Modeling Channel Allocation for Multimedia Transmission Over Infrastructure Based Cognitive Radio Networks

Abstract

Multimedia applications have being widely supported by cognitive radio networks in which high bandwidth can be provided by fully utilizing radio spectrum. However, the research communities lack a theoretical modeling and analysis for multimedia system performance over cognitive radio networks. In this paper, a novel Markov-Chain based model of centralized cognitive radio network (CCRN) consisting of APs and user equipments (UEs) equipped with several antennas (one antenna for channel sensing, the others for data communication) is proposed. In the proposed model, AP will scan the idle primary channels (PCs) that are not used by primary users (PUs), and then transmit data through selected idle channels. Each selected channel in CCRN will be divided into many sub-time slots and some of them are used as the signalling control and the other slots are used only for data transmissions. In addition, three types of communications are considered and an appropriate number of time slots are pre-assigned to ensure QoS of multiple types of multimedia traffic. We used a multi-dimension Markov chain to model time slot allocation and proposed a general channel allocation model for multimedia traffic over CCRN. We validated our model through both theoretical analysis and simulations.