Energy Efficient Cognitive Radio Sensor Networks with Team-Based Hybrid Sensing

Abstract

The massive growth in modern wireless technologies and devices has resulted in increase in spectrum demands and energy consumption of wireless sensor network (WSN). To overcome the spectral scarcity and to meet the energy requirements, a cognitive radio enabled WSN with an energy efficient medium access control protocol is required. However, existing approaches utilize either reactive sense and avoid approach or proactive spectrum access to reconfigure spectrum usage based on observations. In this paper, a team-based hybrid sensing method is proposed for cognitive radio sensor networks (CRSNs), which combines both reactive sensing and proactive sensing in a team based approach. Here, the sensor nodes are grouped into teams based on the detection probability of each primary user (PU) channels and each team senses a PU channel. To avoid sensing overheads and to limit energy consumption, a node with best detection probability $(P_d)$ called sensing representative node (SRN) is involved in reactive sensing. Dynamic channel allocation to the secondary users (SUs) with significantly increased throughput and reduced energy consumption are achieved by using proactive sensing. Proactive sensing predicts the primary user (PU) occupancy using SRNs and allows the SU transmission without any hindrance. Both simulation and software defined radio based hardware results show that, the proposed Hybrid Sensing improves the energy efficiency of CRSNs by $11\%$ over the existing sensing methods without degrading its sensing accuracy.