Performance Analysis of Spectrum Sensing Techniques for Cognitive Radio over Wireless Fading Channels

Abstract

With the advance of wireless communications, the problem of bandwidth scarcity has become more prominent. On the other hand, the studies made by FCC (Federal Communications Commission) showed that large portion of the spectrum lies vacant most of the time and that portion is the licensed spectrum band; which is utilized by licensed users only. So, to solve this problem of spectrum under-utilization, FCC (Federal Communications Commission) allowed secondary users to utilize the licensed band when it is not in use and named it as Cognitive Radio. To sense the existence of licensed users, spectrum sensing techniques are used. Energy detection, Matched filter detection and Cyclo-stationary feature detection are the three conventional methods used for spectrum sensing. However there are some drawbacks of these techniques. The performance of energy detector is susceptible to uncertainty in noise power. Matched filter spectrum sensing technique need a dedicated receiver for every primary user. Cyclostationary feature Detection requires lot of computation effort and long observation time. This thesis discusses the conventional energy detection method and proposed improved energy detection method using cubing operation. Also, cyclic prefix based spectrum sensing is discussed in this thesis. Mathematical Description of energy detection and cyclic prefix based spectrum sensing techniques is also illustrated for fading channels. According to the simulations presented in the thesis, an improvement of up to 0.6 times for AWGN Channel and up to 0.4 times for Rayleigh channel; has been achieved as the squaring operation is replaced by cubing operation in an energy detector. Cooperation among the users is a valuable tool in the implementation of the spectrum sensing and it has been found that it improves the performance of energy detection and cyclic prefix based spectrum sensing techniques. By analyzing the plots of Probability of Detection versus Signal–to-Noise Ratio, it has been shown that Cooperative detection improves the performance of conventional energy detection method up to 2.7 times for AWGN Channel and 2.2 times for Rayleigh Channel as compared to single user detection. It has also been observed that the application of Cooperative Detection in improved Energy detection method (using cubing operation) improves the performance up to 1.3 times for AWGN Channel and 2.3 times for Rayleigh Channel as compared to single user detection. An improvement of up to 3.9 times is achieved using cooperative detection in cyclic prefix based spectrum sensing.