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Real-Valued Orthogonal Sequences for Ultra-low Overhead Channel Estimation in MIMO-FBMC Systems

  • Su Hu
  • Jing Zhang
  • Wanbin Tang
  • Zilong Liu
  • Pei Xiao
  • Yuan Gao
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 251)

Abstract

Multiple-input multiple-output filterbank multicarrier communication (MIMO-FBMC) is a promising technique to achieve very tight spectrum confinement (thus, higher spectral efficiency) as well as strong robustness against dispersive channels. In this paper, we present a novel training design for MIMO-FBMC system which enables efficient estimate of frequency-selective channels (associated to multiple transmit antennas) with only one non-zero FBMC symbol. Our key idea is to design real-valued orthogonal training sequences (in the frequency domain) which displaying zero-correlation zone properties in the time-domain. Compared to our earlier proposed training scheme requiring at least two non-zero FBMC symbols (separated by several zero guard symbols), the proposed scheme features ultra-low training overhead yet achieves channel estimation performance comparable to our earlier proposed complex training sequence decomposition (CTSD). Our simulations validate that the proposed method is an efficient channel estimation approach for practical preamble-based MIMO-FBMC systems.

Keywords

Filterbank multicarrier MIMO-FBMC Channel estimation Preamble Real-valued orthogonality Zero-correlation zone sequences 

Notes

Acknowledgement

The work of S. Hu is jointly supported by the MOST Program of International S&T Cooperation (Grant No. 2016YFE0123200), Science and Technology on Electronic Information Control Laboratory (Grant No. 6142105040103) and Fundamental Research Funds for the Central Universities (Grant No. ZYGX2015J012). The work of Z. Liu and S. Hu was supported in part by National Natural Science Foundation of China (Grant No. 61750110527, Grant No. 61471100/61701503), Research Fund for International Young Scientists. The work of Z. Liu and P. Xiao was also supported in part by European Commission under the 5GPPP H2020 Clear5G Project (Grant No. 761745). The support of members at 5GIC of the University of Surrey (www.surrey.ac.uk/5gic) during this work is also acknowledged.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.National Key Laboratory on CommunicationsUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.Institute of Communication Systems, 5G Innovation CentreUniversity of SurreyGuildfordUK
  3. 3.Department of Electronic EngineeringTsinghua UniversityBeijingChina

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