Video over Cognitive Radio Networks: A Cross-Layer Optimization Approach
Type of Degreedissertation
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Cognitive radios (CR) are intelligent radio devices that can sense the radio environment and adapt to changes in the radio environment. CR represents a new paradigm of wireless communications and networking by efficiently sharing spectrum between licensed users and secondary users. To harvest the high potential of CRs, the mainstream CR research has focused on developing effective spectrum sensing and access techniques. Although considerable advances have been achieved, the important problem of guaranteeing application performance has not been well studied. The first part of this dissertation develops effective algorithms and protocols for spectrum sensing and access. First, we present a spectrum sensing error aware MAC protocol for a CR network collocated with multiple primary networks. Second, we consider the problem of interference mitigation via channel assignment and power allocation for CR users. The second part of this dissertation focuses on the problem of optimized video streaming over CR networks. First, we tackle the problem of scalable video multicast in emerging infrastructure-based CR networks. Second, we investigate the more challenging problem of streaming multiple videos over multi-hop CR networks. Cooperative CR networks are discussed in the third part of this dissertation. First, we investigate the problem of cooperative relay in CR networks for further enhanced network performance. Then, we study the problem of cooperative relay in CR networks for video streaming incorporating interference alignment techniques. In the fourth part of this dissertation, we consider femtocell CR networks, where femto base stations (FBS) are deployed to greatly improve network coverage and capacity. First, we investigate the problem of generic data multicast in femtocell networks. Second, we tackle the problem of streaming scalable videos in femtocell CR networks. This dissertation research provides a new perspective on how robust multi-user video streaming can be achieved in highly dynamic CR networks. It is among the first efforts to address the important area of video over CR networks, and offers systematic and comprehensive results and solutions. The findings may shed new light on the feasibility of CR networks in transporting real-time video and be useful for developing practical CR video systems.