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Distributed parameter detection in massive MIMO wireless sensor networks relying on imperfect CSI

Distributed parameter detection in massive MIMO wireless sensor networks relying on imperfect CSI
Distributed parameter detection in massive MIMO wireless sensor networks relying on imperfect CSI
Distributed parameter detection is conceived for massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs), where multiple sensors collaborate to detect the presence/ absence of a spatially correlated parameter. Neyman-Pearson (NP) and generalized likelihood ratio test (GLRT)-based detectors are developed at the fusion center (FC) for known and unknown parameter detection scenarios, respectively. More explicitly, the GLRT detector also has to estimate the unknown parameter value. Closed-form expressions are derived for the probabilities of detection (PD) and false alarm (PFA) in order to characterize the performance of the proposed schemes. Furthermore, the optimal sensor transmit gains are determined for maximising the detection performance attained. An asymptotic performance analysis is carried out for determining the gain scaling laws for the massive MIMO WSN considered, when the number of antennas tends to infinity. The proposed framework is also extended to the realistic imperfect channel knowledge scenario at the FC, followed by the development of the associated fusion rules and analytical results to characterize the performance. Our simulation results closely tally the theoretical findings.
Antenna arrays, Detectors, MIMO communication, Neyman-Pearson (NP) criterion, Sensor arrays, Sensor phenomena and characterization, Wireless sensor networks, Wireless sensor networks (WSNs), generalized likelihood ratio test (GLRT), massive multiple-input multiple-output (MIMO)
1536-1276
Chawla, Apoorva
4327323a-dc7b-4f7e-bd8e-8c8dd85093ff
Sarode, Ajay Satyakumar
59a77d96-f3d0-487b-9c2d-26dadaa65bc5
Jagannatham, Aditya K.
ea2f628b-0f2a-48a3-a293-122c809757aa
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chawla, Apoorva
4327323a-dc7b-4f7e-bd8e-8c8dd85093ff
Sarode, Ajay Satyakumar
59a77d96-f3d0-487b-9c2d-26dadaa65bc5
Jagannatham, Aditya K.
ea2f628b-0f2a-48a3-a293-122c809757aa
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chawla, Apoorva, Sarode, Ajay Satyakumar, Jagannatham, Aditya K. and Hanzo, Lajos (2020) Distributed parameter detection in massive MIMO wireless sensor networks relying on imperfect CSI. IEEE Transactions on Wireless Communications. (doi:10.1109/TWC.2020.3025877).

Record type: Article

Abstract

Distributed parameter detection is conceived for massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs), where multiple sensors collaborate to detect the presence/ absence of a spatially correlated parameter. Neyman-Pearson (NP) and generalized likelihood ratio test (GLRT)-based detectors are developed at the fusion center (FC) for known and unknown parameter detection scenarios, respectively. More explicitly, the GLRT detector also has to estimate the unknown parameter value. Closed-form expressions are derived for the probabilities of detection (PD) and false alarm (PFA) in order to characterize the performance of the proposed schemes. Furthermore, the optimal sensor transmit gains are determined for maximising the detection performance attained. An asymptotic performance analysis is carried out for determining the gain scaling laws for the massive MIMO WSN considered, when the number of antennas tends to infinity. The proposed framework is also extended to the realistic imperfect channel knowledge scenario at the FC, followed by the development of the associated fusion rules and analytical results to characterize the performance. Our simulation results closely tally the theoretical findings.

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More information

Accepted/In Press date: 20 September 2020
e-pub ahead of print date: 29 September 2020
Additional Information: Publisher Copyright: IEEE
Keywords: Antenna arrays, Detectors, MIMO communication, Neyman-Pearson (NP) criterion, Sensor arrays, Sensor phenomena and characterization, Wireless sensor networks, Wireless sensor networks (WSNs), generalized likelihood ratio test (GLRT), massive multiple-input multiple-output (MIMO)

Identifiers

Local EPrints ID: 444102
URI: http://eprints.soton.ac.uk/id/eprint/444102
ISSN: 1536-1276
PURE UUID: f4f6ff29-11b0-4631-807b-9d8b25b8ded6
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 25 Sep 2020 16:31
Last modified: 04 Oct 2022 04:01

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Contributors

Author: Apoorva Chawla
Author: Ajay Satyakumar Sarode
Author: Aditya K. Jagannatham
Author: Lajos Hanzo ORCID iD

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