Nan, Y, Zhang, LX and Sun, X (2016) An Efficient Downlink Channel Estimation Approach for TDD Massive MIMO Systems. In: Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd. 23rd Vehicular Technology Conference (VTC), 15-18 May 2016 IEEE ISBN 978-1-5090-1698-3
Abstract
In this paper, channel estimation problem for downlink massive multi-input multi-output (MIMO) system is considered. Motivated by the observation that channels in massive MIMO systems may exhibit sparsity and the path delays vary slowly in one uplink-downlink process even though the path gains may be quite different, we propose a novel channel estimation method based on the compressive sensing. Unlike the conventional methods which do not make use of any a priori information, we estimate the probabilities that the paths are nonzero in the downlink channel by exploiting the channel impulse response (CIR) estimated from the uplink channel estimation. Based on these probabilities, we propose the Weighted Structured Subspace Pursuit (WSSP) algorithm to efficiently reconstruct the massive MIMO channel. Simulation results show that the WSSP could reduce the pilots number significantly while maintain decent channel estimation performance.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Keywords: | Channel estimation, Downlink, Delays, MIMO, Uplink, Antennas, Compressed sensing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Oct 2016 15:06 |
Last Modified: | 24 Oct 2016 15:57 |
Published Version: | http://dx.doi.org/10.1109/VTCSpring.2016.7504124 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/VTCSpring.2016.7504124 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:98319 |