Improved EGC method for increasing detection in cognitive radio networks

Abstract The detrimental effects of shadowing and fading, affect the reliability of single user spectrum sensing in Cognitive Radio Networks. Hence to overcome this issue, cooperative spectrum sensing is performed. Fusion rules play an important role in improving the consistency of cooperative spectrum sensing. In this work, in addition to analysing the different soft fusion rules, an improved Equal Gain Combining method (EGC) is proposed to obtain better detection performance than conventional methods. Here, the number of results reported to Fusion Center also get reduced without loss in detection performance, thereby paving the way for energy conservation. Also the proposed improved EGC method is further modified in to two different schemes such as improved EGC method with conditions 1 and 2 (IEGCC1 and IEGCC2) to address the trade-off between throughput and energy consumption. Simulations have been carried out in MATLAB to compare and justify the performance of the proposed method and the modified schemes along with the conventional ones. It is observed that there is about 44% increase in detection in the proposed improved EGC method than the conventional EGC method, while simulating 20 users with SNR range of -30 to -11 and 48% increase while simulating 10 users with SNR range of -30 to -21 for a global false alarm probability of value 0.1. Also IEGCC2 method is found to have increased detection performance and highest energy efficiency of all the compared methods with about 23.31% increase in detection than the improved EGC method at a false alarm probability of 0.1.