Cooperative control of relay based cellular networks

PhDThe increasing popularity of wireless communications and the higher data requirements of new types of service lead to higher demands on wireless networks. Relay based cellular networks have been seen as an effective way to meet users’ increased data rate requirements while still retaining the benefits of a cellular structure. However, maximizing the probability of providing service and spectrum efficiency are still major challenges for network operators and engineers because of the heterogeneous traffic demands, hard-to-predict user movements and complex traffic models. In a mobile network, load balancing is recognised as an efficient way to increase the utilization of limited frequency spectrum at reasonable costs. Cooperative control based on geographic load balancing is employed to provide flexibility for relay based cellular networks and to respond to changes in the environment. According to the potential capability of existing antenna systems, adaptive radio frequency domain control in the physical layer is explored to provide coverage at the right place at the right time. This thesis proposes several effective and efficient approaches to improve spectrum efficiency using network wide optimization to coordinate the coverage offered by different network components according to the antenna models and relay station capability. The approaches include tilting of antenna sectors, changing the power of omni-directional antennas, and changing the assignment of relay stations to different base stations. Experiments show that the proposed approaches offer significant improvements and robustness in heterogeneous traffic scenarios and when the propagation environment changes. The issue of predicting the consequence of cooperative decisions regarding antenna configurations when applied in a realistic environment is described, and a coverage prediction model is proposed. The consequences of applying changes to the antenna configuration on handovers are analysed in detail. The performance evaluations are based on a system level simulator in the context of Mobile WiMAX technology, but the concepts apply more generally

Practical design of optimal wireless metropolitan area networks: model and algorithms for OFDMA networks

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Ph.D.This thesis contributes to the study of the planning and optimisation of wireless metropolitan area networks, in particular to the access network design of OFDMAbased systems, where different parameters like base station position, antenna tilt and azimuth need to be configured during the early stages of the network life. A practical view for the solution of this problem is presented by means of the development of a novel design framework and the use of multicriteria optimisation. A further consideration of relaying and cooperative communications in the context of the design of this kind of networks is done, an area little researched. With the emergence of new technologies and services, it is very important to accurately identify the factors that affect the design of the wireless access network and define how to take them into account to achieve optimally performing and cost-efficient networks. The new features and flexibility of OFDMA networks seem particularly suited to the provision of different broadband services to metropolitan areas. However, until now, most existing efforts have been focused on the basic access capability networks. This thesis presents a way to deal with the trade-offs generated during the OFDMA access network design, and presents a service-oriented optimization framework that offers a new perspective for this process with consideration of the technical and economic factors. The introduction of relay stations in wireless metropolitan area networks will bring numerous advantages such as coverage extension and capacity enhancement due to the deployment of new cells and the reduction of distance between transmitter and receiver. However, the network designers will also face new challenges with the use of relay stations, since they involve a new source of interference and a complicated air interface; and this need to be carefully evaluated during the network design process. Contrary to the well known procedure of cellular network design over regular or hexagonal scenarios, the wireless network planning and optimization process aims to deal with the non-uniform characteristics of realistic scenarios, where the existence of hotspots, different channel characteristics for the users, or different service requirements will determine the final design of the wireless network. This thesis is structured in three main blocks covering important gaps in the existing literature in planning (efficient simulation) and optimisation. The formulation and ideas proposed in the former case can still be evaluated over regular scenarios, for the sake of simplicity, while the study of latter case needs to be done over specific scenarios that will be described when appropriate. Nevertheless, comments and conclusions are extrapolated to more general cases throughout this work. After an introduction and a description of the related work, this thesis first focuses on the study of models and algorithms for classical point-to-multipoint networks on Chapter 3, where the optimisation framework is proposed. Based on the framework, this work: - Identifies the technology-specific physical factors that affect most importantly the network system level simulation, planning and optimization process. - It demonstrates how to simplify the problem and translate it into a formal optimization routine with consideration of economic factors. - It provides the network provider, a detailed and clear description of different scenarios during the design process so that the most suitable solution can be found. Existing works on this area do not provide such a comprehensive framework. In Chapter 4: - The impact of the relay configuration on the network planning process is analysed. - A new simple and flexible scheme to integrate multihop communications in the Mobile WiMAX frame structure is proposed and evaluated. - Efficient capacity calculations that allow intensive system level simulations in a multihop environment are introduced. In Chapter 5: - An analysis of the optimisation procedure with the addition of relay stations and the derived higher complexity of the process is done. - A frequency plan procedure not found in the existing literature is proposed, which combines it with the use of the necessary frame fragmentation of in-band relay communications and cooperative procedures. - A novel joint two-step process for network planning and optimisation is proposed. Finally, conclusions and open issues are exposed

