A Novel Content Aware Channel Allocation Scheme for Video Applications over CRN

Cognitive radio (CR) has emerged as an effective solution to spectrum scarcity problem which efficiently utilizes the unused spectrum of licensed primary user (PU). Video applications, as a bandwidth intensive and delay-sensitive application, will surely get benefitted from CR technology due to its ability to provide additional bandwidth to end users. In this article we investigate the challenges of quality of experience (QoE) driven video applications over CR networks due to the random behavior of PUs, dynamic characteristic of the primary channels, packet error rate etc. Generally, all video applications could be categorized into three groups like slight motion, gentle walking and rapid motion (RM) and each group has its own quality of service (QoS) requirements. The aim of this paper is to minimize QoE degradation by estimating the quality of the available channels based on our proposed Channel Quality Index metric and then allocating the channels depending on the QoS requirements of a particular video application. Extensive analysis validates that there is a performance enhancement of different video applications, especially RM type (nearly 66%) which is considered as most critical among all.