Hojatian, Hamed and Omidi, Mohammad Javad and Saeedi-Sourck, Hamid and Farhang, Arman (2017) Joint CFO and channel estimation in OFDM-based massive MIMO systems. In: 2016 Eighth InternationalSymposium on Telecommunications (IST). IEEE, pp. 343-348. ISBN 978-1-5090-3435-2

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Abstract

Estimation of carrier frequency offset (CFO) is a challenging task in practical systems specifically in the uplink of multiuser systems where multiple CFOs are present in the received signal. Massive MIMO as a multiuser technique has recently attracted a great deal of attention among researchers. However, to the best of our knowledge, there is no study looking into the joint estimation of CFOs and wireless channel in orthogonal frequency division multiplexing (OFDM) based massive MIMO systems. Therefore, in this paper, we propose joint estimation of multiple CFOs and the users' channel responses based on the maximum likelihood (ML) criteria in such systems. We propose to use the zadoff-chu (ZC) training sequences to reduce the implementation complexity. Additionally, utilization of ZC sequences for training simplifies the multidimensional grid search problem of estimating multiple CFOs and converts it into a set of line search problems, i.e., one line search problem per user. Also this sequence has a low peak to average ratio (PAPR). Finally, we show the efficacy of our proposed algorithm through numerical simulations.

Item Type:	Book Section
Additional Information:	This paper was presented at 8th International Symposium on Telecommunications (IST), 27-28 Sep 2016, Tehran, Iran.
Keywords:	carrier frequency offset (CFO); Massive MIMO; orthogonal frequency division multiplexing (OFDM); zadoff-chu (ZC) training sequences;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	11907
Identification Number:	https://doi.org/10.1109/ISTEL.2016.7881837
Depositing User:	Arman Farhang
Date Deposited:	28 Nov 2019 15:41
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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