Hybrid precoder and combiner designs for decentralized parameter estimation in mmWave MIMO wireless sensor networks
Hybrid precoder and combiner designs for decentralized parameter estimation in mmWave MIMO wireless sensor networks
Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input-multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre- and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimation of a parameter vector. The proposed techniques exploit the limited scattering nature of the mmWave MIMO channel for formulating the hybrid transceiver design framework as a multiple measurement vectors (MMVs)-based sparse signal recovery problem. This is then solved using the iterative appealingly low-complexity simultaneous orthogonal matching pursuit (SOMP). Tailor-made designs are presented for WSNs operating under both total and per-sensor power constraints, while considering ideal noiseless as well as realistic noisy sensors. Furthermore, both the Bayesian Cramer-Rao lower bound and the centralized MMSE bound are derived for benchmarking the proposed decentralized estimation schemes. Our simulation results demonstrate the efficiency of the designs advocated and verify the analytical findings.
Estimation, Hybrid transceiver design, MIMO communication, Millimeter wave communication, Parameter estimation, Radio frequency, Transceivers, Wireless sensor networks, decentralized parameter estimation, majorization theory, mmWave MIMO, wireless sensor networks, wireless sensor networks (WSNs), hybrid transceiver design, millimeter wave (mmWave) multiple-input-multiple-output (MIMO), Decentralized parameter estimation
1629-1643
Maity, Priyanka
012f364b-affa-4e39-a488-198035a3fbcc
Srivastava, Suraj
7b40cb6c-7bc6-402c-8751-24346d39002c
Rajput, Kunwar Pritiraj
6501cc13-cf78-45de-a8c8-621c128354f1
Venkategowda, Naveen K.D.
479c3eaa-7676-4573-9549-e188379df4bc
Jagannatham, Aditya K.
b5974907-7880-4637-8f3a-c1388ffbacc4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
1 January 2024
Maity, Priyanka
012f364b-affa-4e39-a488-198035a3fbcc
Srivastava, Suraj
7b40cb6c-7bc6-402c-8751-24346d39002c
Rajput, Kunwar Pritiraj
6501cc13-cf78-45de-a8c8-621c128354f1
Venkategowda, Naveen K.D.
479c3eaa-7676-4573-9549-e188379df4bc
Jagannatham, Aditya K.
b5974907-7880-4637-8f3a-c1388ffbacc4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Maity, Priyanka, Srivastava, Suraj, Rajput, Kunwar Pritiraj, Venkategowda, Naveen K.D., Jagannatham, Aditya K. and Hanzo, Lajos
(2024)
Hybrid precoder and combiner designs for decentralized parameter estimation in mmWave MIMO wireless sensor networks.
IEEE Internet of Things Journal, 11 (1), .
(doi:10.1109/JIOT.2023.3290108).
Abstract
Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input-multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre- and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimation of a parameter vector. The proposed techniques exploit the limited scattering nature of the mmWave MIMO channel for formulating the hybrid transceiver design framework as a multiple measurement vectors (MMVs)-based sparse signal recovery problem. This is then solved using the iterative appealingly low-complexity simultaneous orthogonal matching pursuit (SOMP). Tailor-made designs are presented for WSNs operating under both total and per-sensor power constraints, while considering ideal noiseless as well as realistic noisy sensors. Furthermore, both the Bayesian Cramer-Rao lower bound and the centralized MMSE bound are derived for benchmarking the proposed decentralized estimation schemes. Our simulation results demonstrate the efficiency of the designs advocated and verify the analytical findings.
Text
mmWave_WSN_manuscript
- Accepted Manuscript
More information
Accepted/In Press date: 25 June 2023
e-pub ahead of print date: 27 June 2023
Published date: 1 January 2024
Additional Information:
Funding Information:
The work of Aditya K. Jagannatham was supported in part by the Qualcomm Innovation Fellowship, and in part by the Arun Kumar Chair Professorship. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council under Project EP/W016605/1 and Project EP/X01228X/1, and in part by the European Research Councilss Advanced Fellow Grant QuantCom under Grant 789028.
Publisher Copyright:
© 2014 IEEE.
Keywords:
Estimation, Hybrid transceiver design, MIMO communication, Millimeter wave communication, Parameter estimation, Radio frequency, Transceivers, Wireless sensor networks, decentralized parameter estimation, majorization theory, mmWave MIMO, wireless sensor networks, wireless sensor networks (WSNs), hybrid transceiver design, millimeter wave (mmWave) multiple-input-multiple-output (MIMO), Decentralized parameter estimation
Identifiers
Local EPrints ID: 478663
URI: http://eprints.soton.ac.uk/id/eprint/478663
ISSN: 2327-4662
PURE UUID: 4b51de15-f34c-4345-97d3-a801b319b26e
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Date deposited: 06 Jul 2023 16:50
Last modified: 12 Dec 2024 02:32
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Contributors
Author:
Priyanka Maity
Author:
Suraj Srivastava
Author:
Kunwar Pritiraj Rajput
Author:
Naveen K.D. Venkategowda
Author:
Aditya K. Jagannatham
Author:
Lajos Hanzo
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