认知网络中基于小波分析的切换判决

Handover Decision Method Based on Wavelet for Cognitive Network

基于小波分析和模式识别理论,提出一种认知网络中的切换判决算法.对基站得到的移动台信号进行多分辨分析,得到移动台信号的基本信号强度和噪音信号强度;在此基础上通过人工神经模糊推理系统对得到的结果进行模式识别;通过模糊推理做出切换判决.仿真结果表明,该算法在信道信噪比不断降低的情况下依然可得到较好的判决结果,实现了认知网络通过感知环境变化而做出自适应调整的功能,并具有较好的可靠性.

A handover decision method for cognitive networks is investigated in the context of wavelet and pattern recognition. It follows two steps： firstly, making multi-resolution analysis to the signal received in base station to get the basic signal and the noise signal. Secondly, making the pattern recognition and handover decision by artificial neural fuzzy inference system. Simulation shows that it greatly improve the system ＇ s performance when the channel is in low signal-to-noise ratio. Besides, it makes the system eognitive and adaptive to the changes of the environment.