A Connection Admission Control Framework for UMTS based Satellite Systems.An Adaptive Admission Control algorithm with pre-emption control mechanism for unicast and multicast communications in satellite UMTS.
SupervisorHu, Yim Fun
Halliwell, Rosemary A.
Satellite communication systems
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentSchool of Engineering, Design and Technology
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AbstractIn recent years, there has been an exponential growth in the use of multimedia applications. A satellite system offers great potential for multimedia applications with its ability to broadcast and multicast a large amount of data over a very large area as compared to a terrestrial system. However, the limited transmission capacity along with the dynamically varying channel conditions impedes the delivery of good quality multimedia service in a satellite system which has resulted in research efforts for deriving efficient radio resource management techniques. This issue is addressed in this thesis, where the main emphasis is to design a CAC framework which maximizes the utilization of the scarce radio resources available in the satellite and at the same time increases the performance of the system for a UMTS based satellite system supporting unicast and multicast traffic. The design of the system architecture for a UMTS based satellite system is presented. Based on this architecture, a CAC framework is designed consisting of three different functionalities: the admission control procedure, the retune procedure and the pre-emption procedure. The joint use of these functionalities is proposed to allow the performance of the system to be maintained under congestion. Different algorithms are proposed for different functionalities; an adaptive admission control algorithm, a greedy retune algorithm and three pre-emption algorithms (Greedy, SubSetSum, and Fuzzy). A MATLAB simulation model is developed to study the performance of the proposed CAC framework. A GUI is created to provide the user with the flexibility to configure the system settings before starting a simulation. The configuration settings allow the system to be analysed under different conditions. The performance of the system is measured under different simulation settings such as enabling and disabling of the two functionalities of the CAC framework; retune procedure and the pre-emption procedure. The simulation results indicate the CAC framework as a whole with all the functionalities performs better than the other simulation settings.
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Optimal Multi-Drug Chemotherapy Control Scheme for Cancer Treatment. Design and development of a multi-drug feedback control scheme for optimal chemotherapy treatment for cancer. Evolutionary multi-objective optimisation algorithms were used to achieve the optimal parameters of the controller for effective treatment of cancer with minimum side effects.Hossain, M. Alamgir; Majumder, Md A.A.; Algoul, Saleh (University of BradfordSchool of Computing, Informatics and Media, 2013-01-23)Cancer is a generic term for a large group of diseases where cells of the body lose their normal mechanisms for growth so that they grow in an uncontrolled way. One of the most common treatments of cancer is chemotherapy that aims to kill abnormal proliferating cells; however normal cells and other organs of the patients are also adversely affected. In practice, it¿s often difficult to maintain optimum chemotherapy doses that can maximise the abnormal cell killing as well as reducing side effects. The most chemotherapy drugs used in cancer treatment are toxic agents and usually have narrow therapeutic indices, dose levels in which these drugs significantly kill the cancerous cells are close to the levels which sometime cause harmful toxic side effects. To make the chemotherapeutic treatment effective, optimum drug scheduling is required to balance between the beneficial and toxic side effects of the cancer drugs. Conventional clinical methods very often fail to find drug doses that balance between these two due to their inherent conflicting nature. In this investigation, mathematical models for cancer chemotherapy are used to predict the number of tumour cells and control the tumour growth during treatment. A feedback control method is used so as to maintain certain level of drug concentrations at the tumour sites. Multi-objective Genetic Algorithm (MOGA) is then employed to find suitable solutions where drug resistances and drug concentrations are incorporated with cancer cell killing and toxic effects as design objectives. Several constraints and specific goal values were set for different design objectives in the optimisation process and a wide range of acceptable solutions were obtained trading off among different conflicting objectives. Abstract v In order to develop a multi-objective optimal control model, this study used proportional, integral and derivative (PID) and I-PD (modified PID with Integrator used as series) controllers based on Martin¿s growth model for optimum drug concentration to treat cancer. To the best of our knowledge, this is the first PID/I-PD based optimal chemotherapy control model used to investigate the cancer treatment. It has been observed that some solutions can reduce the cancer cells up to nearly 100% with much lower side effects and drug resistance during the whole period of treatment. The proposed strategy has been extended for more drugs and more design constraints and objectives.
Control strategies for exothermic batch and fed-batch processes A sub-optimal strategy is developed which combines fast response with a chosen control signal safety margin. Design procedures are described and results compared with conventional control.Henry, R.M.; Kaymaz, I. Ali (University of BradfordSchool of Control Engineering, 2010-02-08)There is a considerable scope for improving the temperature control of exothermic processes. In this thesis, a sub-optimal control strategy is developed through utilizing the dynamic, simulation tool. This scheme is built around easily obtained knowledge of the system and still retains flexibility. It can be applied to both exothermic batch and fed-batch processes. It consists of servo and regulatory modes, where a Generalized Predictive Controller (GPC) was used to provide self-tuning facilities. The methods outlined allow for limited thermal runaway whilst keeping some spare cooling capacity to ensure that operation at constraints are not violated. A special feature of the method proposed is that switching temperatures and temperature profiles can be readily found from plant trials whilst the addition rate profile Is capable of fairly straightforward computation. The work shows that It is unnecessary to demand stability for the whole of the exothermic reaction cycle, permitting a small runaway has resulted in a fast temperature response within the given safety margin. The Idea was employed for an exothermic single Irreversible reaction and also to a set of complex reactions. Both are carried out in a vessel with a heating/cooling coil. Two constraints are Imposed; (1) limited heat transfer area, and (11) a maximum allowable reaction temperature Tmax. The non-minimum phase problem can be considered as one of the difficulties in managing exothermic fed-batch process when cold reactant Is added to vessel at the maximum operating temperature. The control system coped with this within limits, a not unexpected result. In all cases, the new strategy out-performed the conventional controller and produced smoother variations in the manipulated variable. The simulation results showed that batch to batch variations and disturbances In cooling were successfully handled. GPC worked well but can be susceptible to measurement noise.
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