Cell identity allocation and optimisation of handover parameters in self-organised LTE femtocell networks

A thesis submitted to the University of Bedfordshire in partial ful lment of the requirements for the degree of Doctor of PhilosophyFemtocell is a small cellular base station used by operators to extend indoor service coverage and enhance overall network performance. In Long Term Evolution (LTE), femtocell works under macrocell coverage and combines with the macrocell to constitute the two-tier network. Compared to the traditional single-tier network, the two-tier scenario creates many new challenges, which lead to the 3rd Generation Partnership Project (3GPP) implementing an automation technology called Self-Organising Network (SON) in order to achieve lower cost and enhanced network performance. This thesis focuses on the inbound and outbound handovers (handover between femtocell and macrocell); in detail, it provides suitable solutions for the intensity of femtocell handover prediction, Physical Cell Identity (PCI) allocation and handover triggering parameter optimisation. Moreover, those solutions are implemented in the structure of SON. In order to e ciently manage radio resource allocation, this research investigates the conventional UE-based prediction model and proposes a cell-based prediction model to predict the intensity of a femtocell's handover, which overcomes the drawbacks of the conventional models in the two-tier scenario. Then, the predictor is used in the proposed dynamic group PCI allocation approach in order to solve the problem of PCI allocation for the femtocells. In addition, based on SON, this approach is implemented in the structure of a centralised Automated Con guration of Physical Cell Identity (ACPCI). It overcomes the drawbacks of the conventional method by reducing inbound handover failure of Cell Global Identity (CGI). This thesis also tackles optimisation of the handover triggering parameters to minimise handover failure. A dynamic hysteresis-adjusting approach for each User Equipment (UE) is proposed, using received average Reference Signal-Signal to Interference plus Noise Ratio (RS-SINR) of the UE as a criterion. Furthermore, based on SON, this approach is implemented in the structure of hybrid Mobility Robustness Optimisation (MRO). It is able to off er the unique optimised hysteresis value to the individual UE in the network. In order to evaluate the performance of the proposed approach against existing methods, a System Level Simulation (SLS) tool, provided by the Centre for Wireless Network Design (CWiND) research group, is utilised, which models the structure of two-tier communication of LTE femtocell-based networks

Context-Aware Self-Healing for Small Cell Networks

These can be an invaluable source of information for the management of the network, in a way that we have denominated as context-aware SON, which is the approach proposed in this thesis. To develop this concept, the thesis follows a top-down approach. Firstly, the characteristics of the cellular deployments are assessed, especially for indoor small cell networks. In those scenarios, the need for context-aware SON is evaluated and considered indispensable. Secondly, a new cellular architecture is defined to integrate both context information and SON mechanisms in the management plane of the mobile network. Thus, the specifics of making context an integral part of cellular OAM/SON are defined. Also, the real-world implementation of the architecture is proposed. Thirdly, from the established general SON architecture, a logical self-healing framework is defined to support the context-aware healing mechanisms to be developed. Fourthly, different self-healing algorithms are defined depending on the failures to be managed and the conditions of the considered scenario. The mechanisms are based on probabilistic analysis, making use of both context and network data for detection and diagnosis of cellular issues. The conditions for the implementation of these methods are assessed. Their applicability is evaluated by means of simulators and testbed trials. The results show important improvements in performance and capabilities in comparison to previous methods, demonstrating the relevance of the proposed approach.The last years have seen a continuous increase in the use of mobile communications. To cope with the growing traffic, recently deployed technologies have deepened the adoption of small cells (low powered base stations) to serve areas with high demand or coverage issues, where macrocells can be both unsuccessful or inefficient. Also, new cellular and non-cellular technologies (e.g. WiFi) coexist with legacy ones, including also multiple deployment schemes (macrocell, small cells), in what is known as heterogeneous networks (HetNets). Due to the huge complexity of HetNets, their operation, administration and management (OAM) became increasingly difficult. To overcome this, the NGMN Alliance and the 3GPP defined the Self-Organizing Network (SON) paradigm, aiming to automate the OAM procedures to reduce their costs and increase the resulting performance. One key focus of SON is the self-healing of the network, covering the automatic detection of problems, the diagnosis of their causes, their compensation and their recovery. Until recently, SON mechanisms have been solely based on the analysis of alarms and performance indicators. However, on the one hand, this approach has become very limited given the complexity of the scenarios, and particularly in indoor cellular environments. Here, the deployment of small cells, their coexistence with multiple telecommunications systems and the nature of those environments (in terms of propagation, coverage overlapping, fast demand changes and users' mobility) introduce many challenges for classic SON. On the other hand, modern user equipment (e.g. smartphones), equipped with powerful processors, sensors and applications, generate a huge amount of context information. Context refers to those variables not directly associated with the telecommunication service, but with the terminals and their environment. This includes the user's position, applications, social data, etc

