判决引导和常数模融合盲均衡算法研究
A study of fusion blind equalization based on DD and CMA
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摘要: 结合判决引导(DD:Decision-Directed)算法和常数模算法(CMA:Constant Modulus Algorithm)的各自优点,研究了一种基于DD和CMA的融合盲均衡算法。DD算法收敛速度快,但要求初始接收信号眼图张开,CMA算法稳健,但是收敛速度慢,为此,对接收信号依DD算法和CMA算法获得瞬时误差后进行加权融合处理,以加权后获得的瞬时误差对均衡器权系数进行调节,实现均衡。计算机仿真证明了融合盲均衡算法有效提高收敛速度的同时具有良好的稳健性和均衡性能。Abstract: Combined the virtues of DD and CMA,a fusion blind equalization algorithm based on DD and CMA has been proposed.Convergence rate of DD algorithm is fast,but it requires eye pattern of received signal open at the beginning.Whereas CMA has steady performance,the convergence rate is slow. So weighting and fusing the transient errors of the received signal obtained by DD and CMA,and then using the weighted transient errors to update equalizer weight coefficient can be a better solution. Simulation results indicate that fusion blind equalization algorithm provides higher convergence rate and better performance.
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