Telecommunications Network Planning and Maintenance

Telecommunications network operators are on a constant challenge to provide new services which require ubiquitous broadband access. In an attempt to do so, they are faced with many problems such as the network coverage or providing the guaranteed Quality of Service (QoS). Network planning is a multi-objective optimization problem which involves clustering the area of interest by minimizing a cost function which includes relevant parameters, such as installation cost, distance between user and base station, supported traffic, quality of received signal, etc. On the other hand, service assurance deals with the disorders that occur in hardware or software of the managed network. This paper presents a large number of multicriteria techniques that have been developed to deal with different kinds of problems regarding network planning and service assurance. The state of the art presented will help the reader to develop a broader understanding of the problems in the domain

Hybridisation of genetic algorithm with simulated annealing for vertical-handover in heterogeneous wireless networks

To provide the seamless mobility in heterogeneous wireless networks two significant methods, simulated annealing (SA) and genetic algorithms (GAs) are hybrid. In this paradigm, vertical handovers (VHs) are necessary for seamless mobility. In this paper, the hybrid algorithm has the ability to find the optimal network to connect with a good quality of service (QoS) in accordance with the user's preferences. The intelligent algorithm was developed to provide solutions near to real time and to avoid slow and considerable computations according to the features of the mobile devices. Moreover, a cost function is used to sustain the chosen QoS during transition between networks, which is measured in terms of the bandwidth, BER, ABR, SNR and monetary cost. Simulation results presented that choosing the SA rules would minimise the cost function and the GA-SA algorithm could reduce the number of unnecessary handovers, and thereby avoid the 'Ping-Pong' effect

DVB-T2 network optimization with swimulated annealing

Postprint (author’s final draft

Cost efficient 5G heterogeneous base station deployment using meta-heuristics

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonOver the last two decades, the telecommunication industry has witnessed sustained growth in the number of mobile user devices driven by the introduction of data services, the take-off of the internet and smart user equipment. This growth, which is forecasted to continue, has continued to push the data transfer capacity requirement on mobile networks and has motivated research into the design of 5th generation (5G) mobile networks. A key concern in the design of 5G is the infrastructure and power consumption cost of the base station network which is expected to be significantly more advanced and dense than that of existing conventional mobile networks. This thesis presents an optimisation framework for the cost efficient design of 5G base station networks, based on the application of meta-heuristic algorithms. The presented optimisation framework is centred on the ability to exploit three key technologies of 5G, a heterogonous base station network with small-cells, multi-antenna spatial multiplexing MIMO and cell range extension. The framework includes mathematical integer programming models for supporting the decisions about the optimal base station topology in a 5G mobile network and provides a clear core for the application of meta-heuristics for optimising 5G base station deployment. The core optimisation framework includes the definition of solution encoding/decoding and fitness mechanisms. To increase power consumption awareness of base station network design, an independent base station deployment strategy has been presented and evaluated. Simulation results show that the strategy can improve base station network design power consumption by as much as 34%. The work in this thesis has been extensively evaluated using a simulated 5G mobile network system model. Evaluations of algorithms have been performed through empirical measurements. The main contribution of this thesis is the definition of a clear framework for application fitness based heuristic search in the design of 5G mobile networks

Contribution to resource management in cellular access networks with limited backhaul capacity

