Cognitive radio systems in LTE networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The most important fact in the mobile industry at the moment is that demand for wireless services will continue to expand in the coming years. Therefore, it is vital to find more spectrums through cognitive radios for the growing numbers of services and users. However, the spectrum reallocations, enhanced receivers, shared use, or secondary markets-will not likely, by themselves or in combination, meet the real exponential increases in demand for wireless resources. Network operators will also need to re-examine network architecture, and consider integrating the fibre and wireless networks to address this issue. This thesis involves driving fibre deeper into cognitive networks, deploying microcells connected through fibre infrastructure to the backbone LTE networks, and developing the algorithms for diverting calls between the wireless and fibre systems, introducing new coexistence models, and mobility management. This research addresses the network deployment scenarios to a microcell-aided cognitive network, specifically slicing the spectrum spatially and providing reliable coverage at either tier. The goal of this research is to propose new method of decentralized-to-distributed management techniques that overcomes the spectrum unavailability barrier overhead in ongoing and future deployments of multi-tiered cognitive network architectures. Such adjustments will propose new opportunities in cognitive radio-to-fibre systematic investment strategies. Specific contributions include: 1) Identifying the radio access technologies and radio over fibre solution for cognitive network infrastructure to increase the uplink capacity analysis in two-tier networks. 2) Coexistence of macro and microcells are studied to propose a roadmap for optimising the deployment of cognitive microcells inside LTE macrocells in the case of considering radio over fibre access systems. 3) New method for roaming mobiles moving between microcells and macrocell coverage areas is proposed for managing spectrum handover, operator database, authentication and accounting by introducing the channel assigning agent entity. The ultimate goal is to reduce unnecessary channel adaptation

Artificial neural networks for location estimation and co-cannel interference suppression in cellular networks

This thesis reports on the application of artificial neural networks to two important problems encountered in cellular communications, namely, location estimation and co-channel interference suppression. The prediction of a mobile location using propagation path loss (signal strength) is a very difficult and complex task. Several techniques have been proposed recently mostly based on linearized, geometrical and maximum likelihood methods. An alternative approach based on artificial neural networks is proposed in this thesis which offers the advantages of increased flexibility to adapt to different environments and high speed parallel processing. Location estimation provides users of cellular telephones with information about their location. Some of the existing location estimation techniques such as those used in GPS satellite navigation systems require non-standard features, either from the cellular phone or the cellular network. However, it is possible to use the existing GSM technology for location estimation by taking advantage of the signals transmitted between the phone and the network. This thesis proposes the application of neural networks to predict the location coordinates from signal strength data. New multi-layered perceptron and radial basis function based neural networks are employed for the prediction of mobile locations using signal strength measurements in a simulated COST-231 metropolitan environment. In addition, initial preliminary results using limited available real signal-strength measurements in a metropolitan environment are also reported comparing the performance of the neural predictors with a conventional linear technique. The results indicate that the neural predictors can be trained to provide a near perfect mapping using signal strength measurements from two or more base stations. The second application of neural networks addressed in this thesis, is concerned with adaptive equalization, which is known to be an important technique for combating distortion and Inter-Symbol Interference (ISI) in digital communication channels. However, many communication systems are also impaired by what is known as co-channel interference (CCI). Many digital communications systems such as digital cellular radio (DCR) and dual polarized micro-wave radio, for example, employ frequency re-usage and often exhibit performance limitation due to co-channel interference. The degradation in performance due to CCI is more severe than due to ISI. Therefore, simple and effective interference suppression techniques are required to mitigate the interference for a high-quality signal reception. The current work briefly reviews the application of neural network based non-linear adaptive equalizers to the problem of combating co-channel interference, without a priori knowledge of the channel or co-channel orders. A realistic co-channel system is used as a case study to demonstrate the superior equalization capability of the functional-link neural network based Decision Feedback Equalizer (DFE) compared to other conventional linear and neural network based non-linear adaptive equalizers.This project was funded by Solectron (Scotland) Ltd

Technology 2003: Conference Proceedings from the Fourth National Technology Transfer Conference and Exposition, Volume 1

Proceedings from symposia of the Technology 2003 Conference and Exposition, December 7-9, I993, Anaheim, CA. Volume 1 features the Plenary Session and the Plenary Workshop, plus papers presented in Advanced Manufacturing, Biotechnology/Medical Technology, Environmental Technology, Materials Science, and Power and Energy

Municipal wireless mesh networks as a competitive broadband delivery platform

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2007.Includes bibliographical references (p. 119-122).Recently there has been a growing interest in deploying Wireless Mesh Networks by municipalities. This interest stems from the desire to provide broadband connectivity to users lacking access to broadband alternatives. The ubiquity of these networks will create more opportunities for new wireless-based applications and services that will generate revenue to the local businesses. The current plan is primarily focusing on the use of the WiFi, which was originally designed for indoor LAN applications operating in unlicensed spectrum. Also, the Municipalities claim that their main targets are Public Safety and the low-income neighborhood that cannot afford DSL or Cable broadband. There is a doubt, however, that the current plan will deliver on its promises in terms of coverage as well as cost. In this research, the goal is to first study the current business model for the current Municipal Wireless Mesh networks under deployment. As such, we will attempt to examine the networks under development in Brookline, Boston, Cambridge, and other cities in the US. We will also examine the technical limitations of these networks. This will lead us to suggest modifications to both the business model and a new system design. The goal for these modifications is to enhance the chance of these networks to succeed in the market place.by Mudhafar Hassan-Ali.S.M

Engineered Porous Materials EXPO `93

The EXPO was organized to increase communication between US industry and DOE`s national laboratories. The report contains copies of viewgraphs of all speakers and reports of workshops designed to identify priority needs of industry. A conference synopsis and set of recommendations to DOE are also included