الفهرس 
Overview of Cognitive Radio NetworkOnly 14 pages are availabe for public view
Abstract
Cognitive Radio Network (CRN) is a future promising technology that allows efficient utilization of the available radio spectrum. Thus solving the problem of spectrum scarcity will be fulfilled. Intensive researches in the field of CR are greatly needed to minimize system errors and accommodate the growing number of users in the presence of limited spectrum resources. There are two types of users: Primary Users (PUs) and Secondary Users (SUs). SU tries to fill the band which is not used by PU.
Detection of the used channel by SUs is a crucial step in cognitive radio that can be achieved in many ways such as matched filter detection, energy detection and cyclostationary detection. These types of detections are non cooperative detections. Simply, exploiting energy detector provides a low complex pathway for detection of vacant channel but it has some drawbacks such as poor performance at low signal to noise ratio. One of the valuable solutions to overcome this disadvantage is using multiple antennas processing based on energy detector with different decision rules.
To improve the performance of the system, relay node will be used. Proposed Adaptive Relay Protocol (ARP) based on signal to noise ratio will be applied to minimize the problems of noise amplification and error propagation that occur in Amplify and Forward (AF) and Decode and Forward (DF) protocols, respectively.
Another method to enhance the performance of CRN is Cooperative Cognitive Relay Network (CCRN) where there is a mutual benefit to both primary users (PUs) and Secondary Users (SUs) by cooperation between them. MIMO-CCRN is proposed to improve the primary and secondary links utilization. Finally, Adaptive Array Antenna (AAA) in cognitive relay network is proposed to reduce the symbol error rate and improve the system performance. Many algorithms such as Wiener Solution and Least Mean Square (LMS) are applied to show the evaluation of AAA in cognitive relay network that achieves this object. AAA at different locations will be studied under AWGN and Rayleigh fading channel. Furthermore, increasing the number of AAA element at the relay node and antenna gain of the source node are proposed to enhance the system efficiency. In addition, increasing the rate adaptation in LMS algorithm is adopted to improve performance of the system.