Linear Prediction Methods for Direct Blind MMSE Equalization
S. F. Hsieh
|關鍵字:||分數取樣等化器;陣列訊號處理;統計訊號處理;盲式等化器;Fractionally spaced equalization;array signal processing;statistical signal processing;blind equalization|
The channel equalization using the high-order statistics methods has a slow convergence rate. In recent years, the second-order statistics (SOS) methods have become a popular research. One of the SOS methods, such as the Ding algorithm proposed by Ding in 2000 is an advanced type of outer-product decomposition algorithm (OPDA), has been shown to have better performance than many existing algorithms. But Ding algorithm needs the pseudo-inverse of the correlation matrix, thus the computation is not simple and could cause numerical problems. It is also not suit for tracking time-varying channels. By the use of linear prediction (LP) method proposed by Fan, we deduce a new algorithm based on Ding algorithm. We name the new algorithm as linear prediction based outer-product decomposition algorithm (LP-OPDA). LP-OPDA combines both the advantages of LP and Ding algorithm and has its new advantages. LP-OPDA does not need the pseudo-inverse operation, thus have superior performance over Ding algorithm. LP-OPDA is available for tracking time-varying channels and also computationally efficient. From the simulation results, we can see LP-OPDA has superior performance over Ding algorithm and many other existing algorithms in many ways.