IEEE Access (Jan 2019)
Achievable Throughput Analysis and Channel Access in Energy Harvesting Cognitive Radio Sensor Network
Abstract
In this paper, we consider an energy harvesting cognitive radio sensor network (EH-CRSN), which is composed of multiple secondary users (sensor nodes) opportunistically access licensed channels. We first propose a novel single-sink EH-CRSN and derive its network throughput. Then, we extend the EH-CRSN to the multi-sink case which will cause interference among secondary communications. To deal with this problem, we optimize channel access schedule, so as to maximize the network throughput in many actual large-scale scenarios. Specifically, we formulate a mixed interaction game and demonstrated the existence of Nash equilibrium. A stochastic learning automata (SLA)-based channel selecting an algorithm is further proposed to achieve the Nash equilibrium. Finally, the simulation results verify the validity of network throughput function in single-sink EH-CRSN and show that the proposed solution can get the maximum or near-maximum system throughput.
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