On the Impact of Backhaul Channel Reliability on Cooperative Wireless Networks

We study the effect of unreliable backhaul links on the performance of Coordinated Multi-Point (CoMP) techniques. CoMP has emerged as a powerful scheme to mitigate co-channel interference. Economically viable deployment of Heterogeneous Networks (HetNets) will require the use of lower-performance backhaul options, e.g. non-line-of-sight microwave links. Motivated by HetNets, a backhauling model is introduced, by assigning Link Failure Probability (LFP) to backhaul links, for the cooperative clusters. In this paper we analyze the centralized and semi-distributed CoMP architectures. We investigate the probability of deficient backhaul links reducing quality of service, by impeding transmission. By valuating the average sum rate of users within a CoMP cluster, we show how backhaul link reliability affects the performance of the cooperative cluster. We conclude, that the performance gains offered by CoMP quickly diminish, as the unreliability of the backhaul links grows

On the Impact of Control Channel Reliability on Coordinated Multi-Point Transmission

In the heterogeneous networks (HetNets), co-channel interference is a serious problem. Coordinated multi-point (CoMP) transmission has emerged as a powerful technique to mitigate co-channel interference. However, all CoMP techniques rely on information exchange through reliable control channels, which are unlikely to be available in HetNets. In this paper, we study the effect of unreliable control channels, consisting of the access links and backhaul links, on the performance of CoMP. A control channel model is introduced by assigning link failure probability (LFP) to backhaul and access links for the cooperative clusters. Three CoMP architectures, namely the centralized, semi-distributed and fully distributed are analyzed. We investigate the probability of deficient control channels reducing quality of service, and impeding transmission. General closed-form expressions are derived for the probability of a cooperative transmission node staying silent in a resource slot due to unreliable control links. By evaluating the average sum rate of users within a CoMP cluster, we show that the performance gains offered by CoMP quickly diminish, as the unreliability of the control links grows

Cognitive network framework for heterogeneous wireless mesh systems

Heterogeneous wireless mesh networks (WMN) provide an opportunity to secure higher network capacity, wider coverage and higher quality of service (QoS). However, heterogeneous systems are complex to configure because of the high diversity of associated devices and resources. This thesis introduces a novel cognitive network framework that allows the integration of WMNs with long-term evolution (LTE) networks so that none of the overlapped frequency bands are used. The framework consists of three novel systems: the QoS metrics management system, the heterogeneous network management system and the routing decision-making system. The novelty of the QoS metrics management system is that it introduces a new routing metric for multi-hop wireless networks by developing a new rate adaptation algorithm. This system directly addresses the interference between neighbouring nodes, which has not been addressed in previous research on rate adaptation for WMN. The results indicated that there was a significant improvement in the system throughput by as much as to 90%. The routing decision-making system introduces two novel methods to select the transmission technology in heterogeneous nodes: the cognitive heterogeneous routing (CHR) system and the semantic reasoning system. The CHR method is used to develop a novel reinforcement learning algorithm to optimise the selection of transmission technology on wireless heterogeneous nodes by learning from previous actions. The semantic reasoning method uses ontologies and fuzzy-based semantic reasoning to facilitate the dynamic addition of new network types to the heterogeneous network. The simulation results showed that the heterogeneous network outperformed the benchmark networks by up to 200% of the network throughput