Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty

Apoorva Chawla; Adarsh Patel; Aditya K. Jagannatham; Pramod K. Varshney

doi:10.1109/VTCFall.2018.8690918

Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty

Apoorva Chawla, Adarsh Patel, Aditya K. Jagannatham, Pramod K. Varshney

Research output: Chapter in Book/Entry/Poem › Conference contribution

6 Scopus citations

Abstract

This paper presents a Neyman-Pearson (NP) criterion based optimal distributed detection framework for a massive multiple-input multiple-output (MIMO) wireless sensor network (WSN). Robust fusion rules are determined for the local decisions transmitted by the sensor nodes, considering the availability of both perfect as well as imperfect channel state information (CSI) at the fusion center. Further, the probability of error of the individual sensor decisions, which arises in practical scenarios, is also incorporated in the decision framework. Closed form expressions are derived to characterize the resulting probabilities of detection and false alarm for the system. Simulation results are presented to demonstrate the improved performance of the proposed detectors in comparison to the existing detectors and to validate the theoretical findings.

Original language	English (US)
Title of host publication	2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538663585
DOIs	https://doi.org/10.1109/VTCFall.2018.8690918
State	Published - Jul 2 2018
Externally published	Yes
Event	88th IEEE Vehicular Technology Conference, VTC-Fall 2018 - Chicago, United States Duration: Aug 27 2018 → Aug 30 2018

Publication series

Name	IEEE Vehicular Technology Conference
Volume	2018-August
ISSN (Print)	1550-2252

Conference

Conference	88th IEEE Vehicular Technology Conference, VTC-Fall 2018
Country/Territory	United States
City	Chicago
Period	8/27/18 → 8/30/18

ASJC Scopus subject areas

Computer Science Applications
Electrical and Electronic Engineering
Applied Mathematics

Access to Document

10.1109/VTCFall.2018.8690918

Cite this

Chawla, A., Patel, A., Jagannatham, A. K., & Varshney, P. K. (2018). Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty. In 2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings Article 8690918 (IEEE Vehicular Technology Conference; Vol. 2018-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2018.8690918

Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty. / Chawla, Apoorva; Patel, Adarsh; Jagannatham, Aditya K. et al.
2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8690918 (IEEE Vehicular Technology Conference; Vol. 2018-August).

Research output: Chapter in Book/Entry/Poem › Conference contribution

Chawla, A, Patel, A, Jagannatham, AK & Varshney, PK 2018, Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty. in 2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings., 8690918, IEEE Vehicular Technology Conference, vol. 2018-August, Institute of Electrical and Electronics Engineers Inc., 88th IEEE Vehicular Technology Conference, VTC-Fall 2018, Chicago, United States, 8/27/18. https://doi.org/10.1109/VTCFall.2018.8690918

@inproceedings{f30c8c209ef94560ae3ae07cd8667d69,

title = "Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty",

abstract = "This paper presents a Neyman-Pearson (NP) criterion based optimal distributed detection framework for a massive multiple-input multiple-output (MIMO) wireless sensor network (WSN). Robust fusion rules are determined for the local decisions transmitted by the sensor nodes, considering the availability of both perfect as well as imperfect channel state information (CSI) at the fusion center. Further, the probability of error of the individual sensor decisions, which arises in practical scenarios, is also incorporated in the decision framework. Closed form expressions are derived to characterize the resulting probabilities of detection and false alarm for the system. Simulation results are presented to demonstrate the improved performance of the proposed detectors in comparison to the existing detectors and to validate the theoretical findings.",

author = "Apoorva Chawla and Adarsh Patel and Jagannatham, {Aditya K.} and Varshney, {Pramod K.}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 88th IEEE Vehicular Technology Conference, VTC-Fall 2018 ; Conference date: 27-08-2018 Through 30-08-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/VTCFall.2018.8690918",

language = "English (US)",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings",

}

TY - GEN

T1 - Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty

AU - Chawla, Apoorva

AU - Patel, Adarsh

AU - Jagannatham, Aditya K.

AU - Varshney, Pramod K.

PY - 2018/7/2

Y1 - 2018/7/2

N2 - This paper presents a Neyman-Pearson (NP) criterion based optimal distributed detection framework for a massive multiple-input multiple-output (MIMO) wireless sensor network (WSN). Robust fusion rules are determined for the local decisions transmitted by the sensor nodes, considering the availability of both perfect as well as imperfect channel state information (CSI) at the fusion center. Further, the probability of error of the individual sensor decisions, which arises in practical scenarios, is also incorporated in the decision framework. Closed form expressions are derived to characterize the resulting probabilities of detection and false alarm for the system. Simulation results are presented to demonstrate the improved performance of the proposed detectors in comparison to the existing detectors and to validate the theoretical findings.

AB - This paper presents a Neyman-Pearson (NP) criterion based optimal distributed detection framework for a massive multiple-input multiple-output (MIMO) wireless sensor network (WSN). Robust fusion rules are determined for the local decisions transmitted by the sensor nodes, considering the availability of both perfect as well as imperfect channel state information (CSI) at the fusion center. Further, the probability of error of the individual sensor decisions, which arises in practical scenarios, is also incorporated in the decision framework. Closed form expressions are derived to characterize the resulting probabilities of detection and false alarm for the system. Simulation results are presented to demonstrate the improved performance of the proposed detectors in comparison to the existing detectors and to validate the theoretical findings.

UR - http://www.scopus.com/inward/record.url?scp=85064939537&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064939537&partnerID=8YFLogxK

U2 - 10.1109/VTCFall.2018.8690918

DO - 10.1109/VTCFall.2018.8690918

M3 - Conference contribution

AN - SCOPUS:85064939537

T3 - IEEE Vehicular Technology Conference

BT - 2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 88th IEEE Vehicular Technology Conference, VTC-Fall 2018

Y2 - 27 August 2018 through 30 August 2018

ER -

Robust Distributed Detection in Massive MIMO Wireless Sensor Networks under CSI Uncertainty

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this