386 research outputs found

    Intercell interference mitigation in long term evolution (LTE) and LTE-advanced

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    University of Technology Sydney. Faculty of Engineering and Information Technology.Bandwidth is one of the limited resources in Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks. Therefore, new resource allocation techniques such as the frequency reuse are needed to increase the capacity in LTE and LTE-A. However, the system performance is severely degraded using the same frequency in adjacent cells due to increase of intercell interference. Therefore, the intercell interference management is a critical point to improve the performance of the cellular mobile networks. This thesis aims to mitigate intercell interference in the downlink LTE and LTE-A networks. The first part of this thesis introduces a new intercell interference coordination scheme to mitigate downlink intercell interference in macrocell-macrocell scenario based on user priority and using fuzzy logic system (FLS). A FLS is an expert system which maps the inputs to outputs using “IF...THEN” rules and an aggregation method. Then, the final output is obtained through a deffuzifaction approach. Since this thesis aims to mitigate interference in downlink LTE networks, the inputs of FLS are selected from important metrics such as throughput, signal to interference plus noise ratio and so on. Simulation results demonstrate the efficacy of the proposed scheme to improve the system performance in terms of cell throughput, cell edge throughput and delay when compared with reuse factor one. Thereafter, heterogeneous networks (HetNets) are studied which are used to increase the coverage and capacity of system. The focus of the next part of this thesis is picocell because it is one of the important low power nodes in HetNets which can efficiently improve the overall system capacity and coverage. However, new challenges arise to intercell interference management in macrocell-picocell scenario. Three enhanced intercell interference coordination (eICIC) schemes are proposed in this thesis to mitigate the interference problem. In the first scheme, a dynamic cell range expansion (CRE) approach is combined with a dynamic almost blank subframe (ABS) using fuzzy logic system. In the second scheme, a fuzzy q-learning (FQL) approach is used to find the optimum ABS and CRE offset values for both full buffer traffic and video streaming traffic. In FQL, FLS is combined by q-learning approach to optimally select the best consequent part of each FLS rule. In the third proposed eICIC scheme, the best location of ABSs in each frame is determined using Genetic Algorithm such that the requirements of video streaming traffic can be met. Simulation results show that the system performance can be improved through the proposed schemes. Finally, the optimum CRE offset value and the required number of ABSs will be mathematically formulated based on the outage probability, ergodic rate and minimum required throughput of users using stochastic geometry tool. The results are an analytical formula that leads to a good initial estimate through a simple approach to analyse the impact of system parameters on CRE offset value and number of ABSs

    A survey of self organisation in future cellular networks

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    This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

    Techniques for Efficient Spectrum Usage for Next Generation Mobile Communication Networks. An LTE and LTE-A Case Study

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    A Multi-Agent Neural Network for Dynamic Frequency Reuse in LTE Networks

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    Fractional Frequency Reuse techniques can be employed to address interference in mobile networks, improving throughput for edge users. There is a tradeoff between the coverage and overall throughput achievable, as interference avoidance techniques lead to a loss in a cell's overall throughput, with spectrum efficiency decreasing with the fencing off of orthogonal resources. In this paper we propose MANN, a dynamic multiagent frequency reuse scheme, where individual agents in charge of cells control their configurations based on input from neural networks. The agents' decisions are partially influenced by a coordinator agent, which attempts to maximise a global metric of the network (e.g., cell-edge performance). Each agent uses a neural network to estimate the best action (i.e., cell configuration) for its current environment setup, and attempts to maximise in turn a local metric, subject to the constraint imposed by the coordinator agent. Results show that our solution provides improved performance for edge users, increasing the throughput of the bottom 5% of users by 22%, while retaining 95% of a network's overall throughput from the full frequency reuse case. Furthermore, we show how our method improves on static fractional frequency reuse schemes

    Models and optimisation methods for interference coordination in self-organising cellular networks

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    A thesis submitted for the degree of Doctor of PhilosophyWe are at that moment of network evolution when we have realised that our telecommunication systems should mimic features of human kind, e.g., the ability to understand the medium and take advantage of its changes. Looking towards the future, the mobile industry envisions the use of fully automatised cells able to self-organise all their parameters and procedures. A fully self-organised network is the one that is able to avoid human involvement and react to the fluctuations of network, traffic and channel through the automatic/autonomous nature of its functioning. Nowadays, the mobile community is far from this fully self-organised kind of network, but they are taken the first steps to achieve this target in the near future. This thesis hopes to contribute to the automatisation of cellular networks, providing models and tools to understand the behaviour of these networks, and algorithms and optimisation approaches to enhance their performance. This work focuses on the next generation of cellular networks, in more detail, in the DownLink (DL) of Orthogonal Frequency Division Multiple Access (OFDMA) based networks. Within this type of cellular system, attention is paid to interference mitigation in self-organising macrocell scenarios and femtocell deployments. Moreover, this thesis investigates the interference issues that arise when these two cell types are jointly deployed, complementing each other in what is currently known as a two-tier network. This thesis also provides new practical approaches to the inter-cell interference problem in both macro cell and femtocell OFDMA systems as well as in two-tier networks by means of the design of a novel framework and the use of mathematical optimisation. Special attention is paid to the formulation of optimisation problems and the development of well-performing solving methods (accurate and fast)

    Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

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    Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
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