A FRAMEWORK FOR DATA TRAFFIC IN COGNITIVE RADIO NETWORKS USING TRUSTED TOKEN ANALYZER SCHEME

Abstract

A cognitive radio network is considered as a key technology for future wireless communications. The motivation behind cognitive radio is the effective usage of limited spectrum. Cognitive radio networks are designed to opportunistically exploit the underutilized or unused spectrum bands. Cognitive radio combines sensing, learning, and optimization algorithms to manage and adapt the radio system from the physical layer and up the communication stack. Spectrum Sensing, Spectrum Decision, Spectrum Mobility and Spectrum Sharing, are the four functionalities involved in Cognitive Radio Networks. This paper proposes a framework for data traffic management by considering the QoS requirement of the secondary user and also the primary user activity. The Location information of the primary user in cognitive radio networks can be used to assist the communication among secondary users outside the transmission coverage area of primary users and also for tracking the primary user activities. The objective of the paper is to design a framework which will support the secondary user data transmission while considering the primary user activity and QoS requirement.