Mobile Offloading in Residential Wireless Access Markets

The growth of mobile data traffic has been increasing at a tremendous pace. Currently, mobile broadband is mostly served by macro base stations. Strong attenuation occurs when the signals penetrate through buildings affecting the quality of service. Hence, mobile operators need to enhance the capacity to minimise congestion problems and improve the coverage on their macro networks for better network operation. As most of the mobile traffic occurs indoors, there is a need for indoor network deployments. A qualitative analysis employing the combination of various research methods (value network configuration, system dynamics, expert interviews) has been carried out to investigate various factors besides mobile offloading, which could lead to a large-scale deployment of femtocells in homes with the focus on Finland. This study also discusses several options to cope with the mobile traffic growth and examines different indoor network deployment scenarios. Furthermore, the scenarios of Femtocell-as-a-Service are highlighted and its possible impacts on mobile operators’ business are covered as well. The analysis is also conducted to illustrate how different actors are interrelated in the home network business. The analysis reveals that the primary factor that will contribute to the success of femtocell deployment in homes is the need for future mobile offloading. However, many other factors have important implications which require careful consideration by mobile operators. With the presence of good macro network capacity like in Finland, new services and partnership with third party providers has been identified as the most important factor. Mobile operators need to offer an incentive to attract end-users to adopt a femtocell service due to the strong positioning of WiFi in homes. Therefore, new services would also enable the penetration of femtocells into homes to compete with WiFi access points. Three factors (interference mitigation and interoperability, femtocell management system, backhaul) are also important as these are needed to ensure the femtocell networks operate reliably. As lowering the cost is essential for building scale, the model of Femtocell-as-a-Service is useful as it reduces capital investments for mobile operators. Interviews with the experts found that major mobile operators are less likely to adopt this model. This is better suited for smaller mobile operators that want to quickly enter the femtocell business

LTE Advanced: Technology and Performance Analysis

Wireless data usage is increasing at a phenomenal rate and driving the need for continued innovations in wireless data technologies to provide more capacity and higher quality of service. In October 2009, 3rd Generation Partnership Project (3GPP) submitted LTE-Advanced to the ITU as a proposed candidate IMT-Advanced technology for which specifications could become available in 2011 through Release-10 . The aim of “LTE-Advanced” is to further enhance LTE radio access in terms of system performance and capabilities compared to current cellular systems, including the first release of LTE, with a specific goal to ensure that LTE fulfills and even surpass the requirements of “IMT-Advanced” as defined by the International Telecommunication Union (ITU-R) . This thesis offers an introduction to the mobile communication standard known as LTE Advanced, depicting the evolution of the standard from its roots and discussing several important technologies that help it evolve to accomplishing the IMT-Advanced requirements. A short history of the LTE standard is offered, along with a discussion of its standards and performance. LTE-Advanced details include analysis on the physical layer by investigating the performance of SC-FDMA and OFDMA of LTE physical layer. The investigation is done by considering different modulation schemes (QPSK, 16QAM and 64QAM) on the basis of PAPR, BER, power spectral density (PSD) and error probability by simulating the model of SC-FDMA & OFDMA. To evaluate the performance in presence of noise, an Additive White Gaussian Noise (AWGN) channel was introduced. A set of conclusions is derived from our results describing the effect of higher order modulation schemes on BER and error probability for both OFDMA and SC-FDMA. The power spectral densities of both the multiple access techniques (OFDMA and SC-FDMA) are calculated and result shows that the OFDMA has higher power spectral density.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Context-aware Self-Optimization in Small-Cell Networks

