Practical issues in estimation over multiaccess fading channels with TBMA wireless sensor networks

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Practical issues in histogram and parameter estimation over fading channels with type-based multiple access (TBMA) sensor networks is addressed in this paper, where the parameter of interest is estimated through the histogram, or type, of the observations. Existing histogram estimators in the literature require the transmitted signal waveforms to be orthogonal to represent different observations. If the fading channels from the sensors to the fusion center are zero mean, channel state information (CSI) is required at the sensor side. However, in practice, the interference between the orthogonal waveforms, and channel estimation error (CEE) cannot be avoided. How these practical issues affect the histogram and parameter estimation is discussed in this paper. A unified framework for histogram and parameter estimation in the presence of interference and imperfect CSI is proposed. In the interference-free case, a novel histogram estimator is proposed, which does not require the knowledge of the channel statistics at the fusion center, and yields an asymptotically optimal estimator. This approach is then generalized to the presence of interference. The existing estimators without the knowledge of interference statistics are shown to be biased, which motivates the proposed asymptotically optimal estimators that utilize interference statistics. Moreover, the performance of the asymptotically optimal estimators are shown to deteriorate when the waveforms are not orthogonal. Simulation results corroborate our analysis.

Original languageEnglish (US)
Pages (from-to)1217-1229
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume56
Issue number3
DOIs
StatePublished - Mar 2008

Fingerprint

Fading channels
Parameter estimation
Wireless sensor networks
Channel state information
Statistics
Fusion reactions
Sensors
Channel estimation
Sensor networks

Keywords

  • Fading channels
  • Parameter estimation
  • Sensor networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing

Cite this

Practical issues in estimation over multiaccess fading channels with TBMA wireless sensor networks. / Gao, Ping; Tepedelenlioglu, Cihan.

In: IEEE Transactions on Signal Processing, Vol. 56, No. 3, 03.2008, p. 1217-1229.

Research output: Contribution to journalArticle

@article{4c4111aaf9744bca80af85ee74e2ee8d,
title = "Practical issues in estimation over multiaccess fading channels with TBMA wireless sensor networks",
abstract = "Practical issues in histogram and parameter estimation over fading channels with type-based multiple access (TBMA) sensor networks is addressed in this paper, where the parameter of interest is estimated through the histogram, or type, of the observations. Existing histogram estimators in the literature require the transmitted signal waveforms to be orthogonal to represent different observations. If the fading channels from the sensors to the fusion center are zero mean, channel state information (CSI) is required at the sensor side. However, in practice, the interference between the orthogonal waveforms, and channel estimation error (CEE) cannot be avoided. How these practical issues affect the histogram and parameter estimation is discussed in this paper. A unified framework for histogram and parameter estimation in the presence of interference and imperfect CSI is proposed. In the interference-free case, a novel histogram estimator is proposed, which does not require the knowledge of the channel statistics at the fusion center, and yields an asymptotically optimal estimator. This approach is then generalized to the presence of interference. The existing estimators without the knowledge of interference statistics are shown to be biased, which motivates the proposed asymptotically optimal estimators that utilize interference statistics. Moreover, the performance of the asymptotically optimal estimators are shown to deteriorate when the waveforms are not orthogonal. Simulation results corroborate our analysis.",
keywords = "Fading channels, Parameter estimation, Sensor networks",
author = "Ping Gao and Cihan Tepedelenlioglu",
year = "2008",
month = "3",
doi = "10.1109/TSP.2007.909000",
language = "English (US)",
volume = "56",
pages = "1217--1229",
journal = "IEEE Transactions on Signal Processing",
issn = "1053-587X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",

}

TY - JOUR

T1 - Practical issues in estimation over multiaccess fading channels with TBMA wireless sensor networks

AU - Gao, Ping

AU - Tepedelenlioglu, Cihan

PY - 2008/3

Y1 - 2008/3

N2 - Practical issues in histogram and parameter estimation over fading channels with type-based multiple access (TBMA) sensor networks is addressed in this paper, where the parameter of interest is estimated through the histogram, or type, of the observations. Existing histogram estimators in the literature require the transmitted signal waveforms to be orthogonal to represent different observations. If the fading channels from the sensors to the fusion center are zero mean, channel state information (CSI) is required at the sensor side. However, in practice, the interference between the orthogonal waveforms, and channel estimation error (CEE) cannot be avoided. How these practical issues affect the histogram and parameter estimation is discussed in this paper. A unified framework for histogram and parameter estimation in the presence of interference and imperfect CSI is proposed. In the interference-free case, a novel histogram estimator is proposed, which does not require the knowledge of the channel statistics at the fusion center, and yields an asymptotically optimal estimator. This approach is then generalized to the presence of interference. The existing estimators without the knowledge of interference statistics are shown to be biased, which motivates the proposed asymptotically optimal estimators that utilize interference statistics. Moreover, the performance of the asymptotically optimal estimators are shown to deteriorate when the waveforms are not orthogonal. Simulation results corroborate our analysis.

AB - Practical issues in histogram and parameter estimation over fading channels with type-based multiple access (TBMA) sensor networks is addressed in this paper, where the parameter of interest is estimated through the histogram, or type, of the observations. Existing histogram estimators in the literature require the transmitted signal waveforms to be orthogonal to represent different observations. If the fading channels from the sensors to the fusion center are zero mean, channel state information (CSI) is required at the sensor side. However, in practice, the interference between the orthogonal waveforms, and channel estimation error (CEE) cannot be avoided. How these practical issues affect the histogram and parameter estimation is discussed in this paper. A unified framework for histogram and parameter estimation in the presence of interference and imperfect CSI is proposed. In the interference-free case, a novel histogram estimator is proposed, which does not require the knowledge of the channel statistics at the fusion center, and yields an asymptotically optimal estimator. This approach is then generalized to the presence of interference. The existing estimators without the knowledge of interference statistics are shown to be biased, which motivates the proposed asymptotically optimal estimators that utilize interference statistics. Moreover, the performance of the asymptotically optimal estimators are shown to deteriorate when the waveforms are not orthogonal. Simulation results corroborate our analysis.

KW - Fading channels

KW - Parameter estimation

KW - Sensor networks

UR - http://www.scopus.com/inward/record.url?scp=40749083542&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=40749083542&partnerID=8YFLogxK

U2 - 10.1109/TSP.2007.909000

DO - 10.1109/TSP.2007.909000

M3 - Article

AN - SCOPUS:40749083542

VL - 56

SP - 1217

EP - 1229

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

SN - 1053-587X

IS - 3

ER -