Coverage in WLAN with minimum number of access points

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Optimal placement of access point in WLAN based on a new algorithm

When designing wireless communication systems, it is very important to know the optimum numbers and locations for the access points (APs). The impact of incorrect placement of APs is significant. If they are placed too far apart, they will generate a coverage gap, but if they are too close to each other, this will lead to excessive co-channel interferences. In this paper we describe a mathematical model developed to find the optimal number and location of APs. To solve the problem, we use the Discrete Gradient optimization algorithm developed at the University of Ballarat. Results indicate that our model is able to solve optimal coverage problems for different numbers of users

An approach for the design of infrastructure mode indoor WLAN based on ray tracing and a binary optimizer

This paper presents an approach that combines a ray tracing tool with a binary version of the particle swarm optimization method (BPSO) for the design of infrastructure mode indoor wireless local area networks (WLAN). The approach uses the power levels of a set of candidate access point (AP) locations obtained with the ray tracing tool at a mesh of potential receiver locations or test points to allow the BPSO optimizer to carry out the design of the WLAN. For this purpose, several restrictions are imposed through a fitness function that drives the search towards the selection of a reduced number of AP locations and their channel assignments, keeping at the same time low transmission power levels. During the design, different coverage priority areas can be defined and the signal to interference ratio (SIR) levels are kept as high as possible in order to comply with the Quality of Service (QoS) requirements imposed. The performance of this approach in a real scenario at the author´s premises is reported, showing its usefulness.This work was supported by the Spanish Ministry of Science and Innovation (TEC2008-02730) and the Spanish Ministry of Economy and Competitiveness (TEC2012-33321)

A multiobjective Tabu framework for the optimization and evaluation of wireless systems

This chapter will focus on the multiobjective formulation of an optimization problem and highlight the assets of a multiobjective Tabu implementation for such problems. An illustration of a specific Multiobjective Tabu heuristic (referred to as MO Tabu in the following) will be given for 2 particular problems arising in wireless systems. The first problem addresses the planning of access points for a WLAN network with some Quality of Service requirements and the second one provides an evaluation mean to assess the performance evaluation of a wireless sensor network. The chapter will begin with an overview of multiobjective (MO) optimization featuring the definitions and concepts of the domain (e.g. Dominance, Pareto front,...) and the main MO search heuristics available so far. We will then emphasize on the definition of a problem as a multiobjective optimization problem and illustrate it by the two examples from the field of wireless networking. The next part will focus on MO Tabu, a Tabu-inspired multiobjective heuristic and describe its assets compared to other MO heuristics. The last part of the chapter will show the results obtained with this MO Tabu strategy on the 2 wireless networks related problems. Conclusion on the use of Tabu as a multiobjective heuristic will be drawn based on the results presented so far

Алгоритм розміщення базових станцій для крупно масштабних гетерогенних LТЕ мереж

Мета роботи заключається в знаходженні оптимального еволюційного алгоритму для оптимізації процесу розміщення базових станцій стандарту LTE. Результати цього дослідження можуть бути використані для розміщення нових стільників та для оптимізації вже наявних мереж стандарту LTE . Або ж на основі цих даних можна розробити інше рішення , для великої варіації застосувань еволюційних алгоритмі у світовій практиці.Рurроse of the work is to find the optimal evolutionary algorithm for optimizing the process of LTE base stations deployment. The results of this study can be used to deploy new cells and to optimize existing LTE networks. Or on the basis of these data it is possible to develop new decision, for the big variation of applications of evolutionary algorithm in world practice

Power minimization and optimum ONU placements in integrated wireless optical access networks

The deployment of optical fibre in place of copper cable in access networks has experienced remarkable growth over the past several years due to a wide range of benefits. A major benefit of optical fibre over copper cable is that it is more secure and immune to electromagnetic interferences. Optical fibre has also provided the capability of handling higher throughputs for longer distances, and experiences no crosstalk between other fibre optic cables. However, the last mile reach to end-users with optical fibre is very costly. This alternative replacement results in increased costs for manual labour and energy consumption in the access network. The current demand in all areas of telecommunications, and especially access networks, is greener networking. In order to offset the high costs of optical access implementations and to satisfy this demand, an investigation into integrated wireless optical access networks (IWOAN) is warranted. The proliferation of wireless devices has also motivated the interest in IWOAN as it combines the flexibility and efficiency of wireless with the security and stability provided by optical. With the emergence of smart phones and tablets, wireless access networks are now supporting an increasing amount of traffic volume with improved throughput and accessibility. We employ a Passive Optical Network (PON) infrastructure from the central office to the customer, traced from the Optical Line Terminal (OLT) to the customer premises devices known as Optical Network Units (ONUs) for IWOAN. At the ONU, the optical fibre is terminated and wireless communication is implemented. The ONU acts as a wireless access point/gateway for wireless Base Stations (BS) serving different coverage areas in point-to-point topology. With recent trends of advanced wireless technologies, premium rich applications such as multimedia streaming, interactive gaming and cloud computing are delivered in a satisfactory and economic way. This wireless-optical integration aims to reduce and solve the cost of replacing copper cables. However, another issue is raised with increased costs in energy consumption due to the integration of wireless and optical communication. Typically a large number of ONUs need to be deployed in order to serve many wireless BSs located in different coverage areas. As a result, any cost savings gained by the integration process is exhausted with the increased cost of power consumption

The automatic placement of multiple indoor antennas using Particle Swarm Optimisation

In this thesis, a Particle Swarm Optimization (PSO) method combined with a ray propagation method is presented as a means to optimally locate multiple antennas in an indoor environment. This novel approach uses Particle Swarm Optimisation combined with geometric partitioning. The PSO algorithm uses swarm intelligence to determine the optimal transmitter location within the building layout. It uses the Keenan-Motley indoor propagation model to determine the fitness of a location. If a transmitter placed at that optimum location, transmitting a maximum power is not enough to meet the coverage requirements of the entire indoor space, then the space is geometrically partitioned and the PSO initiated again independently in each partition. The method outputs the number of antennas, their effective isotropic radiated power (EIRP) and physical location required to meet the coverage requirements. An example scenario is presented for a real building at Loughborough University and is compared against a conventional planning technique used widely in practice