A limited feedback scheme for massive MIMO systems based on principal component analysis

Zhang, Tiankui, Ge, Anmeng, Beaulieu, Norman C, Hu, Zhirui and Loo, Jonathan ORCID: https://orcid.org/0000-0002-2197-8126 (2016) A limited feedback scheme for massive MIMO systems based on principal component analysis. EURASIP Journal on Advances in Signal Processing (64). ISSN 1687-6172

[thumbnail of Zhang-etal-2016-A-limited-feedback-scheme-for-massive-MIMO-systems.pdf]
Zhang-etal-2016-A-limited-feedback-scheme-for-massive-MIMO-systems.pdf - Published Version
Available under License Creative Commons Attribution.

Download (926kB) | Preview


Massive multiple-input multiple-output (MIMO) is becoming a key technology for future 5G cellular networks. Channel feedback for massive MIMO is challenging due to the substantially increased dimension of the channel matrix. This motivates us to explore a novel feedback reduction scheme based on the theory of principal component analysis (PCA). The proposed PCA-based feedback scheme exploits the spatial correlation characteristics of the massive MIMO channel models, since the transmit antennas are deployed compactly at the base station (BS). In the proposed scheme, the mobile station (MS) generates a compression matrix by operating PCA on the channel state information (CSI) over a long-term period, and utilizes the compression matrix to compress the spatially correlated high-dimensional CSI into a low-dimensional representation. Then, the compressed low-dimensional CSI is fed back to the BS in a short-term period. In order to recover the high-dimensional CSI at the BS, the compression matrix is refreshed and fed back from MS to BS at every long-term period. The information distortion of the proposed scheme is also investigated and a closed-form expression for an upper bound to the normalized information distortion is derived. The overhead analysis and numerical results show that the proposed scheme can offer a worthwhile tradeoff between the system capacity performance and implementation complexity including the feedback overhead and codebook search complexity

Item Type: Article
Identifier: 10.1186/s13634-016-0364-9
Additional Information: © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Massive MIMO, Limited feedback, Principal component analysis, Information distortion analysis
Subjects: Computing
Depositing User: Jonathan Loo
Date Deposited: 22 Jun 2017 09:13
Last Modified: 06 Feb 2024 15:53
URI: https://repository.uwl.ac.uk/id/eprint/3506


Downloads per month over past year

Actions (login required)

View Item View Item