Second-order statistics-based semi-blind techniques for channel estimation in millimeter-wave MIMO analog and hybrid beamforming
Second-order statistics-based semi-blind techniques for channel estimation in millimeter-wave MIMO analog and hybrid beamforming
Semi-blind (SB) channel estimation is conceived for millimeter wave (mmWave) analog-beamforming (AB) and hybrid-beamforming (HB)-based multiple-input multiple-output (MIMO) systems, which also exploits the data symbols for improving the estimation accuracy. A novel aspect of the proposed framework is that it directly estimates the analog beamformer/combiner weights without necessitating the estimation of the entire mmWave MIMO channel matrix. By involving powerful matrix perturbation theoretic techniques, a closed-form expression is derived for the mean-squared-error (MSE) of the mmWave-AB-SB algorithm. As a further novelty, our mmWave-HB-SB technique relies on the decomposition of the channel matrix as the product of a decorrelating and a unitary matrix. Subsequently, the former is estimated purely relying on the unknown data symbols, whereas the latter is estimated exclusively from the training vectors. A lower bound on the MSE of the proposed mmWave-HB-SB technique is derived using the constrained Cramér-Rao lower bound (CRLB) framework. Furthermore, the performance gain of our mmWave-HB-SB technique over the conventional purely training-based scheme is also quantified analytically. Our simulation results demonstrate the superiority of the techniques advocated over the existing solutions and also verify the accuracy of our analytical findings.
CRLB, MIMO, Millimeter wave, analog- and hybrid-beamforming, semi-blind channel estimation
6886-6901
Singh, Prem
b3155131-3d31-4d82-876c-33655420c7e5
Srivastava, Suraj
7b40cb6c-7bc6-402c-8751-24346d39002c
Jagannatham, Aditya K.
ea2f628b-0f2a-48a3-a293-122c809757aa
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
November 2020
Singh, Prem
b3155131-3d31-4d82-876c-33655420c7e5
Srivastava, Suraj
7b40cb6c-7bc6-402c-8751-24346d39002c
Jagannatham, Aditya K.
ea2f628b-0f2a-48a3-a293-122c809757aa
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Singh, Prem, Srivastava, Suraj, Jagannatham, Aditya K. and Hanzo, Lajos
(2020)
Second-order statistics-based semi-blind techniques for channel estimation in millimeter-wave MIMO analog and hybrid beamforming.
IEEE Transactions on Communications, 68 (11), , [9165794].
(doi:10.1109/TCOMM.2020.3016010).
Abstract
Semi-blind (SB) channel estimation is conceived for millimeter wave (mmWave) analog-beamforming (AB) and hybrid-beamforming (HB)-based multiple-input multiple-output (MIMO) systems, which also exploits the data symbols for improving the estimation accuracy. A novel aspect of the proposed framework is that it directly estimates the analog beamformer/combiner weights without necessitating the estimation of the entire mmWave MIMO channel matrix. By involving powerful matrix perturbation theoretic techniques, a closed-form expression is derived for the mean-squared-error (MSE) of the mmWave-AB-SB algorithm. As a further novelty, our mmWave-HB-SB technique relies on the decomposition of the channel matrix as the product of a decorrelating and a unitary matrix. Subsequently, the former is estimated purely relying on the unknown data symbols, whereas the latter is estimated exclusively from the training vectors. A lower bound on the MSE of the proposed mmWave-HB-SB technique is derived using the constrained Cramér-Rao lower bound (CRLB) framework. Furthermore, the performance gain of our mmWave-HB-SB technique over the conventional purely training-based scheme is also quantified analytically. Our simulation results demonstrate the superiority of the techniques advocated over the existing solutions and also verify the accuracy of our analytical findings.
Text
mmWave_SB
- Accepted Manuscript
More information
Accepted/In Press date: 5 August 2020
Published date: November 2020
Additional Information:
Funding Information:
Manuscript received January 7, 2020; revised May 5, 2020 and June 25, 2020; accepted August 4, 2020. Date of publication August 12, 2020; date of current version November 18, 2020. This research has been supported by the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India, Space Technology Cell, IIT Kanpur, IIMA IDEA Telecom Centre of Excellence, Qualcomm Innovation Fellowship and Arun Kumar Chair Professorship. L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/N004558/1, EP/P034284/1, EP/P034284/1, EP/P003990/1 (COALESCE), of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom. The associate editor coordinating the review of this article and approving it for publication was L. Song. (Corresponding author: Lajos Hanzo.) Prem Singh, Suraj Srivastava, and Aditya K. Jagannatham are with the Department of Electrical Engineering, IIT Kanpur, Kanpur 208016, India (e-mail: psrawat@iitk.ac.in; ssrivast@iitk.ac.in; adityaj@iitk.ac.in).
Publisher Copyright:
© 1972-2012 IEEE.
Keywords:
CRLB, MIMO, Millimeter wave, analog- and hybrid-beamforming, semi-blind channel estimation
Identifiers
Local EPrints ID: 443240
URI: http://eprints.soton.ac.uk/id/eprint/443240
ISSN: 0090-6778
PURE UUID: 9613e58b-e74b-480a-b899-80b547557a0f
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Date deposited: 18 Aug 2020 16:31
Last modified: 18 Mar 2024 02:36
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Contributors
Author:
Prem Singh
Author:
Suraj Srivastava
Author:
Aditya K. Jagannatham
Author:
Lajos Hanzo
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