Nan, Y, Sun, X and Zhang, LX (2016) Joint Channel Estimation Algorithm via Weighted Homotopy for Massive MIMO OFDM System. Digital Signal Processing, 50. pp. 34-42. ISSN 1051-2004
Abstract
Massive (or large-scale) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system is widely acknowledged as a key technology for future communication. One main challenge to implement this system in practice is the high dimensional channel estimation, where the large number of channel matrix entries requires prohibitively high computational complexity. To solve this problem efficiently, a channel estimation approach using few number of pilots is necessary. In this paper, we propose a weighted Homotopy based channel estimation approach which utilizes the sparse nature in MIMO channels to achieve a decent channel estimation performance with much less pilot overhead. Moreover, inspired by the fact that MIMO channels are observed to have approximately common support in a neighborhood, an information exchange strategy based on the proposed approach is developed to further improve the estimation accuracy and reduce the required number of pilots through joint channel estimation. Compared with the traditional sparse channel estimation methods, the proposed approach can achieve more than 2dB gain in terms of mean square error (MSE) with the same number of pilots, or achieve the same performance with much less pilots.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2015, Elsevier. This is an author produced version of a paper published in Digital Signal Processing. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Massive MIMO; Channel Estimation; Weighted Homotopy |
Dates: |
|
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: | 21 Dec 2015 13:26 |
Last Modified: | 21 Dec 2016 08:19 |
Published Version: | http://dx.doi.org/10.1016/j.dsp.2015.11.010 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.dsp.2015.11.010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:92693 |