Enhancement Channel Estimation Using Outer-Product Decomposition Algorithm Based on Frequency Transformation
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RESEARCH ARTICLE
Enhancement Channel Estimation Using Outer-Product Decomposition Algorithm Based on Frequency Transformation Xiukun Li 1,2,3 & Ji Wang 1,2,3 & Dexin Zhao 4 Received: 13 January 2019 / Accepted: 8 July 2019 # Harbin Engineering University and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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
1 Introduction In wireless communication systems, unknown channels will introduce an intersymbol interference (ISI) to reduce communication quality. A common method for eliminating ISI is to add a known sequence as a training sequence in the transmitted signal. Then, the training sequence is used to equalize the ISI (Ghofrani et al. 2018; Qiao et al. 2017). In the field of system identification, such as seismic inversion, no training sequence exists in the measured signal. Also, a direct measurement of a transmission Article Highlights • The calculation of OPDA algorithm is accelerated significantly. • The estimation error of the OPDA is reduced. * Dexin Zhao [email protected] 1
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
2
Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University), Ministry of Industry and Information Technology, Harbin 150001, China
3
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
4
Advanced Interdisciplinary Technology Research Center, National Innovation Institute of Defense Technology, Beijing 100010, China
channel is infeasible. In these scenarios, techniques for directly identifying a channel or system from observations need to be developed. Blind channel identification identifies channels that rely solely on a received channel output signal and certain a priori statistical knowledge (e.g., whiteness) of the source. Thus, blind channel identification can be used in scenarios where the source signal or system impulse response function cannot be directly obtained. In a radar communication system, a blind identification method can estimate a channel in rea
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