Optimal Placement Of Base Stations Research Articles

Optimal Placement of Base Stations in Integrated Design of Wireless Networks

Optimal Placement of Base Stations in Integrated Design of Wireless Networks

Optimal placement of base stations in border surveillance using limited capacity drones

Imagine an island modeled as a simple polygon P with n vertices whose coastline we wish to monitor. We consider the problem of building the minimum number of refueling stations along the boundary of P in such a way that a drone can follow a polygonal route enclosing the island without running out of fuel. A drone can fly a maximum distance d between consecutive stations and is restricted to move either along the boundary of P or its exterior (i.e., over water). We present an algorithm that, given P, finds the locations for a set of refueling stations whose cardinality is at most the optimal plus one. The time complexity of this algorithm is O(n2+Ldn), where L is the length of P. We also present an algorithm that returns an additive ϵ-approximation for the problem of minimizing the fuel capacity required for the drones when we are allowed to place k base stations around the boundary of the island; this algorithm also finds the locations of these refueling stations. Finally, we propose a practical discretization heuristic which, under certain conditions, can be used to certify optimality of the results.

Measurement and Analysis of Quality of Service of Mobile Networks in Afghanistan – End User Perspective

Enhanced Quality of Service (QoS) and satisfaction of mobile phone user are major concerns of a service provider. In order to manage network efficiently and to provide enhanced end to end Quality of Experience (QoE), operator is expected to measure and analyze QoS from various perspectives and at different relevant points of network. The scope of this paper is measurement and statistically analysis of QoS of mobile networks from end user perspective in Afghanistan. The study is based on primary data collected on random basis from 1,515 mobile phone users of five cellular operators. The paper furthermore proposes adequate technical solutions to mobile operators in order to address existing challenges in the area of QoS and to remain competitive in the market. Based on the result of processed data, considering geographical locations, population and telecom regulations of the government, authors recommend deployment of small cells (SCs), increasing number of regular performance tests, optimal placement of base stations, increasing number of carriers, and high order sectorization as proposed technical solutions.

English

English

Base Station Placement for Wireless Sensor Network Positioning System via Lexicographical Stratified Programming

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

Optimal base station placement for wireless sensor networks with successive interference cancellation.

We consider the base station placement problem for wireless sensor networks with successive interference cancellation (SIC) to improve throughput. We build a mathematical model for SIC. Although this model cannot be solved directly, it enables us to identify a necessary condition for SIC on distances from sensor nodes to the base station. Based on this relationship, we propose to divide the feasible region of the base station into small pieces and choose a point within each piece for base station placement. The point with the largest throughput is identified as the solution. The complexity of this algorithm is polynomial. Simulation results show that this algorithm can achieve about 25% improvement compared with the case that the base station is placed at the center of the network coverage area when using SIC.

Effectiveness-based Voronoi partition: a new tool for solving a class of location optimization problems

In this article we provide a framework for optimal placement or deployment of facilities in a region of interest. We present a generalization of Voronoi partition, where functions modeling the effectiveness of facilities are used in the place of the usual distance measure used in the standard Voronoi partition and its variations. We illustrate the usefulness of the generalization in designing strategies for optimal deployment of multiple vehicles equipped with sensors, optimal placement of base stations in a cellular network design problem, and locational optimization of power plants.

Development of a Hybrid Algorithm for Efficient Optimisation of Base Station Placement for Indoor Wireless Communication Systems

A new hybrid algorithm termed Reduction Estimation--Combinatorial Optimisation--Reduction Approximation is proposed to identify an optimal base station placement as a subset of a known set of potential sites to provide wireless communication services to a given set of stationary users. Both forward and reverse link signal-to-interference ratios are considered, and the performance of the proposed algorithm is reported for several representative case studies and compared with Brute Force Search and existing optimisation algorithms (including Genetic, Ngadiman and Greedy algorithms). For the cases considered, the proposed algorithm is found to be superior to the existing algorithms in that it can yield an optimal deployment (equivalent to Brute Force Search) in an acceptable time.

Optimal base station placement in wireless sensor networks

Base station location has a significant impact on network lifetime performance for a sensor network. For a multihop sensor network, this problem is particularly challenging due to its coupling with data routing. This article presents an approximation algorithm that can guarantee (1 − ε)-optimal network lifetime performance for base station placement problem with any desired error bound ε > 0. The proposed (1 − ε)-optimal approximation algorithm is based on several novel techniques that makes it possible to reduce an infinite search space to a finite-element search space for base station location. The first technique used in this reduction is to discretize cost parameter (associated with energy consumption) with performance guarantee. Subsequently, the continuous search space can be broken up into a finite number of subareas. The second technique is to exploit the cost property of each subarea and represent it by a novel notion called fictitious cost point, each with guaranteed cost bounds. We give a proof that the proposed base station placement algorithm is (1− ε)-optimal. This approximation algorithm is simpler and faster than a state-of-the-art algorithm and represents the best known result to the base station placement problem.