Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86875
Title: Training Sequence Design for Efficient Channel Estimation in MIMO-FBMC Systems
Authors: Hu, Su
Liu, Zilong
Guan, Yong Liang
Jin, Chuanxue
Huang, Yixuan
Wu, Jen-Ming
Keywords: Multiple-input Multiple-output (MIMO)
Filterbank Multicarrier (FBMC)
Issue Date: 2017
Source: Hu, S., Liu, Z., Guan, Y. L., Jin, C., Huang, Y., & Wu, J.-M. (2017). Training Sequence Design for Efficient Channel Estimation in MIMO-FBMC Systems. IEEE Access, 5, 4747-4758.
Series/Report no.: IEEE Access
Abstract: 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.
URI: https://hdl.handle.net/10356/86875
http://hdl.handle.net/10220/44221
DOI: http://dx.doi.org/10.1109/ACCESS.2017.2688399
Rights: © 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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