576 research outputs found

    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

    Applications of Soft Computing in Mobile and Wireless Communications

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    Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

    Participatory sensing as an enabler for self-organisation in future cellular networks

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    In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells

    Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

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    Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

    MODELS FOR GREENFIELD AND INCREMENTAL CELLULAR NETWORK PLANNING

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    Mobility, as provided in cellular networks, is largely affected by the location of the base stations. To a large extent, the location of base stations is determined by the quantity of base stations available to provide coverage. It is therefore not surprising that the quantity and subsequent location of base stations will not only impact service delivery but also have a large associated cost for implementation. Generally, the higher the quantity of base stations required to provide coverage, the greater the cost of implementation and operation of the radio network. This thesis proposes a modified optimization model to aid the cell planning process. This model, unlike those surveyed, is applicable to both green field and incremental network designs. The variation in model design is fundamental in ensuring cost effective growth and expansion of cellular networks. Numerical studies of the modified model applied to both abstract and real system configurations are carried out using MATLAB. Terrain data from Kampala, Uganda, was used to aid the study. Results show that the antenna height significantly determines the solution of the objective function. In addition, it is shown that slight variations in the cost association between the antenna height and the site construction requirements can be decisively used for predefined targeted network planning. A comparison is also made between an actual network installation and the estimates provided by the model. As expected, results from the study show that the difference between the estimated count and the actual count can be adEquately minimized by slight variations in antenna height requirements
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