【摘 要】
：
提出了一种结合小波变换的结构风险最小化空时均衡器(WSRM-STE),WSRM-STE采用小波变换技术可提高收敛速度.该方法在多维小波基上张成的空间中,综合利用通信信号中的学习信息
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提出了一种结合小波变换的结构风险最小化空时均衡器(WSRM-STE),WSRM-STE采用小波变换技术可提高收敛速度.该方法在多维小波基上张成的空间中,综合利用通信信号中的学习信息和滤波器自身的结构信息,可自适应调整最佳小波系数和容量控制作用.通过仿真实验,并与结构风险最小化空时均衡器(SRM-STE)和结合小波变换的支持向量机空时均衡器(WSVM-STE)比较,得出结论:WSRM-STE收敛速度快,跟踪性能好,在复杂环境下的无线移动通信中具有一定的应用前景.
(WSRM-STE), which combines wavelet transform and WSRM-STE, can improve the convergence speed by using wavelet transform technology.This method combines the advantages of communication Signal learning information and the structure of the filter itself, which can adaptively adjust the best wavelet coefficients and capacity control functions.Through the simulation experiments, and with the structural risk minimization SRM-STE and wavelet transform Compared with WSVM-STE, it is concluded that WSRM-STE has the advantages of fast convergence and good tracking performance, and has certain application prospect in wireless mobile communication under complex environment.
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