Enhancement Channel Estimation Using Outer-Product Decomposition Algorithm Based on Frequency Transformation

Abstract

The outer-product decomposition algorithm (OPDA) performs well at blindly identifying system function. However, the direct use of the OPDA in systems using bandpass source will lead to errors. This study proposes an approach to enhance the channel estimation quality of a bandpass source that uses OPDA. This approach performs frequency domain transformation on the received signal and obtains the optimal transformation parameter by minimizing the p-norm of an error matrix. Moreover, the proposed approach extends the application of OPDA from a white source to a bandpass white source or chirp signal. Theoretical formulas and simulation results show that the proposed approach not only reduces the estimation error but also accelerates the algorithm in a bandpass system, thus being highly feasible in practical blind system identification applications.

Keywords

Blind identification / Outer-product decomposition algorithm / Bandpass white signal / Chirp signal / Second-order statistics

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