Cellular Automata Approach for Spectrum Sensing in Energy Efficient Sensor Network Aided Cognitive Radio

Abstract

Efficient spectrum sensing is an important requirement for the success of the cognitive radio (CR) system. A novel spectrum sensing approach through external sensing is proposed here. In external sensing, an external agent performs the sensing and broadcasts the channel occupancy information to SUs. A large number of low cost and energy efficient wireless sensors can be deployed in the field, to sense the spectrum continuously or periodically. Individual sensing result can be send to the central node (CN) for final decision making through the sensor network. Since we are looking for energy efficient and low cost network installation, individual sensing results are expected to get affected by noise, fading, and shadowing. In this paper we employed a Cellular Automata (CA) based approach at the CN to obtain spectrum status and the correct coverage region of a Primary User (PU). This method requires less number of computations compared to existing fusion rules that are proposed for cooperative spectrum sensing. Impact of sensor density on the percentage false positive and false negative are been carried out. It was also found that with CA based approach the CN can calculate the coverage region of a PU at any point of time accurately with minimum computational effort.