Capacity Enhancement Approaches for Long Term Evolution networks: Capacity Enhancement-Inspired Self-Organized Networking to Enhance Capacity and Fairness of Traffic in Long Term Evolution Networks by Utilising Dynamic Mobile Base-Stations

The long-term evolution (LTE) network has been proposed to provide better network capacity than the earlier 3G network. Driven by the market, the conventional LTE (3G) network standard could not achieve the expectations of the international mobile telecommunications advanced (IMT-Advanced) standard. To satisfy this gap, the LTE-Advanced was introduced with additional network functionalities to meet up with the IMT-Advanced Standard. In addition, due to the need to minimize operational expenditure (OPEX) and reduce human interventions, the wireless cellular networks are required to be self-aware, self-reconfigurable, self-adaptive and smart. An example of such network involves transceiver base stations (BTSs) within a self-organizing network (SON). Besides these great breakthroughs, the conventional LTE and LTE-Advanced networks have not been designed with the intelligence of scalable capacity output especially in sudden demographic changes, namely during events of football, malls, worship centres or during religious and cultural festivals. Since most of these events cannot be predicted, modern cellular networks must be scalable in terms of capacity and coverage in such unpredictable demographic surge. Thus, the use of dynamic BTSs is proposed to be used in modern and future cellular networks for crowd and demographic change managements. Dynamic BTSs are complements of the capability of SONs to search, determine and deploy less crowded/idle BTSs to densely crowded cells for scalable capacity management. The mobile BTSs will discover areas of dark coverages and fill-up the gap in terms of providing cellular services. The proposed network relieves the LTE network from overloading thus reducing packet loss, delay and improves fair load sharing. In order to trail the best (least) path, a bio-inspired optimization algorithm based on swarm-particle optimization is proposed over the dynamic BTS network. It uses the ant-colony optimization algorithm (ACOA) to find the least path. A comparison between an optimized path and the un-optimized path showed huge gain in terms of delay, fair load sharing and the percentage of packet loss

Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics

Abstract Network planning in the highly competitive, demand-adaptive and rapidly growing cellular telecommunications industry is a fairly complex and crucial issue. It comprises collective optimization of the supporting, switching, signaling and interconnection networks to minimize costs while observing imposed infrastructure constraints. This work focuses on the problem of assigning cells to switches, which comprise the Base Station Controller and Mobile Switching Center, in a cellular mobile network. As a classic instance of the NP-hard Quadratic Assignment Problem (QAP), deterministic algorithms are incapable of nding optimal solutions in the vast complex search space in polynomial time. Hence, a randomized, heuristic algorithm, such as Simulated Evolution is used in this work to optimize the transmission costs in cellular networks. The results achieved are compared with existing methods available in literature. Key words: Network planning, Cellular Mobile Network, Assignment, Quadratic Assignment Problem, Heuristics, Evolutionary Heuristics, Soft Computing

Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics

Abstract Network planning in the highly competitive, demand-adaptive and rapidly growing cellular telecommunications industry is a fairly complex and crucial issue. It comprises collective optimization of the supporting, switching, signaling and interconnection networks to minimize costs while observing imposed infrastructure constraints. This work focuses on the problem of assigning cells to switches, which comprise the Base Station Controller and Mobile Switching Center, in a cellular mobile network. As a classic instance of the NP-hard Quadratic Assignment Problem (QAP), deterministic algorithms are incapable of nding optimal solutions in the vast complex search space in polynomial time. Hence, a randomized, heuristic algorithm, such as Simulated Evolution is used in this work to optimize the transmission costs in cellular networks. The results achieved are compared with existing methods available in literature. Key words: Network planning, Cellular Mobile Network, Assignment, Quadratic Assignment Problem, Heuristics, Evolutionary Heuristics, Soft Computing

Data analysis methods for cellular network performance optimization

Modern cellular networks including GSM/GPRS and UMTS networks offer faster and more versatile communication services for the network subscribers. As a result, it becomes more and more challenging for the cellular network operators to enhance the usage of available radio resources in order to meet the expectations of the customers. Cellular networks collect vast amounts of measurement information that can be used to monitor and analyze the network performance as well as the quality of service. In this thesis, the application of various data-analysis methods for the processing of the available measurement information is studied in order to provide more efficient methods for performance optimization. In this thesis, expert-based methods have been presented for the monitoring and analysis of multivariate cellular network performance data. These methods allow the analysis of performance bottlenecks having an effect in multiple performance indicators. In addition, methods for more advanced failure diagnosis have been presented aiming in identification of the causes of the performance bottlenecks. This is important in the analysis of failures having effect on multiple performance indicators in several network elements. Finally, the use of measurement information in selection of most useful optimization action have been studied. In order to obtain good network performance efficiently, the expected performance of the alternative optimization actions must be possible to evaluate. In this thesis, methods to combine measurement information and application domain models are presented in order to build predictive regression models that can be used to select the optimization actions providing the best network performance

Self-tuning algorithms for the assignment of packet control units and handover parameters in GERAN

Esta tesis aborda el problema de la optimización automática de parámetros en redes de acceso radio basadas en GSM-EDGE Radio Access Network (GERAN). Dada la extensión del conjunto de parámetros que se puede optimizar, este trabajo se centra en dos de los procesos encargados de la gestión de la movilidad: el proceso de (re)selección de celda para servicios por conmutación de paquetes y el proceso de traspaso para servicios de voz por conmutación de circuitos

