Performance enhancement of crwsn

Abstract

The abrupt growth in current wireless technologies and devices has resulted in massive spectrum demands and energy consumption of Wireless Sensor Network (WSN) To mitigate the spectral scarcity and to ensure the energy requirements a cognitive radio enabled WSN is required Since Wireless Sensor Networks usually operates in unlicensed bands acquiring Cognitive Radio into WSN with an energy efficiency is a challenging task However the state of the art technologies applies either reactive spectrum sensing or proactive spectrum sensing approaches to reform spectrum usage based on environment observations The main goal of the thesis is to address the performance of CRSN in terms of various parameters like throughput energy consumption sensing efficiency error probability and energy efficiency Initially a team-based hybrid sensing method is proposed for Cognitive Radio Sensor Networks (CRSNs) which applies both reactive sensing and proactive sensing by a team-based approach First the Secondary Users (SUs) are grouped into teams based on its detection probability of each Primary User (PU) channels Each team is limited to sense a PU channel Next a SU with maximum detection Probability (Pd) called Sensing Representative Node (SRN) is involved in reactive sensing Hence the sensing overheads is avoided and energy consumption is limited By the dynamic channel allocation the SUs throughput is increased Proactive sensing predicts the PU channel occupancies and allows the SU transmission over the vacant PU channels Both simulation and Universal Software Radio Peripheral (USRP) based test bed results show that the proposed Team-Based Hybrid Sensing (TBHS) improves the throughput and energy efficiency of CRSNs by 2% and 4% over the existing sensing methods newline