Not available

M. Tech. Electrical Engineering / The radio frequency (RF) spectrum is a natural resource used by wireless network operators to provide radio communication and transmission systems. The availability of RF spectrum to various wireless network operators using large bandwidth and more than one channel, as demanded by their offered services, is challenging, due to RF spectrum scarcity and lack of optimal channel selection. On the other hand, the under-utilisation of licensed spectrum by some primary users' (PU's) networks may be improved by the use of dynamic spectrum access (DSA) techniques. Recent research has shown that a large portion of the assigned spectrum is used irregularly, leading to under-utilisation and waste of valuable frequency resources. The notion of cognitive radio (CR) was introduced to increase the effectiveness and efficiency of spectrum consumption. In a cognitive radio network (CRN), each secondary user (SU) is expected to select the best RF spectrum band for opportunistic use when the PUs have temporarily vacated the spectrum allocated to them. The literature has proposed many spectrum selection methods for selecting vacant spectra in CRNs. However, most of these methods do not consider the channel usage pattern over time by PUs and also do not adequately consider the effect that frequent channel-switching might have on the quality of service requirements of the SUs and the throughput of the CR system. Thus, the proposed scheme, which is heuristic-based spectrum selection scheme for minimal channel switching (HBSSS-MCS) and heuristic-based spectrum selection scheme for maximum throughput (HBSSS-MT) addresses these issues. The main study objectives were as follows: 1) Minimise the frequent switching of channels using HBSS-MCS; 2) Maximise the throughput of the CR system using HBSSS-MT. To achieve the objectives of this research work, the following sub-problems were addressed: 1) To investigate the spectrum selection schemes in cognitive radio network (CRN); 2) To design a learning mechanism to facilitate the selection of a suitable channel in the primary network.

D. Tech. Engineering: Electrical. / The remarkable evolution of wireless networks into the next generation to provide ubiquitous and seamless broadband applications has recently triggered the emergence of Wireless Mesh Networks (WMNs). The WMNs comprise stationary Wireless Mesh Routers (WMRs) forming Wireless Backbone Mesh Networks (WBMNs) and mobile Wireless Mesh Clients (WMCs) forming the WMN access. While WMCs are limited in function and radio resources, the WMRs are expected to support heavy duty applications: that is, WMRs have gateway and bridge functions to integrate WMNs with other networks such as the Internet, cellular, IEEE 802.11, IEEE 802.15, IEEE 802.16, sensor networks, et cetera. Consequently, WMRs are constructed from fast switching radios or multiple radio devices operating on multiple frequency channels. WMRs are expected to be self-organized, self-configured and constitute a reliable and robust WBMN which needs to sustain high traffic volumes and long "online" time. However, meeting such stringent service expectations requires the development of decentralized dynamic transmission power control (DTPC) approaches. This thesis addresses the DTPC problem for both single and multiple channel WBMNs. For single channel networks, the problem is formulated as the minimization of both the link-centric and network-centric convex cost function. For multi-radio multichannel (MRMC) WBMNs, the network is modelled as sets of unified channel graphs (UCGs), each consisting of interconnected active network users communicating on the same frequency channel.

Not available / text

Not available / text

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy