Optimal and practical handover decision algorithms in heteregeneous marco-femto cellular networks

Driven by the smart tablet/phone revolution and the proliferation of bandwidth hungry applications such as cloud computing and streaming video, the demand for high data rate wireless communication is increasing tremendously. In order to meet the increasing demand from subscribers, wireless operators are in the process of augmenting their macrocell network with supplemental infrastructure such as microcells, distributed antennas and relays. An alternative with lower upfront costs is to improve indoor coverage and capacity by using end-consumer installed femtocells. A femtocell is a low power, short range (up to 100 meters coverage radius) cellular wireless access point (AP), functioning in service provider owned licensed spectrum. Due to the proximity of end users to the femtocell access points, APs are able to provide higher end-user QoE and better spatial reuse of limited spectrum. Femtocells are useful in offloading the macro-cellular network as well as reducing the operating and capital expenditure costs for operators. Femtocells coexist with legacy cellular networks consisting of macrocells. In this emerging combined architecture, large number of Femtocell Application Point (FAPs) is randomly deployed in the coverage area of macro BSs. However, several problems related to MM (mobility management) and RM (resource management) in this combined architecture still remain to be solved. The ad hoc deployment of FAPs and asymmetric radio communication and call processing capabilities between macrofemto networks are the primary causes of these problems. Uncoordinated deployment of FAPs providing indoor oriented wireless access service within the macro coverage may cause severe interference problems that need to be mitigated and handled by RM/MM schemes. The MM decisions should take into account the resource constraints and UE mobility in order to prevent unnecessary or undesirable handovers towards femtocells. Ignoring these factors in MM decisions may lead to low customer satisfaction due to mismanagement of handover events in the combined macro-femto network, delayed signaling traffic and unsatisfactory call/connection quality. In order to address all of the aforementioned issues, the handover decision problem in combined femto-macro networks has been formulated as a multi-objective non-linear optimization problem. Since there are no known analytical solution to this problem, an MDP (Markov Decision Process) based heuristic has been proposed as a practical and optimal HO (handover) decision making scheme. This heuristic has been updated and improved in an iterative manner and has also been supported by a dynamic SON (Self Organizing Networks) algorithms that is based on heuristic's components. The performance results show that the final version of MDP based heuristic has signi cantly superior performance in terms offloading the macro network, minimizing the undesirable network events (e.g. outage and admission rejection) when compared to state-of-art handover algorithms

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR)

Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Efficient offloading and load distribution based on D2D relaying and UAVs for emergent wireless networks

The device to device (D2D) and unmanned aerial vehicle (UAV) communications are considered as enabling technologies of the emergent 5th generation of wireless and cellular system (5G). Consequently, it is important to determine their corresponding performance with respect to the 5G requirements. In particular, we focus on enhancing the offloading and load balancing performance in three directions. In the first direction, we study the achievable data rate of user relay assisting other users in two-tier networks. We propose a novel heuristic communication scheme called device-for-device (D4D). The D4D enables moving users to share their resource by taking advantage of cooperative communication. We study the moving user rate sensitivity to the relay selection and blocking probability. In the second direction, we study the offloading from macrocell to small cell and load balancing among small cell. Also, we design a new utility weight function that enables a balanced relay assignment. We propose a novel low complexity algorithm for centralized scheme maximizing the load among small cells as well as users subject to SINR threshold constraints. The simulations show that our proposed schemes achieve performance in load balancing compared to those obtained with the previous or traditional method. In the third direction, we study the 3D deployment of multiple UAVs for emergent on-demand offloading. We propose a novel on-demand deployment scheme based on maximizing both the operator’s profit and the quality of service. The proposed scheme is based on solving a non-convex problem by combining k-means clustering with pattern search to find the suboptimal location of UAVs. The simulation results show that our proposed scheme maximizes the operator’s profit and improves offloading traffic efficiency. Our global contribution was the development of a scheme to improve the quality of service and the performance in emergent networks through the improvement of the load distribution and resource sharing using D2D and UAV

Handover management strategies in LTE-advanced heterogeneous networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Meeting the increasing demand for data due to the proliferation of high-specification mobile devices in the cellular systems has led to the improvement of the Long Term Evolution (LTE) framework to the LTE-Advanced systems. Different aspects such as Massive Multiple-Input Multiple Output (MIMO), Orthogonal Frequency Division Multiple Access (OFDMA), heterogeneous networks and Carrier Aggregation have been considered in the LTE-Advanced to improve the performance of the system. The small cells like the femtocells and the relays play a significant role in increasing the coverage and the capacity of the mobile cellular networks in LTE-Advanced (LTE-A) heterogeneous network. However, the user equipment (UE) are faced with the frequent handover problems in the heterogeneous systems than the homogeneous systems due to the users‟ mobility and densely populated cells. The objective of this research work is to analyse the handover performance in the current LTE/LTE-A network and to propose various handover management strategies to handle the frequent handover problems in the LTE-Advance heterogeneous networks. To achieve this, an event driven simulator using C# was developed based on the 3GPP LTE/LTE-A standard to evaluate the proposed strategies. To start with, admission control which is a major requirement during the handover initiation stage is discussed and this research work has therefore proposed a channel borrowing admission control scheme for the LTE-A networks. With this scheme in place, resources are better utilized and more calls are accepted than in the conventional schemes where the channel borrowing is not applied. Also proposed is an enhanced strategy for the handover management in two-tier femtocell-macrocell networks. The proposed strategy takes into consideration the speed of user and other parameters in other to effectively reduce the frequent and unnecessary handovers, and as well as the ratio of target femtocells in the system. We also consider scenarios such as the one that dominate the future networks where femtocells will be densely populated to handle very heavy traffic. To achieve this, a Call Admission Control (CAC)-based handover management strategy is proposed to manage the handover in dense femtocell-macrocell integration in the LTE-A network. The handover probability, the handover call dropping probability and the call blocking probability are reduced considerably with the proposed strategy. Finally, the handover management for the mobile relays in a moving vehicle is considered (using train as a case study). We propose a group handover strategy where the Mobile Relay Node (MRN) is integrated with a special mobile device called “mdev” to prepare the group information prior to the handover time. This is done to prepare the UE‟s group information and services for timely handover due to the speed of the train. This strategy reduces the number of handovers and the call dropping probability in the moving vehicle.Publications and conferences listed on page iv-v

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

System optimisation and radio planning for future LTE-advanced

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis work is related to wireless communication. In this Thesis three main issues are addressed for future cellular networks: power consumption, interference and mobility. These issues continue to be a burden on the system’s performance as long as technology keeps evolving. In the presented chapters, the focus was to introduce greater intelligence to the LTE system algorithms and bring to them a dynamic and self-organizing approach. The first approach concerns power consumption in wireless terminals. The currently applied solution to save energy is the DRX mechanism. It organizes the time when the terminal wakes up and starts receiving data, and when it goes into sleep mode in order to save its battery power. The current DRX is described as static or fixed which makes its parameters unsuitable for the nature of the bursty traffic. In this work an adaptive DRX mechanism is proposed and evaluated as the wireless terminal battery saving algorithm. The second approach is co-channel interference mitigation. To increase the system’s capacity and avoid spectrum scarcity, small cells such as Femtocells are deployed and operate on the same frequency bands as the Macrocell. Although these small nodes increase the system capacity, however, the challenges will be in the femtocells planning and management in addition to the interference issues. Here a dynamic interference cancellation approach is presented to enable the Femtocell to track the allocated resources to the Macro-users, and to avoid using them. The third approach concerns mobility management in heterogeneous networks. The wireless terminal may have different mobility levels during handover which increases the handover failures due to failure in handover commands and aging of the reported parameters. This issue is presented in detail with the aim to avoid performance degradation and improve the reporting mechanisms during fast mobility levels. For this regard the presented method proposes more cooperation between the serving cell and the end-user so that the large amount of overhead and measurement are reduced. Simulations with different configurations are conducted to present the results of the proposed models. Results show that the proposed models bring improvements to the LTE system. The enhanced self-organized architecture in the three presented approaches performs well in terms of power saving, dynamic spectrum utilization by Femtocells, and mitigation of sudden throughput degradation due to the serving cell’s downlink signal outage during mobility.Brunel University Londo