Optimal Threshold Selection of Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks

Abstract

Recent progress in various wireless services such as device-to-device (D2D) communication, anytime anywhere access to multimedia content on smart phones, have driven explosive demand of data traffic. In addition, new frequency spectrum is required to provide these different wireless services to the end users resulting inadequacy of required radio spectrum. However, as per the Federal Communication Committee (FCC) report, the allocated spectrum is not utilized efficiently due to fixed spectrum assignment policy which has resulted the spectrum scarcity problem. In the fixed spectrum assignment policy, the dedicated spectrum (licensed channel) is allocated to the users called licensed/primary users and other unlicensed users are not allowed to access that dedicated spectrum. Therefore, the demand of dynamic spectrum allocation (DSA) strategy has been developed, which also allows the unlicensed users to access the licensed channel without affecting the communication of licensed users. Cognitive Radio (CR) technology is a promising technology which has the potential to address frequency requirements by employing DSA and improve spectrum efficiency. Various spectrum sensing techniques can be employed by CR in order to sense the status of licensed channels being active/busy or idle. The energy detector spectrum sensing (EDSS) is one of the potential spectrum sensing technique, majorly employed by various researchers due to its low computation complexity and easy implementation over other techniques. Further, it is a blind spectrum sensing method which does not require prior knowledge of the primary user (PU) signal. Due to its inherent advantages, we have employed EDSS based CR system in this thesis. The spectrum sensing decision in energy detector spectrum sensing relies on the sensing threshold consequently, the computation and selection of sensing threshold is a very prominent aspect. In addition, the key spectrum sensing performance metrics of CR are the false-alarm and detection probabilities.