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Evolutionary computation and power control for radio resource management in CDMA cellular radio networks

机译:CDMA蜂窝无线网络中用于无线资源管理的进化计算和功率控制

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This paper has proposed the distributed power control (PC) algorithms that employ two evolutionary computation (EC) techniques in order to solve linear systems of equations for power update in CDMA cellular radio systems. The proposed algorithms are developed by applying evolutionary computation algorithms with the phenotypic and genotypic views to the CDMA power control problem. The major gain from the applied evolutionary computation algorithms is more rapid optimization on linear systems of equations compared with the simple genetic algorithm (GA). Employing the distributed constrained power control (DCPC) as a basic reference algorithm, we have designed and implemented computational experiments on the DS-CDMA system. The results indicate that the proposed algorithms significantly enhance the optimization and calculation speed of power control. The proposed algorithms are also compared with the bang-bang type algorithm used in the IS-95 and the W-CDMA systems. The results show that the proposed the EC-DCPC phenotypic and GAPC genotypic algorithms also have a high potential advantage for increasing the CDMA cellular radio network capacity and decreasing the mobile terminal power consumption.
机译:本文提出了采用两种进化计算(EC)技术的分布式功率控制(PC)算法,以解决CDMA蜂窝无线电系统中用于功率更新的方程式的线性系统。提出的算法是通过将具有表型和基因型视图的进化计算算法应用于CDMA功率控制问题而开发的。与简单遗传算法(GA)相比,应用的进化计算算法的主要收益是在线性方程组上实现了更快的优化。利用分布式约束功率控制(DCPC)作为基本参考算法,我们在DS-CDMA系统上设计并实现了计算实验。结果表明,所提出的算法大大提高了功率控制的优化和计算速度。还将所提出的算法与IS-95和W-CDMA系统中使用的bang-bang类型算法进行比较。结果表明,提出的EC-DCPC表型和GAPC基因型算法在增加CDMA蜂窝无线网络容量和降低移动终端功耗方面也具有很高的潜在优势。

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