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Optimization of Antenna Placement in 3G Networks Using Genetic Algorithms

机译:使用遗传算法优化3G网络的天线放置

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Third generation (3G) cellular networks are being implemented in many countries at high rate. Due to the fact that manual cell planning is a time consuming process and prone to a degree of error and inefficiency, there is a need for automated approaches to optimise coverage, capacity and quality of cellular networks in a fraction of the time. This paper studies the application of genetic algorithms to solve the Antenna Placement Problem (APP) in Universal Mobile Telecommunication System (UMTS) networks. The parameters of the genetic algorithm are tuned so that the algorithm converges optimally. The main task of the algorithm is to find the best set of base station locations so as to maximise coverage and quality of service measured as the signal-to-interference and noise ratio (SINR), as well as minimise the network cost by using fewer base stations. Assuming that a flat area is considered, the performance of the proposed algorithm was evaluated with 98% of the users in the network being covered with a good quality signal.
机译:第三代(3G)蜂窝网络正在许多国家在许多国家实施。由于手动小区规划是一种耗时的过程并且容易出现误差和低效率,需要自动化方法,以优化蜂窝网络的一小部分时间的覆盖,容量和质量。本文研究了遗传算法在通用移动电信系统(UMTS)网络中解决天线放置问题(APP)的应用。调谐遗传算法的参数,使得算法在最佳地收敛。该算法的主要任务是找到最佳的基站位置集,以便最大化作为信号到干扰和噪声比(SINR)测量的服务的覆盖率和质量,以及使用更少的网络成本最小化基站。假设考虑了平坦区域,所提出的算法的性能被评估为98%的网络中的用户被覆盖有良好的质量信号。

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