Secure and reliable routing in cognitive radio networks

Due to the mobility of node and different spectrum availability pattern, CR networks are frequently divided into unpredictable partitions. Usually, these partitions are irregularly connected; hence, secure and reliable routing becomes major issue for these types of network. In order to overcome these issues, we propose a secure and reliable routing in CRN based on distributed Boltzmann–Gibbs learning algorithm. This algorithm is implemented for relay node selection phase. In addition, the authentication is done based on secure routing distributed Boltzmann–Gibbs learning algorithm. We consider the metrics such as trust value and total delay for the successful and reliable transmission of the packet. Also, in order to increase the reliability, we implement LDPC code at the time of relay node selection phase. The proposed code helps to cancel any kind of electronic interference and channel noise interference.