La interfaz radio de los sistemas de comunicaciones móviles es normalmente considerada como la única limitación de capacidad en la red de acceso radio. Sin embargo, a medida que se van desplegando nuevas y más eficientes interfaces radio, y de que el tráfico de datos y multimedia va en aumento, existe la creciente preocupación de que la infraestructura de transporte (backhaul) de la red celular pueda convertirse en el cuello de botella en algunos escenarios. En este contexto, la tesis se centra en el desarrollo de técnicas de gestión de recursos que consideran de manera conjunta la gestión de recursos en la interfaz radio y el backhaul. Esto conduce a un nuevo paradigma donde los recursos del backhaul se consideran no sólo en la etapa de dimensionamiento, sino que además son incluidos en la problemática de gestión de recursos. Sobre esta base, el primer objetivo de la tesis consiste en evaluar los requerimientos de capacidad en las redes de acceso radio que usan IP como tecnología de transporte, de acuerdo a las recientes tendencias de la arquitectura de red. En particular, se analiza el impacto que tiene una solución de transporte basada en IP sobre la capacidad de transporte necesaria para satisfacer los requisitos de calidad de servicio en la red de acceso. La evaluación se realiza en el contexto de la red de acceso radio de UMTS, donde se proporciona una caracterización detallada de la interfaz Iub. El análisis de requerimientos de capacidad se lleva a cabo para dos diferentes escenarios: canales dedicados y canales de alta velocidad. Posteriormente, con el objetivo de aprovechar totalmente los recursos disponibles en el acceso radio y el backhaul, esta tesis propone un marco de gestión conjunta de recursos donde la idea principal consiste en incorporar las métricas de la red de transporte dentro del problema de gestión de recursos. A fin de evaluar los beneficios del marco de gestión de recursos propuesto, esta tesis se centra en la evaluación del problema de asignación de base, como estrategia para distribuir el tráfico entre las estaciones base en función de los niveles de carga tanto en la interfaz radio como en el backhaul. Este problema se analiza inicialmente considerando una red de acceso radio genérica, mediante la definición de un modelo analítico basado en cadenas de Markov. Dicho modelo permite calcular la ganancia de capacidad que puede alcanzar la estrategia de asignación de base propuesta. Posteriormente, el análisis de la estrategia propuesta se extiende considerando tecnologías específicas de acceso radio. En particular, en el contexto de redes WCDMA se desarrolla un algoritmo de asignación de base basado en simulatedannealing cuyo objetivo es maximizar una función de utilidad que refleja el grado de satisfacción de las asignaciones respecto los recursos radio y transporte. Finalmente, esta tesis aborda el diseño y evaluación de un algoritmo de asignación de base para los futuros sistemas de banda ancha basados en OFDMA. En este caso, el problema de asignación de base se modela como un problema de optimización mediante el uso de un marco de funciones de utilidad y funciones de coste de recursos. El problema planteado, que considera que existen restricciones de recursos tanto en la interfaz radio como en el backhaul, es mapeado a un problema de optimización conocido como Multiple-Choice Multidimensional Knapsack Problem (MMKP). Posteriormente, se desarrolla un algoritmo de asignación de base heurístico, el cual es evaluado y comparado con esquemas de asignación basados exclusivamente en criterios radio. El algoritmo concebido se basa en el uso de los multiplicadores de Lagrange y está diseñado para aprovechar de manera simultánea el balanceo de carga en la intefaz radio y el backhaul.Postprint (published version

On the optimisation of practical wireless indoor and outdoor microcells subject to QOS constraints

Wireless indoor and outdoor microcells (WIOMs) have emerged as a promising means to deal with a high demand of mobile users for a variety of services. Over such heterogeneous networks, the deployment of WIOMs costs mobile/telecommunications company high capital expenditures and operating expenses. This paper aims at optimising the WIOMs taking into account various network communication environments. We first develop an optimisation problem to minimise the number of cells as well as determining their optimal locations subject to the constraints of the coverage and quality-of-service (QoS) requirements. In particular, we propose a binary-search based cell positioning (BSCP) algorithm to find the optimal number of cells given a preset candidate antenna positions. The proposed BSCP algorithm is shown to not only reduce the number of cells for saving resources but also requires a low computational complexity compared to the conventional approaches with exhaustive search over all available sites. Moreover, EDX SignalPro is exploited as a simulation platform to verify the effectiveness of the proposed BSCP for the WIOMs with respect to various propagation modes and antenna parameters of different types, including isotropic, multiple-input single-output and multiple-input multiple-output

Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art

Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP