subset of channels for sensing, yielding higher throughput. We construct channel-aware optimal and myopic sensing strategies in a Partially Observable Markov Decision Process framework based on the proposed channel selection criterion. The effects of sensing errors and collisions between PU and SU on the throughput of latter are studied. It is shown that there exists a trade-off between the transmission duration and the energy lost in collisions.
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Papers by Jeya Pradha