International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 02 Issue: 05 | Aug-2015 www.irjet.net p-ISSN: 2395-0072 © 2015, IRJET ISO 9001:2008 Certified Journal Page 64 Detection of Primary User in Cognitive Radio Using Bayesian Approach Padma Sai Prudvi 1 , Lingaiah Jada 2 , M. Siva Kumar 3 1 Pursuing M.Tech, Electronics and Communication, Arjun college of Technology and Science, Telangana, India 2 Head of Department, Electronics and Communication, Arjun college of Technology and Science, Telangana, India 3 Application Engineer, Uni String Tech Solutions, Telangana, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Using cognitive radios (CRs), the secondary users (SUs) is allowed to use the spectrum originally allocated to primary users (PUs) as long as the primary users are not using it temporarily. This operation is called opportunistic spectrum access (OSA). To avoid interference to the primary users, the SUs have to perform spectrum sensing before their attempts to transmit over the spectrum. In this paper we use energy detector, Bayesian detector and Approximate Bayesian detector for digitally modulated primary user to maximize the spectrum utilization, without prior information of transmitted sequence of the primary signals. We provide the performance analysis of the suboptimal detectors in terms of probabilities of detection and false alarm. In spectrum utilization and secondary user’s throughput performance of the Bayesian and approximate Bayesian detector are better when compared with the energy detector. For the performance estimation we use MATLAB simulation environment. Key Words: Bayesian, probability of detection, probability of false alarm, cognitive radio, spectrum sensing, primary user, secondary user. 1. INTRODUCTION The popularity of wireless technologies is skyrocketing as more devices are being connected and more technologies being deployed [9]-[10]. However, the underlying transmission medium of wireless technology, the radio spectrum, is a limited resource. While radio spectrum is theoretically unlimited, the frequency ranges that are suitable for commercial application is limited but required to support an ever increasing consumer base [1]. The term Ǯcognitive radioǯ is given to an emerging wireless access scheme that is Ǯan intelligent wireless communication system that is aware of its surrounding environment to allow changes in certain operating parameters for the objective of providing reliable communication and efficient utilization of the radio interference to PU activity is minimal and confined [2]. Since the first mentioning in 1999 [3], cognitive radio has become the focus of significant research from industry, research centers and universities alike [4]. In fact, the popularity and potential of cognitive radio is acknowledged by IEEE to promote and develop a standard based on cognitive radio technology, Ǯ IEEE ͺͲʹ.ʹʹ wireless region area networks Ǯ, to deliver wireless broadband to regional area using UHF/VHF TV bands between 54-862 MHz in America [5]. Spectrum sensing is the task where the SU identifies possible spectrum opportunities and is one of the most crucial components of cognitive radio. Spectrum sensing is performed by the SU to sense a spectrum of interested, with the objective of detecting the presence of any PU signals to prevent interference and identify spectrum opportunity for secondary access [2, 5].The SU uses spectrum sensing detectors to analyze the signal captured or observed during the sensing period, and based on the detection results, decides whether or not to utilize the spectrum the transmission period. Spectrum sensing results in one of two decisions: false alarm where the SU declares PU is present when the spectrum is empty and detection where the SU correctly declares a PU is using the spectrum. The performance of sensing detection is thus measured through the probability of these two events. Various conventional detectors have been adapted for the application of spectrum sensing for cognitive radio, including energy detector [6], waveform or matched filter based detector [6,7], cyclostationarity-based detector [8], wavelet and time frequency based detector. Each of the detectors have their advantages and disadvantages with varying detection performance, implementation complexity, detection time, assumptions/ requirements on PU signal, etc. 2. Spectrum Sensing Using Energy Detection And Bayesian Detector A). Energy- Detection Based Spectrum Sensing The energy detection method is simple in implementation since it does not require the knowledge about the structure of the primary signal. The energy detection method calculates the energy of the input signal and compares it with a threshold energy value. The signal is