Aspects of capacity enhancement techniques in cellular networks

Frequency spectrum is the scarce resource. From mobile operator’s point of view, efficient utilization of the radio resources is needed while providing maximum coverage, and ensuring good quality of service with minimal infrastructure. In high capacity demanding areas, multilayer networks with multiband and multi radio access technologies are deployed, in order to meet the capacity requirements. In his doctoral thesis, Usman Sheikh has proposed a “Smart Traffic Handling” strategy, which is based on user’s required service type and location. Smart traffic handling scheme efficiently utilizes the different layers of the network, balances the load among them, and improves the system capacity. Power resources at base station are also limited. Usman Sheikh’s proposed “Power Control Scheme for High Speed Downlink Packet Access (HSDPA) network” improves the cell edge user experience, while maintaining the fairness among the other users in a cell. With the help of a proposed power control scheme, a user far from the base station can also enjoy the better quality of service. Generally, mobile operators use macro cells with wide beam antennas for wider coverage in the cell, but future capacity demands cannot be achieved by using only them. “Higher Order Sectorization” is one possible way to increase the system capacity. Usman Sheikh proposed new network layouts called “Snowflake” and “Flower” tessellations, for 6-sector and 12-sector sites, respectively. These tessellations can be used as a basis for making a nominal network plan for sites with higher order sectorization. These tessellations would be helpful for simulation purposes. Through his work, he has also tried to highlight the importance of deploying “Adaptive MIMO Switching” in Long Term Evolution (LTE) system, the fourth generation of wireless networks. In future, the fifth generation of wireless networks is expected to offer thousand times more capacity compared to LTE. The novel concept of “Single Path Multiple Access (SPMA)” given by Usman Sheikh is a revolutionary idea, and gives a possibility to increase the system capacity by a giant margin. SPMA can be considered as a right step towards 5G technology. Usman Sheikh’s work is of high importance not only from mobile operator’s point of view; rather his contributions to the scientific community will also lead to better user (customer) experience. His work will definitely benefit the mankind in utilizing the limited resources in an optimum and efficient way

