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Multi-rate power control of CDMA cellular system using genetic algorithm

机译:基于遗传算法的CDMA蜂窝系统多速率功率控制

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For a given channel allocation, the capacity and quality of communications of cellular radio systems using CDMA can be increased by using transmitter power control scheme to combat the near-far problem. In this work, we present an approach to the modeling and controlling methodology to enhance performance of cellular networks using genetic algorithm. We modeled and solved problem by combining the power control with transmission rate adjustment and calldrop, which is appropriate for the capacity optimization of the next generation CDMA capacity. The formulated problem has the nature of NP hard problem, which is known as difficult to solve by using conventional optimization methods. Genetic algorithm approximately mimics natural evolution. It performs a multidirectional search by maintaining a population of potential solutions and by combining elements of directed and stochastic search. Here, we propose to apply genetic algorithm to solve the formulated problem utilizing the problem specific knowledge of the system. The simulation results illustrate the effectiveness and validity of our approach.
机译:对于给定的信道分配,可以通过使用发射器功率控制方案来打击近远的问题,增加使用CDMA使用CDMA的蜂窝无线电系统的通信的能力和质量。在这项工作中,我们介绍了建模和控制方法的方法,以提高遗传算法的蜂窝网络性能。我们通过将电源控制与传输速率调整和CALLDROP组合来建模和解决问题,这适用于下一代CDMA容量的容量优化。配制的问题具有NP难题的性质,这被称为难以使用常规优化方法解决。遗传算法大致模仿自然演化。它通过维护潜在的解决方案群体来执行多向搜索,并通过组合定向和随机搜索的元素来执行。在这里,我们建议应用遗传算法来利用系统的具体知识来解决配方的问题。仿真结果说明了我们方法的有效性和有效性。

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