Abstract

In this paper, we propose a cognitive radio sensor network with green power beacon (PB) to solve spectrum and energy scarcity problems in the resource-limited wireless sensor networks. In the proposed model, a PB node harvests energy from ambient sources and transmits the harvested energy to cognitive sensor node (CSN) through in-band energy transmission. The CSN uses the received energy to transfer its data to the sink. Resource-constrained condition of sensor network motivates us to deploy random spectrum access scheme to control the interference between primary and secondary networks, and also self-interference inside the secondary network (i.e., between the CSN and the PB). This spectrum access scheme benefits from low hardware complexity and energy consumption. Using tools from queueing theory, we analyze the service rate of the CSN and primary network for both limited-battery as well as infinite-battery CSN. Then, by optimizing the spectrum access parameters of the PB and the CSN, service rate of the CSN is maximized, while the quality of service (QoS) constraint of primary network is satisfied. For each energy harvesting rate and QoS constraint, it is determined whether energy or spectrum or both are limiting the performance of the CSN. This result can be used to adopt proper solutions for improving the performance of the network.

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