Abstract

We consider a wireless sensor network for distributed estimation over fading channels. The sensors transmit their observations over a multiple access fading channel to a fusion center (FC), where a source parameter is estimated. The sensor transmissions add incoherently over a multiple access channel, which motivates the need for channel knowledge at the sensors to improve performance. We consider the effects of different fading channel models on the performance of the system, and characterize the effect of different amounts of channel information at the sensors. We calculate the variance of the estimate for cases when both perfect, and differing amounts of partial channel information are available at the sensors. Asymptotic variance expressions for large number of sensors are derived for different channel statistics and feedback scenarios.We show that the degradation in variance due to using only channel phase information is at most a factor of 4/π over Rayleigh fading channels. We consider continuous feedback error and evaluate the degradation in performance due to differing degrees of error. The loss in performance due to feedback quantization, and effect of error in feedback are also quantified. We also consider speed of convergence, and compare the rate of convergence under different conditions. Further, we characterize the effect of correlated channels between sensors and the FC, and provide the different values for the speed of convergence for this case. Simulation results are provided to show that only a few tens of sensors are required for the asymptotic results to hold. Numerical results corroborate our analytical results.

Original languageEnglish (US)
Article number5170081
Pages (from-to)414-425
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume58
Issue number1
DOIs
StatePublished - Jan 2010

Fingerprint

Fading channels
Feedback
Sensors
Fusion reactions
Degradation
Rayleigh fading
Wireless sensor networks
Statistics

Keywords

  • Distributed estimation
  • Fading channels
  • Feedback
  • Multisensor systems
  • Parameter estimation
  • Quantization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing

Cite this

Estimation over fading channels with limited feedback using distributed sensing. / Banavar, Mahesh K.; Tepedelenlioglu, Cihan; Spanias, Andreas.

In: IEEE Transactions on Signal Processing, Vol. 58, No. 1, 5170081, 01.2010, p. 414-425.

Research output: Contribution to journalArticle

@article{78d21f04dc344af1b4eeff0ed6da61fe,
title = "Estimation over fading channels with limited feedback using distributed sensing",
abstract = "We consider a wireless sensor network for distributed estimation over fading channels. The sensors transmit their observations over a multiple access fading channel to a fusion center (FC), where a source parameter is estimated. The sensor transmissions add incoherently over a multiple access channel, which motivates the need for channel knowledge at the sensors to improve performance. We consider the effects of different fading channel models on the performance of the system, and characterize the effect of different amounts of channel information at the sensors. We calculate the variance of the estimate for cases when both perfect, and differing amounts of partial channel information are available at the sensors. Asymptotic variance expressions for large number of sensors are derived for different channel statistics and feedback scenarios.We show that the degradation in variance due to using only channel phase information is at most a factor of 4/π over Rayleigh fading channels. We consider continuous feedback error and evaluate the degradation in performance due to differing degrees of error. The loss in performance due to feedback quantization, and effect of error in feedback are also quantified. We also consider speed of convergence, and compare the rate of convergence under different conditions. Further, we characterize the effect of correlated channels between sensors and the FC, and provide the different values for the speed of convergence for this case. Simulation results are provided to show that only a few tens of sensors are required for the asymptotic results to hold. Numerical results corroborate our analytical results.",
keywords = "Distributed estimation, Fading channels, Feedback, Multisensor systems, Parameter estimation, Quantization",
author = "Banavar, {Mahesh K.} and Cihan Tepedelenlioglu and Andreas Spanias",
year = "2010",
month = "1",
doi = "10.1109/TSP.2009.2028196",
language = "English (US)",
volume = "58",
pages = "414--425",
journal = "IEEE Transactions on Signal Processing",
issn = "1053-587X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

TY - JOUR

T1 - Estimation over fading channels with limited feedback using distributed sensing

AU - Banavar, Mahesh K.

AU - Tepedelenlioglu, Cihan

AU - Spanias, Andreas

PY - 2010/1

Y1 - 2010/1

N2 - We consider a wireless sensor network for distributed estimation over fading channels. The sensors transmit their observations over a multiple access fading channel to a fusion center (FC), where a source parameter is estimated. The sensor transmissions add incoherently over a multiple access channel, which motivates the need for channel knowledge at the sensors to improve performance. We consider the effects of different fading channel models on the performance of the system, and characterize the effect of different amounts of channel information at the sensors. We calculate the variance of the estimate for cases when both perfect, and differing amounts of partial channel information are available at the sensors. Asymptotic variance expressions for large number of sensors are derived for different channel statistics and feedback scenarios.We show that the degradation in variance due to using only channel phase information is at most a factor of 4/π over Rayleigh fading channels. We consider continuous feedback error and evaluate the degradation in performance due to differing degrees of error. The loss in performance due to feedback quantization, and effect of error in feedback are also quantified. We also consider speed of convergence, and compare the rate of convergence under different conditions. Further, we characterize the effect of correlated channels between sensors and the FC, and provide the different values for the speed of convergence for this case. Simulation results are provided to show that only a few tens of sensors are required for the asymptotic results to hold. Numerical results corroborate our analytical results.

AB - We consider a wireless sensor network for distributed estimation over fading channels. The sensors transmit their observations over a multiple access fading channel to a fusion center (FC), where a source parameter is estimated. The sensor transmissions add incoherently over a multiple access channel, which motivates the need for channel knowledge at the sensors to improve performance. We consider the effects of different fading channel models on the performance of the system, and characterize the effect of different amounts of channel information at the sensors. We calculate the variance of the estimate for cases when both perfect, and differing amounts of partial channel information are available at the sensors. Asymptotic variance expressions for large number of sensors are derived for different channel statistics and feedback scenarios.We show that the degradation in variance due to using only channel phase information is at most a factor of 4/π over Rayleigh fading channels. We consider continuous feedback error and evaluate the degradation in performance due to differing degrees of error. The loss in performance due to feedback quantization, and effect of error in feedback are also quantified. We also consider speed of convergence, and compare the rate of convergence under different conditions. Further, we characterize the effect of correlated channels between sensors and the FC, and provide the different values for the speed of convergence for this case. Simulation results are provided to show that only a few tens of sensors are required for the asymptotic results to hold. Numerical results corroborate our analytical results.

KW - Distributed estimation

KW - Fading channels

KW - Feedback

KW - Multisensor systems

KW - Parameter estimation

KW - Quantization

UR - http://www.scopus.com/inward/record.url?scp=72949105636&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=72949105636&partnerID=8YFLogxK

U2 - 10.1109/TSP.2009.2028196

DO - 10.1109/TSP.2009.2028196

M3 - Article

AN - SCOPUS:72949105636

VL - 58

SP - 414

EP - 425

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

SN - 1053-587X

IS - 1

M1 - 5170081

ER -