Self-Organized Coverage and Capacity Optimization for Cellular Mobile Networks

Die zur Erfüllung der zu erwartenden Steigerungen übertragener Datenmengen notwendige größere Heterogenität und steigende Anzahl von Zellen werden in der Zukunft zu einer deutlich höheren Komplexität bei Planung und Optimierung von Funknetzen führen. Zusätzlich erfordern räumliche und zeitliche Änderungen der Lastverteilung eine dynamische Anpassung von Funkabdeckung und -kapazität (Coverage-Capacity-Optimization, CCO). Aktuelle Planungs- und Optimierungsverfahren sind hochgradig von menschlichem Einfluss abhängig, was sie zeitaufwändig und teuer macht. Aus diesen Grnden treffen Ansätze zur besseren Automatisierung des Netzwerkmanagements sowohl in der Industrie, als auch der Forschung auf groes Interesse.Selbstorganisationstechniken (SO) haben das Potential, viele der aktuell durch Menschen gesteuerten Abläufe zu automatisieren. Ihnen wird daher eine zentrale Rolle bei der Realisierung eines einfachen und effizienten Netzwerkmanagements zugeschrieben. Die vorliegende Arbeit befasst sich mit selbstorganisierter Optimierung von Abdeckung und Übertragungskapazität in Funkzellennetzwerken. Der Parameter der Wahl hierfür ist die Antennenneigung. Die zahlreichen vorhandenen Ansätze hierfür befassen sich mit dem Einsatz heuristischer Algorithmen in der Netzwerkplanung. Im Gegensatz dazu betrachtet diese Arbeit den verteilten Einsatz entsprechender Optimierungsverfahren in den betreffenden Netzwerkknoten. Durch diesen Ansatz können zentrale Fehlerquellen (Single Point of Failure) und Skalierbarkeitsprobleme in den kommenden heterogenen Netzwerken mit hoher Knotendichte vermieden werden.Diese Arbeit stellt einen "Fuzzy Q-Learning (FQL)"-basierten Ansatz vor, ein einfaches Maschinenlernverfahren mit einer effektiven Abstraktion kontinuierlicher Eingabeparameter. Das CCO-Problem wird als Multi-Agenten-Lernproblem modelliert, in dem jede Zelle versucht, ihre optimale Handlungsstrategie (d.h. die optimale Anpassung der Antennenneigung) zu lernen. Die entstehende Dynamik der Interaktion mehrerer Agenten macht die Fragestellung interessant. Die Arbeit betrachtet verschiedene Aspekte des Problems, wie beispielsweise den Unterschied zwischen egoistischen und kooperativen Lernverfahren, verteiltem und zentralisiertem Lernen, sowie die Auswirkungen einer gleichzeitigen Modifikation der Antennenneigung auf verschiedenen Knoten und deren Effekt auf die Lerneffizienz.Die Leistungsfähigkeit der betrachteten Verfahren wird mittels eine LTE-Systemsimulators evaluiert. Dabei werden sowohl gleichmäßig verteilte Zellen, als auch Zellen ungleicher Größe betrachtet. Die entwickelten Ansätze werden mit bekannten Lösungen aus der Literatur verglichen. Die Ergebnisse zeigen, dass die vorgeschlagenen Lösungen effektiv auf Änderungen im Netzwerk und der Umgebung reagieren können. Zellen stellen sich selbsttätig schnell auf Ausfälle und Inbetriebnahmen benachbarter Systeme ein und passen ihre Antennenneigung geeignet an um die Gesamtleistung des Netzes zu verbessern. Die vorgestellten Lernverfahren erreichen eine bis zu 30 Prozent verbesserte Leistung als bereits bekannte Ansätze. Die Verbesserungen steigen mit der Netzwerkgröße.The challenging task of cellular network planning and optimization will become more and more complex because of the expected heterogeneity and enormous number of cells required to meet the traffic demands of coming years. Moreover, the spatio-temporal variations in the traffic patterns of cellular networks require their coverage and capacity to be adapted dynamically. The current network planning and optimization procedures are highly manual, which makes them very time consuming and resource inefficient. For these reasons, there is a strong interest in industry and academics alike to enhance the degree of automation in network management. Especially, the idea of Self-Organization (SO) is seen as the key to simplified and efficient cellular network management by automating most of the current manual procedures. In this thesis, we study the self-organized coverage and capacity optimization of cellular mobile networks using antenna tilt adaptations. Although, this problem is widely studied in literature but most of the present work focuses on heuristic algorithms for network planning tool automation. In our study we want to minimize this reliance on these centralized tools and empower the network elements for their own optimization. This way we can avoid the single point of failure and scalability issues in the emerging heterogeneous and densely deployed networks.In this thesis, we focus on Fuzzy Q-Learning (FQL), a machine learning technique that provides a simple learning mechanism and an effective abstraction level for continuous domain variables. We model the coverage-capacity optimization as a multi-agent learning problem where each cell is trying to learn its optimal action policy i.e. the antenna tilt adjustments. The network dynamics and the behavior of multiple learning agents makes it a highly interesting problem. We look into different aspects of this problem like the effect of selfish learning vs. cooperative learning, distributed vs. centralized learning as well as the effect of simultaneous parallel antenna tilt adaptations by multiple agents and its effect on the learning efficiency.We evaluate the performance of the proposed learning schemes using a system level LTE simulator. We test our schemes in regular hexagonal cell deployment as well as in irregular cell deployment. We also compare our results to a relevant learning scheme from literature. The results show that the proposed learning schemes can effectively respond to the network and environmental dynamics in an autonomous way. The cells can quickly respond to the cell outages and deployments and can re-adjust their antenna tilts to improve the overall network performance. Additionally the proposed learning schemes can achieve up to 30 percent better performance than the available scheme from literature and these gains increases with the increasing network size

Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks

In this thesis, several optimization techniques for next-generation wireless networks are proposed to solve different problems in the field of Self-Organizing Networks and heterogeneous networks. The common basis of these problems is that network parameters are automatically tuned to deal with the specific problem. As the set of network parameters is extremely large, this work mainly focuses on parameters involved in mobility management. In addition, the proposed self-tuning schemes are based on Fuzzy Logic Controllers (FLC), whose potential lies in the capability to express the knowledge in a similar way to the human perception and reasoning. In addition, in those cases in which a mathematical approach has been required to optimize the behavior of the FLC, the selected solution has been Reinforcement Learning, since this methodology is especially appropriate for learning from interaction, which becomes essential in complex systems such as wireless networks. Taking this into account, firstly, a new Mobility Load Balancing (MLB) scheme is proposed to solve persistent congestion problems in next-generation wireless networks, in particular, due to an uneven spatial traffic distribution, which typically leads to an inefficient usage of resources. A key feature of the proposed algorithm is that not only the parameters are optimized, but also the parameter tuning strategy. Secondly, a novel MLB algorithm for enterprise femtocells scenarios is proposed. Such scenarios are characterized by the lack of a thorough deployment of these low-cost nodes, meaning that a more efficient use of radio resources can be achieved by applying effective MLB schemes. As in the previous problem, the optimization of the self-tuning process is also studied in this case. Thirdly, a new self-tuning algorithm for Mobility Robustness Optimization (MRO) is proposed. This study includes the impact of context factors such as the system load and user speed, as well as a proposal for coordination between the designed MLB and MRO functions. Fourthly, a novel self-tuning algorithm for Traffic Steering (TS) in heterogeneous networks is proposed. The main features of the proposed algorithm are the flexibility to support different operator policies and the adaptation capability to network variations. Finally, with the aim of validating the proposed techniques, a dynamic system-level simulator for Long-Term Evolution (LTE) networks has been designed

