Cooperative Cognitive Wireless Communications Systems

Abstract

ABSTRACT: Cognitive wireless communications is used recently to improve the spectrum utilization. The main work of this thesis is focusing on a challenging research topic in this field which is the cooperation between different users within one cognitive network to improve spectrum sensing for the network. Instead of targeting a certain probability of detection or a certain probability of false alarm, this thesis is presenting the network spectral efficiency rate as a new target of cooperative spectrum sensing. A constant spectral efficiency rate should yield a constant throughput rate of the network. Targeting several spectral efficiency rates using different network sizes, window lengths, received signal-to-noise values, and different fusion rules is investigated in this thesis. The maximum probability of detection can be achieved using an optimal number of cooperated users with the highest signal-to-noise ratio less than the total network users and using a window length shorter than the total allowable sensing window. Moreover, It is proved that modifying the previous hard decision scheme into a soft decision weighted scheme will improve the achieved maximum probability of detection of the network. The weights added to the sensing results are optimized using the optimization of the modified deflection coefficient. Although the weighted network needs to cooperate all users to reach the maximum probability of detection, an optimal sensing window length less than the total allowable sensing window could be achieved.