Cross-Layer QoE Improvement with Dynamic Spectrum Allocation in OFDM-Based Cognitive Radio.

PhDRapid development of devices and applications results in dramatic growth of wireless tra c, which leads to increasing demand on wire- less spectrum resources. Current spectrum resource allocation pol- icy causes low e ciency in licensed spectrum bands. Cognitive Ra- dio techniques are a promising solution to the problem of spectrum scarcity and low spectrum utilisation. Especially, OFDM based Cog- nitive Radio has received much research interest due to its exibility in enabling dynamic resource allocation. Extensive research has shown how to optimise Cognitive Radio networks in many ways, but there has been little consideration of the real-time packet level performance of the network. In such a situation, the Quality of Service metrics of the Secondary Network are di cult to guarantee due to uctuating resource availability; nevertheless QoS metric evaluation is actually a very important factor for the success of Cognitive Radio. Quality of Experience is also gaining interest due to its focus on the users' per- ceived quality, and this opens up a new perspective on evaluating and improving wireless networks performance. The main contributions of this thesis include: it focuses on the real-time packet level QoS (packet delay and loss) performance of Cognitive Radio networks, and eval- uates the e ects on QoS of several typical non-con gurable factors including secondary user service types, primary user activity patterns and user distance from base station. Furthermore, the evaluation results are uni ed and represented using QoE through existing map- ping techniques. Based on the QoE evaluation, a novel cross layer RA scheme is proposed to dynamically compensate user experience, and this is shown to signi cantly improve QoE in scenarios where traditional RA schemes fail to provide good user experience