一种基于遗传算法的功率控制方法

A New and Better Power Control Approach in Cellular Mobile Communication System

利用遗传算法强有力的全局搜索和优化能力,提出了一种基于遗传算法的功率控制方法,该方法有效地提高了CDMA蜂窝移动通信系统中功率控制的收敛速度。仿真结果表明:与现有算法相比,该算法能够迅速寻找到功率控制问题的最优解,有效地提高功率控制的收敛速度,降低了计算的复杂度。

We aim to present a new method that is better than the existing methods such as DCPC （Distributed Constrained Power Control） and CSOPC （Constrained Second Order Power Control）. Our better power control approach is based on genetic algorithm （GA） which has powerful capability of stochastic search and optimization. The new approach effectively and greatly enhances the convergence rate of power control in the cellular mobile communication systems. We call our method GAPC （Genetic Algorithm Power Control）. Simulation results for DCPC, CSOPC, and GAPC for CDMA cellular mobile communication system are compared on a graph which has normalized Euclidean distance （NED） as ordinate and number of iterations as abscissa. At the end of 10 iterations, NED values for DCPC, CSOPC, and GAPC are respectively of the order of 10^-2, 10^-3, and 10^-5. At the end of 20 iterations, NED values for DCPC, CSOPC, GAPC are respectively of the order of 10^-4, 10^-8, and 10^-10. The smaller the NED, the closer is the transmitting power vector to its optimum. The above-mentioned numerical results show that NED for CSOPC is very much smaller than that of DCPC and the NED for GAPC is very much still smaller than that for CSOPC. The simulated results indicate that, compared with the existing algorithms, the new algorithm can function more effectively in tracing and finding the best solutions to the power control problem, and thus significantly speeds up the convergence and calculation of the power control.