Most mobile communications take place at indoor environments, especially in commercial and corporate scenarios. These places normally present coverage and capacity issues due to the poor signal quality, which degrade the end-user Quality of Experience (QoE). In these cases, mobile operators are offering small cells to overcome the indoor issues, being femtocells the main deployed base stations. Femtocell networks provide significant benefits to mobile operators and their clients. However, the massive integration and the particularities of femtocells, make the maintenance of these infrastructures a challenge for engineers. In this sense, Self-Organizing Networks (SON) techniques play an important role. These techniques are a key feature to intelligently automate network operation, administration and management procedures. SON mechanisms are based on the analysis of the mobile network alarms, counters and indicators. In parallel, electronics, sensors and software applications evolve rapidly and are everywhere. Thanks to this, valuable context information can be gathered, which properly managed can improve SON techniques performance. Within possible context data, one of the most active topics is the indoor positioning due to the immediate interest on indoor location-based services (LBS). At indoor commercial and corporate environments, user densities and traffic vary in spatial and temporal domain. These situations lead to degrade cellular network performance, being temporary traffic fluctuations and focused congestions one of the most common issues. Load balancing techniques, which have been identified as a use case in self-optimization paradigm for Long Term Evolution (LTE), can alleviate these congestion problems. This use case has been widely studied in macrocellular networks and outdoor scenarios. However, the particularities of femtocells, the characteristics of indoor scenarios and the influence of users’ mobility pattern justify the development of new solutions. The goal of this PhD thesis is to design and develop novel and automatic solutions for temporary traffic fluctuations and focused network congestion issues in commercial and corporate femtocell environments. For that purpose, the implementation of an efficient management architecture to integrate context data into the mobile network and SON mechanisms is required. Afterwards, an accurate indoor positioning system is developed, as a possible inexpensive solution for context-aware SON. Finally, advanced self-optimization methods to shift users from overloaded cells to other cells with spare resources are designed. These methods tune femtocell configuration parameters based on network information, such as ratio of active users, and context information, such as users’ position. All these methods are evaluated in both a dynamic LTE system-level simulator and in a field-trial

Software-defined Networking enabled Resource Management and Security Provisioning in 5G Heterogeneous Networks

Due to the explosive growth of mobile data traffic and the shortage of spectral resources, 5G networks are envisioned to have a densified heterogeneous network (HetNet) architecture, combining multiple radio access technologies (multi-RATs) into a single holistic network. The co-existing of multi-tier architectures bring new challenges, especially on resource management and security provisioning, due to the lack of common interface and consistent policy across HetNets. In this thesis, we aim to address the technical challenges of data traffic management, coordinated spectrum sharing and security provisioning in 5G HetNets through the introduction of a programmable management platform based on Software-defined networking (SDN). To address the spectrum shortage problem in cellular networks, cellular data traffic is efficiently offloaded to the Wi-Fi network, and the quality of service of user applications is guaranteed with the proposed delay tolerance based partial data offloading algorithm. A two-layered information collection is also applied to best load balancing decision-making. Numerical results show that the proposed schemes exploit an SDN controller\u27s global view of the HetNets and take optimized resource allocation decisions. To support growing vehicle-generated data traffic in 5G-vehicle ad hoc networks (VANET), SDN-enabled adaptive vehicle clustering algorithm is proposed based on the real-time road traffic condition collected from HetNet infrastructure. Traffic offloading is achieved within each cluster and dynamic beamformed transmission is also applied to improve trunk link communication quality. To further achieve a coordinated spectrum sharing across HetNets, an SDN enabled orchestrated spectrum sharing scheme that integrates participating HetNets into an amalgamated network through a common configuration interface and real-time information exchange is proposed. In order to effectively protect incumbent users, a real-time 3D interference map is developed to guide the spectrum access based on the SDN global view. MATLAB simulations confirm that average interference at incumbents is reduced as well as the average number of denied access. Moreover, to tackle the contradiction between more stringent latency requirement of 5G and the potential delay induced by frequent authentications in 5G small cells and HetNets, an SDN-enabled fast authentication scheme is proposed in this thesis to simplify authentication handover, through sharing of user-dependent secure context information (SCI) among related access points. The proposed SCI is a weighted combination of user-specific attributes, which provides unique fingerprint of the specific device without additional hardware and computation cost. Numerical results show that the proposed non-cryptographic authentication scheme achieves comparable security with traditional cryptographic algorithms, while reduces authentication complexity and latency especially when network load is high

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