Routing And Resource Allocation For Heterogeneous Services In Cognitive Wireless Mesh Networks

Wireless mesh networks (WMNs) are considered to be a promising solution for the support of low-cost broadband Internet access for heterogeneous services in a large coverage area. However, the scarcity of wireless resources presents a key challenge for WMNs to accommodate the explosively growing data traffic. Cognitive radio, allowing secondary users to opportunistically access the spectrum of primary users, is an excellent candidate to supply WMNs with the additional spectra and improves their performance, leading to the so-called cognitive mesh networks. In this thesis, resources management including routing and resource allocation for cognitive wireless mesh networks are studied.Firstly, stability-based route selection problem in cognitive mesh-network is studied. Specifically, our objective is to find a route that can achieve the maximal expected transmission rate for the secondary flows while the end-to-end date rate and hop requirements are satisfied. Simulation results demonstrate that the proposed scheme enables a secondary flow to maintain a maximal expected transmission rate on average and thus enhances its stability.Secondly, resource allocation for real time (RT) and non-real time (NRT) flows in cognitive mesh network are studied respectively, with the objectives of minimizing network-wide radio resource consumed by RT flows and maximizing total throughput of NRT flows. We formulate these two problems as two mixed-integer nonlinear programming (MINLP) problems which are NP-hard in general, and propose low-complexity yet efficient suboptimal algorithms to solve the formulated MINLP problems. Simulation results show that, in contrast to the compared algorithm, the proposed algorithms can achieve high system performance with low cost.Thirdly, joint routing and resource allocation for heterogeneous services in cognitive mesh network are studied. We design a two-step approach, namely long-time route selection and periodic resource allocation. By introducing the interference cushion to resource allocation, we prevent RT traffic from starving NRT traffic. Simulation results show the effectiveness of the proposed algorithms in terms of RT flow’s mean access ratio and NRT flow’s mean throughput. Also, we find that how to set interference cushion can affect the performance tradeoff between QoS provisioning for RT traffic and throughput maximization for NRT traffic.