QoS management in UMTS terrestrial radio access FDD networks

This work investigates the role and importance of some of the key aspects of QoS planning, provisioning, monitoring and optimisation (QoS Management) for UMTS Terrestrial Radio Access (UTRA) FDD networks within the framework of the 3rd Generation Partnership Project (3GPP). Firstly, the differences between Quality of end user Experience (QoE) and Quality of Service (QoS) are explained. This is followed by a review of 3GPP requirements for QoS concept and architecture. Then all models and the main assumptions in this dissertation are presented. Based on these, original QoS mechanisms in the radio access network domain, means and methods for QoS provisioning, planning, monitoring and "optimisation" are discussed. Simulation results showed substantial spectral efficiency gains provided by service (or user) differentiation in UTRAN by means of priorities and differentiated parameter settings. When appropriately configured, the proposed QoS mechanisms can greatly reduce the need for bandwidth. Performance results proved also the proposed virtual time simulator to be an appropriate tool for service driven WCDMA radio interface dimensioning and detailed radio network planning. It is also shown that measuring QoS performance by a proper classification of counters (and or gauges), based on a particular subset of radio access bearer attributes, is a promising technique for assessing performances of service applications through WCDMA networks. With this new method there is no need to trace upper layer protocols at different interfaces or dumping data in mobile terminals. The proposed metrics allow operators to measure the bandwidth required for robust statistical reliability, to assess and exploit statistical sharing of resources, to configure QoS functions effectively, and to monitor QoE. The application of the proposed technique is not limited to the WCDMA Radio Network Subsystem (RNS), yet it can be deployed in any radio access and packet core network supporting mapping of performance indicators onto a particular subset of QoS attributes. Finally, in order to maximise the performance of the available services in UTRAN, at a given QoE, simulation results showed clear needs for the network administrator to adapt the parameter settings to diverse input application traffic conditions and the proposed genetic approach to be an appropriate solution space search algorithm for this purpose.reviewe

Interference analysis of and dynamic channel assignment algorithms in TD–CDMA/TDD systems

The radio frequency spectrum for commercial wireless communications has become an expensive commodity. Consequently, radio access techniques are required which enable the efficient exploitation of these resources. This, however, is a difficult task due to an increasing diversity of wireless services. Hence, in order to achieve acceptable spectrum efficiency a flexible air– interface is required. It has been demonstrated that code division multiple access (CDMA) provides flexibility by enabling efficient multi user access in a cellular environment. In addition, time division duplex (TDD) as compared to frequency division duplex (FDD) represents an appropriate method to cater for the asymmetric use of a duplex channel. However, the TDD technique is subject to additional interference mechanisms in particular if neighbouring cells require different rates of asymmetry. If TDD is combined with an interference limited multiple access technique such as CDMA, the additional interference mechanism represents an important issue. This issue poses the question of whether a CDMA/TDD air–interface can be used in a cellular environment. The problems are eased if a hybrid TDMA (time division multiple access) / CDMA interface (TD–CDMA) is used. The reason for this is that the TDMA component adds another degree of freedom which can be utilised to avoid interference. This, however, requires special channel assignment techniques. This thesis analyses cellular CDMA/TDD systems used in indoor environments. A key parameter investigated is the interference in such systems. In the interference analysis a special focus is placed on adjacent channel interference since the jamming entity and victim entity can be in close proximity. The interference analysis shows that co–location of BS’s using adjacent channels is not feasible for an adjacent channel protection factor that is less than 40 dB and frame synchronisation errors of more than 10%. Furthermore, it is demonstrated that ideal frame synchronisation does not necessarily yield the highest capacity. As a consequence, a new technique termed ’TS–opposing’ is introduced. This method is intended to enable a cellular TD–CDMA/TDD system to apply cell independent channel asymmetry. For this purpose, a centralised DCA is developed. It is found that this algorithm indeed enables neighbouring cells to adopt different rates of asymmetry without a significant capacity loss. Moreover, a decentralised DCA algorithm based on the TS–opposing principle is developed. In this context, a novel TS assignment concept is proposed which reduces the complexity associated with the TS–opposing technique. In addition, the TS assignment plan allows for full spatial coverage. It is shown that the capacity of a TD–CDMA/TDD interface can be greater than the capacity of an equivalent FDD interface. The performance of the decentralised DCA algorithm is limited by the interference in the uplink. Therefore, additional methods which assist in reducing the interference in the uplink are envisaged to further improve the performance of the decentralised DCA algorithm. The exploitation of the TS–opposing technique in two different ways demonstrates that this method can be used to improve the performance of a TD–CDMA/TDD system significantly