TY - JOUR
T1 - Robust Linear Transceiver Designs for Vector Parameter Estimation in MIMO Wireless Sensor Networks under CSI Uncertainty
AU - Rajput, Kunwar Pritiraj
AU - Verma, Yogesh
AU - Venkategowda, Naveen K.D.
AU - Jagannatham, Aditya K.
AU - Varshney, Pramod K.
N1 - Funding Information:
Manuscript received February 11, 2021; accepted May 25, 2021. Date of publication June 1, 2021; date of current version August 13, 2021. This work was supported in part by the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India, in part by the Space Technology Cell, IIT Kanpur, in part by the IIMA IDEA Telecom Centre of Excellence, in part by the Qualcomm Innovation Fellowship, and in part by the Arun Kumar Chair Professorship. The review of this article was coordinated by Prof. Jia-Chin Lin. (Corresponding author: Kunwar Pritiraj Rajput.) Kunwar Pritiraj Rajput and Aditya K. Jagannatham are with the Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016, India (e-mail: pratiraj@iitk.ac.in; adityaj@iitk.ac.in).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2021/8
Y1 - 2021/8
N2 - This work conceives the robust linear transceivers for the estimation of an unknown vector parameter in a coherent multiple access channel (MAC)-based multiple-input multiple-output (MIMO) multi-sensor network under imperfect channel state information (CSI) at the fusion center (FC). Both the popular stochastic (S-) and norm ball CSI uncertainty (N-CSIU) models are considered for robust design. The proposed techniques are based on two design criterion, the first being, minimizing the mean squared error (MSE) of the estimate at the FC subject to total network power or individual sensor power constraints. Second, minimizing the total power consumption in the network while meeting a predefined level of MSE performance. Furthermore, the framework for precoder and combiner optimization is based on results from majorization theory, which leads to non-iterative closed-form solutions for the transceivers. While the most general scenario with correlated parameters and arbitrary observation SNR is considered to begin with, scenarios with uncorrelated parameters and high observation SNR are also considered as special cases, which makes the analysis comprehensive. Simulation results are presented to demonstrate the efficacy of the proposed schemes.
AB - This work conceives the robust linear transceivers for the estimation of an unknown vector parameter in a coherent multiple access channel (MAC)-based multiple-input multiple-output (MIMO) multi-sensor network under imperfect channel state information (CSI) at the fusion center (FC). Both the popular stochastic (S-) and norm ball CSI uncertainty (N-CSIU) models are considered for robust design. The proposed techniques are based on two design criterion, the first being, minimizing the mean squared error (MSE) of the estimate at the FC subject to total network power or individual sensor power constraints. Second, minimizing the total power consumption in the network while meeting a predefined level of MSE performance. Furthermore, the framework for precoder and combiner optimization is based on results from majorization theory, which leads to non-iterative closed-form solutions for the transceivers. While the most general scenario with correlated parameters and arbitrary observation SNR is considered to begin with, scenarios with uncorrelated parameters and high observation SNR are also considered as special cases, which makes the analysis comprehensive. Simulation results are presented to demonstrate the efficacy of the proposed schemes.
KW - Wireless sensor networks
KW - decentralized estimation
KW - parameter estimation
KW - robust transceiver design
KW - stochastic robust design
KW - worst-case design
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U2 - 10.1109/TVT.2021.3085838
DO - 10.1109/TVT.2021.3085838
M3 - Article
AN - SCOPUS:85107325645
SN - 0018-9545
VL - 70
SP - 7347
EP - 7362
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 8
M1 - 9444772
ER -