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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.
Based on the wavelet analysis and pattern recognition theory, a handover decision algorithm in cognitive network is proposed, which is based on multiresolution analysis of mobile station signals obtained by base station, and obtains the basic signal strength and noise signal strength of mobile station signals. On this basis, The artificial neural fuzzy inference system performs pattern recognition on the obtained result, and makes the switching decision by fuzzy inference. The simulation results show that the algorithm can still get good decision results under the condition of decreasing signal-to- Network through the perception of environmental changes to make adaptive adjustment function, and has good reliability.