Adjacency visualization in mobile networks

The ever-increasing usage of mobile phones forces the network operators to expand and tune their mobile networks continuously to meet the growing requirements for the quality of service. This is done with the help of optimization tools. One of the network optimization tools used by operators is Nokia Optimizer, whose adjacency management functionality as well as the process for developing the said functionality is described in this thesis. The development of Optimizer started in 2001, at the time as this study began. Several versions of Optimizer were developed during the course of this study. The aim of this thesis is to study the possibilities for managing and visualizing handovers in a mobile network in a graphical user interface. The thesis also covers software architecture and performance related issues as part of the software implementation process. The most important research problem was adjacency visualization on top of a geographical map. More specifically, the aim was to study what kind of icons and color usage were best suited for representing adjacencies and related information on the map, at the same time keeping in mind that the solution would have to work also in cases where a sizeable amount of objects as well as other information was to be shown. During the course of this study it came apparent that performance issues related to adjacency management had to be addressed as well. As a result of this study, useful solutions for adjacency visualization were found for Optimizer. Significant improvements in adjacency management and in performance were achieved as well, as a comparison of Optimizer and earlier Nokia optimization tools demonstrates.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Femtocell deployment; next generation in cellular systems

The final Bachelor’s Thesis that is shown below has such a final purpose of giving an overview of the inclusion of the so-called Femtocells (or Home Node B) in the current cellular systems. The main objective is to give a clear but simple idea about the concepts of Femtocells, as well as to explain the benefits and disadvantages of the mass uses of these services both for consumers and associated companies with this phenomenon. In this text it is also possible to find a brief review of wireless technologies throughout the history of telecommunications, as well as an introduction to the more current wireless technologies, with a special interest in the concept of cellular systems. In the last chapter a simple mathematical explanation of the key issue of interference between Femtocells and macrocellular networks is presented, with a brief argument about possible solutions

Simulating Road Traffic for Generating Cellular Network Logs in Urban Context

Viimastel aastatel on hakanud mobiilside andmestik paeluma aina rohkem teadlasi erinevatelt teadusdistsipliinidelt. Need andmed aitavad mõista inimeste käitumis- kui ka liikumismustreid. Mitmed mobiilsusandmestikud (nagu näiteks Call Detail Records mobiilside andmed) ning GPS andmed näitavad inimeste liikumissagedust ja -põhjusi.Need andmestikud sisaldavad endas väärtuslikku informatsiooni ühiskonna kohta. Töödeldud informatsiooni saab kasutada mitmel otstarbel. Teadlased saaksid andmestiku põhjal planeerida teedevõrgustikke, paremini suunata inimestele reklaame arvestades nende paiknemist, luua uusi positsioneerimistehnoloogiaid, arendada rahvastikukontrolli tarkvara jne.Vaatamata tehnoloogilistele võimalustele on inimeste mobiilsusandmestikud väga raskesti kättesaadavad, sest need on kaitstud riiklike regulatsioonide poolt, kuna riivavad inimeste privaatsust. Teine tegur on mobiilioperaatorite enda huvi luua inimeste mobiilsusandmetel põhinevaid kommertslahendusi. Selline situatsioon ei innusta operaatoreid jagama äriliselt vajalikku informatsiooni kolmandate osapooltega. Antud magistritöö käigus näidatakse, kuidas sellest raskest probleemist üle saada arendades mobiilsidevõrgukäitumissimulatsiooni prototüüpi. Genereerides andmeid läbi erinevate teaduslike liikumismudelite, mida võimaldab meile liiklussimulatsiooni tarkvara.Uurimistöö tulemusena selgus, et selline lähenemine on resultatiivne ja omab mitmeid laienemisvõimalusi. Täheldati mitmeid võimalusi koostööks teiste uurimisvaldkondadega, et muuta genereeritavaid mobiilsusandmeid reaalelule sarnanevateks. Mobiilsidevõrgu käituvussimulatsioon on näidanud suurt potentsiaali ning arendamise käigus avaldusid võimalused, mida algselt ei osatud oodata. Mainitud mobiilsidevõrgu käituvussimulatsioon on integreeritud eksisteeriva liiklussimulatsiooni tarkvaraga, mis on vabavara ning mida on võimalik laialdaselt konfigureerida. Liiklussimulatsiooni tarkvaraskasutatavad inimkäitumise mudelid põhinevad erinevate teadustööde tulemustel ning seetõttu mobiilsidevõrgu käituvus- ning liiklussimulatsiooni sümbioosi tulemusel genereeritud andmed on märkimisväärse väärtusega.In the last years, the use of mobile phone data logs start to attract a lot of researchers’ attentions from various disciplines. Those logs help the scientist to understand and predict human behaviour. The mobility logs, like Call Detail Records and GPS data, show where to people commute, how often do they commute and, usually, those logs also say why. These logs hold knowledge about our society, from that data the knowledge could be extracted and used for multiple purposes. The scientists could analyse through the movement how to plan the road infrastructure, generate target advertisement based on forecasting peoples displacement, new positioning technology, population control software, etc. But there are limits on the people's mobility data. Those information logs are heavily protected by the government privacy data laws to protect the personal rights. Additionally, the mobile operators are interested in their own commercial solutions and therefore their interest to share vital information is low. Here, in this thesis, we show that this cumbersome problem can be over-stepped by prototyping a cellular network behaviour simulator to generate the logs for us through different scientific commuting models inherited from the traffic simulation program.The result of this thesis reveals that this approach is feasible and shows multiple expansion possibilities how to produce even more real-life like mobility logs. The development of the cellular network behaviour simulation has shown huge potential and even bigger possibilities than predicted in the beginning. Since, our cellular network behaviour simulation is integrated with already existing open-source, highly configurable, road traffic simulator basing on the scientific human behaviour models produce with considerable value data