Weighted-directed-hypergraph-based spectrum access for energy harvesting cognitive radio sensor network

Abstract

In this paper, we investigate the spectrum access for energy harvesting cognitive radio sensor network (EH-CRSN), where sensor nodes (SNs) connected to different sinks share several channels. To maximize the sum of system energy efficiency (EE) and spectrum efficiency (SE), different from traditional works modeling the interference relationship by binary graph and unweighted hypergraph, we apply a novel weighted directed hypergraph (WDH) to accurately characterize the degree of interference among neighbor SNs and formulate the channel access problem in multi-sink network as a WDH game. We analyze the existence of Nash equilibrium (NE) and design a spectrum access algorithm to achieve the optimal solution which is one of NE. Moreover, simulation results are presented to verify the effectiveness of the proposed algorithm.