Nonlinear Amplify-and-Forward Distributed Estimation over Nonidentical Channels

Robert Santucci, Mahesh K. Banavar, Cihan Tepedelenlioʇlu, Andreas Spanias

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents the use of nonlinear distributed estimation in a wireless system transmitting over channels with random gains. Specifically, we discuss the development of estimators and analytically determine their attainable variance for two conditions: 1) when full channel state information (CSI) is available at the transmitter and receiver; and 2) when only channel gain statistics and phase information are available. For the case where full CSI is available, we formulate an optimization problem to allocate power among each of the transmitting sensors while minimizing the estimate variance. We show that minimizing the estimate variance when the transmitter is operating in its most nonlinear region can be formulated in a manner very similar to optimizing sensor gains with full CSI and linear transmitters. Furthermore, we show that the solution to this optimization problem in most scenarios is approximately equivalent to one of two low-complexity power allocation systems.

Original languageEnglish (US)
Article number6982200
Pages (from-to)5390-5395
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Volume64
Issue number11
DOIs
StatePublished - Nov 1 2015

Fingerprint

Distributed Estimation
Amplify-and-forward
Channel state information
Channel State Information
Transmitter
Transmitters
Optimization Problem
Nonlinear Estimation
Sensor
Sensors
Power Allocation
Estimate
Low Complexity
Receiver
Statistics
Estimator
Scenarios

Keywords

  • Channel estimation
  • Estimation
  • Mathematical model
  • Noise
  • Noise measurement
  • Optimization
  • Sensors

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Aerospace Engineering
  • Automotive Engineering
  • Computer Networks and Communications
  • Applied Mathematics

Cite this

Nonlinear Amplify-and-Forward Distributed Estimation over Nonidentical Channels. / Santucci, Robert; Banavar, Mahesh K.; Tepedelenlioʇlu, Cihan; Spanias, Andreas.

In: IEEE Transactions on Vehicular Technology, Vol. 64, No. 11, 6982200, 01.11.2015, p. 5390-5395.

Research output: Contribution to journalArticle

Santucci, Robert ; Banavar, Mahesh K. ; Tepedelenlioʇlu, Cihan ; Spanias, Andreas. / Nonlinear Amplify-and-Forward Distributed Estimation over Nonidentical Channels. In: IEEE Transactions on Vehicular Technology. 2015 ; Vol. 64, No. 11. pp. 5390-5395.
@article{0dad52aea22b41759d0cf147741e6a8c,
title = "Nonlinear Amplify-and-Forward Distributed Estimation over Nonidentical Channels",
abstract = "This paper presents the use of nonlinear distributed estimation in a wireless system transmitting over channels with random gains. Specifically, we discuss the development of estimators and analytically determine their attainable variance for two conditions: 1) when full channel state information (CSI) is available at the transmitter and receiver; and 2) when only channel gain statistics and phase information are available. For the case where full CSI is available, we formulate an optimization problem to allocate power among each of the transmitting sensors while minimizing the estimate variance. We show that minimizing the estimate variance when the transmitter is operating in its most nonlinear region can be formulated in a manner very similar to optimizing sensor gains with full CSI and linear transmitters. Furthermore, we show that the solution to this optimization problem in most scenarios is approximately equivalent to one of two low-complexity power allocation systems.",
keywords = "Channel estimation, Estimation, Mathematical model, Noise, Noise measurement, Optimization, Sensors",
author = "Robert Santucci and Banavar, {Mahesh K.} and Cihan Tepedelenlioʇlu and Andreas Spanias",
year = "2015",
month = "11",
day = "1",
doi = "10.1109/TVT.2014.2381094",
language = "English (US)",
volume = "64",
pages = "5390--5395",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",

}

TY - JOUR

T1 - Nonlinear Amplify-and-Forward Distributed Estimation over Nonidentical Channels

AU - Santucci, Robert

AU - Banavar, Mahesh K.

AU - Tepedelenlioʇlu, Cihan

AU - Spanias, Andreas

PY - 2015/11/1

Y1 - 2015/11/1

N2 - This paper presents the use of nonlinear distributed estimation in a wireless system transmitting over channels with random gains. Specifically, we discuss the development of estimators and analytically determine their attainable variance for two conditions: 1) when full channel state information (CSI) is available at the transmitter and receiver; and 2) when only channel gain statistics and phase information are available. For the case where full CSI is available, we formulate an optimization problem to allocate power among each of the transmitting sensors while minimizing the estimate variance. We show that minimizing the estimate variance when the transmitter is operating in its most nonlinear region can be formulated in a manner very similar to optimizing sensor gains with full CSI and linear transmitters. Furthermore, we show that the solution to this optimization problem in most scenarios is approximately equivalent to one of two low-complexity power allocation systems.

AB - This paper presents the use of nonlinear distributed estimation in a wireless system transmitting over channels with random gains. Specifically, we discuss the development of estimators and analytically determine their attainable variance for two conditions: 1) when full channel state information (CSI) is available at the transmitter and receiver; and 2) when only channel gain statistics and phase information are available. For the case where full CSI is available, we formulate an optimization problem to allocate power among each of the transmitting sensors while minimizing the estimate variance. We show that minimizing the estimate variance when the transmitter is operating in its most nonlinear region can be formulated in a manner very similar to optimizing sensor gains with full CSI and linear transmitters. Furthermore, we show that the solution to this optimization problem in most scenarios is approximately equivalent to one of two low-complexity power allocation systems.

KW - Channel estimation

KW - Estimation

KW - Mathematical model

KW - Noise

KW - Noise measurement

KW - Optimization

KW - Sensors

UR - http://www.scopus.com/inward/record.url?scp=84947751774&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84947751774&partnerID=8YFLogxK

U2 - 10.1109/TVT.2014.2381094

DO - 10.1109/TVT.2014.2381094

M3 - Article

AN - SCOPUS:84947751774

VL - 64

SP - 5390

EP - 5395

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 11

M1 - 6982200

ER -