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

• Main Authors: Hu, Su, Liu, Zilong, Guan, Yong Liang, Jin, Chuanxue, Huang, Yixuan, Wu, Jen-Ming
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2017
• Subjects: Multiple-input Multiple-output (MIMO); Filterbank Multicarrier (FBMC)
• Online Access: https://hdl.handle.net/10356/86875; http://hdl.handle.net/10220/44221
• Institution: Nanyang Technological University

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.