一种基于高阶统计量的组合盲均衡新算法

A New Hybrid Algorithm for Blind Equalization Based on Higher Order Statistics

基于高阶统计量的逆滤波器准则(IFC)和超指数迭代算法(SEA)已经被广泛地应用于解决盲均衡问题。Chi,Feng和Chen通过对两种算法的性能分析提出在特定的条件下SEA和IFC算法的得到的均衡器是等价的。基于这种等价性,文献中提出通过对这两种算法进行组合来提高算法性能的改进方案。采用这种改进的改进方案,将一种最新的改进的SEA算法[1]和IFC算法进行组合,提出一种收敛性又好,收敛速度又快的组合算法。

Shalvi and Weinstein propose two computationally efficient algorithms-the super-exponential algorithm（SEA）and IFC- based algorithm. Chi, Feng and Chen analyze the performance of those algorithms and have provide that the results of those two algorithms are equivalent under the specifically conditions. The equivalence suggests that the optimum equalization can be obtained using a hybrid framework of the IFC-based algorithm and SEA. This paper proposes a new hybrid algorithm of a new improved SEA algorithm and IFC. This new hybrid algorithm exhibits fast convergence and does not suffer from the divergence problem of SEA.