Abstract
In this paper, we consider an energy harvesting cognitive radio network (CRN), where both of primary user (PU) and secondary user (SU) are operating in time slotted mode, and the SU powered exclusively by the energy harvested from the radio signal of the PU. The SU can only perform either energy harvesting or data transmission due to the hardware limitation. In this case, the entire time-slot is segmented into two non-overlapping fractions. During the first sub-timeslot, the SU can harvest energy from the ambient radio signal when the PU is transmitting. In order to obtain more revenue, the PU leases a portion of its time to SU, while the SU can transmit its own data by using the harvested energy. According to convex optimization, we get the optimal leasing time to maximize the SU’s throughput while guaranteeing the quality of service (QoS) of PU. To evaluate the performance of our proposed spectrum leasing scheme, we compare the utility of PU and the energy efficiency ratio of the entire networks in our framework with the conventional strategies respectively. The numerical simulation results prove the superiority of our proposed spectrum leasing scheme.
Highlights
With the rapid development and extensive application of wireless communication technology, limited spectrum resource and inflexible spectrum assignment policy bring about poor spectrum utilization currently
Another is spectrum leasing which is adopted in this paper, the primary user (PU) is aware of existence of the secondary user (SU) and it can gain some revenue by leasing parts of spectrum to the SU
The utility function of the primary network consists of two elements: the utility associated with the capacity of primary user, and the revenue gained from secondary user by spectrum renting, U p = ω p Ud + Ur
Summary
With the rapid development and extensive application of wireless communication technology, limited spectrum resource and inflexible spectrum assignment policy bring about poor spectrum utilization currently. In [13], the authors considered a cognitive radio sensor network powered by RF energy harvesting and formulated the optimal mode selection (“access” or “harvest”) policy as a partially observable Markov decision process (POMDP). Due to the dynamic and random feature of energy in natural circumstance, we consider merely a scenario that wireless communication device collects energy from ambient wireless signal Compared with these works, the salient feature of this paper is that, by considering the aforementioned trade-offs between energy harvesting and secondary transmission, we investigate the optimal secondary transmission duration time that maximizes the SU’s achievable throughput and further present energy efficiency ratio of the entire network based on the optimal closed-form solutions.
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