Oct 26, 2021 · Abstract: Base Station is the primary unit of any mobile communication system. An antenna is the most important part of the Base Station as it is responsible for exchange of all
Dec 1, 2024 · Base Transceiver Stations (BTSs), are foundational to mobile networks but are vulnerable to power failures, disrupting service delivery and causing user inconvenience. This
May 17, 2021 · This paper proposes a scattering area model for processing multipath parameters achieve single base station positioning. First of all, we construct a scattering area model based
Feb 1, 2014 · Due to the introduction of newer technologies like Long Term Evolution (LTE) in already deployed cellular access networks, changes in the energy-efficiency of networks
Feb 3, 2013 · In this paper, dynamic traffic load is considered to determine optimal location of base station (BS) using evolutionary optimization algorithms. The various parameters such as
Various site optimization models for selecting base station sites for cellular network planning have been studied by Tayal et al. (2020). The paper concludes that while planning the mobile tower network, evaluation of population, demographic data, and the proximity of roads and highways has to be done.
The commonly used optimization models for Bee Colony Optimization (ABC) and Particle Swarm Optimization T echnique (PSO). when used for base station placement optimization [ 1,2]. While implementing SA, [ 2]. Other important parameters which control the algorithm and the methods for choosing their values in an efficient way are addressed in [ 1].
... An optimization problem of Base Transceiver Station (BTS) placement can be tackled using a Geographic Information Systems (GIS) approach , , , . Another more popular approach is a meta-heuristic, which is much simpler and generally produces a more optimum solution.
T abu search is capable of base station site planning. In a comparison of local search cost value on multiple runs. It maximizes the coverage with least number of base stations. munication is presented in [ 6]. Here the coverage of cellular towers is set constrained in order to satisfy traffic demands.
Pattern the furthest Mobile Station MS. By doing this, number of necessary BTS required to cover a particular area is determined. FCM is used to distribute these BTS among the population. Optimization method then determines whether the number of allocated BTS can minimize the distance connecting BTS and farthest MS or not. Optimization
The purpose of clustering deployment area of BTS tower. Results of clustering were used as input parameters (chromosomes of the initial population) to produce the best fitness of GA. Pattern the furthest Mobile Station MS.
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