CDMA蜂窝系统中基于模糊神经网络的反向链路功率控制

CDMA是一个干扰受限系统,反向链路功率控制对于克服“远近效应”和增加系统容量是非常重要的.本文提出了一种基于模糊神经网络(FNN)的自适应闭环功率控制算法,该算法动态地调整功率控制增量,使基站接收到的每个用户的发射功率相等.仿真结果表明,由于模糊神经网络能够较好地识别反向链路的时变特性,FNN功率控制算法比传统的固定步长功率控制方法取得了更好的控制性能和更大的系统容量.而且,FNN能够通过神经网络训练自动地调整隶属度函数和模糊规则,从而适合于实现在线系统识别和自适应控制.

Power Control on the Reverse Link for a CDMA Cellular System Using a Fuzzy Neural Network

The CDMA mobile communication is an interference-limited system,the power control on the reverse link is important to combat the near-far problem and increase the system capacity.In this paper,an adaptive close-loop power control algorithm based on Fuzzy Neural Network (FNN) is proposed to adjust the power control increment dynamically and keep the received signal power from each user constant at the base station.Simulation results show that compared to the conventional fixed-step power controller,FNN power control algorithm achieves better control performance and higher traffic capacity due to the inherent ability of FNN to identify the fast time-varying characteristic of inverse channel.Furthermore,the FNN power control algorithm can realize the automatic tuning of fuzzy rules and membership functions by neural network training and is suitable for on-line identification and adaptive control.