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Training Sequence Design for Efficient Channel Estimation in MIMO-FBMC Systems

Hu, Su and Liu, Zilong and Guan, Yong Liang and Jin, Chuanxue and Huang, Yixuan and Wu, Jen-Ming (2017) 'Training Sequence Design for Efficient Channel Estimation in MIMO-FBMC Systems.' IEEE Access, 5. pp. 4747-4758. ISSN 2169-3536

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This paper is focused on training sequence design for efficient channel estimation in multiple-input multiple-output filterbank multicarrier (MIMO-FBMC) communications using offset quadrature amplitude modulation (OQAM). MIMO-FBMC is a promising technique to achieve high spectrum efficiency as well as strong robustness against dispersive channels due to its feature of time-frequency localization. A salient drawback of FBMC/OQAM signals is that only real-field orthogonality can be kept, leading to the intrinsic imaginary interference being a barrier for high-performance channel estimations. Also, conventional channel estimations in the MIMO-FBMC systems mostly suffer from high training overhead especially for large number of transmit antennas. Motivated by these problems, in this paper, we propose a new class of training sequences, which are formed by concatenation of two identical zero-correlation zone sequences whose auto-correlation and cross correlation are zero within a time-shift window around the in-phase position. Since only real-valued symbols can be transmitted in MIMO-FBMC systems, we propose “complex training sequence decomposition (CTSD)” to facilitate the reconstruction of the complex-field orthogonality of MIMO-FBMC signals. Our simulations validate that the proposed CTSD is an efficient channel estimation approach for practical preamble-based MIMO-FBMC systems.

Item Type: Article
Uncontrolled Keywords: Filterbank multicarrier (FBMC), multiple-input multiple-output (MIMO), channelestimation, preamble, zero-correlation zone (ZCZ) sequences
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Jul 2021 15:11
Last Modified: 23 Sep 2022 19:37

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