Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2016

22.07.2016

Moment-Based Joint Estimation of Ricean K-Factor and SNR Over Linearly-Modulated Wireless SIMO Channels

verfasst von: M. Bassem Ben Salah, Abdelaziz Samet

Erschienen in: Wireless Personal Communications | Ausgabe 2/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this paper, we develop a new joint estimator for the Ricean K-factor and the signal-to-noise ratio (SNR) when multiple antenna elements receive linearly-modulated signals with a complex additive white Gaussian noise spatially uncorrelated. The fourth-order cross-moments and the second-order moments of the received signal at a single-input multiple-output (SIMO) system are considered. The SNR is deduced by estimating the powers of the useful signals and the noise. While the K-factor is computed by estimating the kurtosises of the transmitted data and the Ricean channel. The new joint estimator is non-data-aided and does not require the a priori knowledge of the modulation type or order. The performances of this algorithm are investigated in terms of normalized root mean square error over different modulated transmissions and compared with the data-aided auto-correlation function (DA-ACF) based joint estimator extended to a SIMO configuration. Simulation results show that our approach outperforms the DA-ACF estimator.
Vorheriger Artikel Power Optimization in MIMO-OFDM Systems with Mixed Orthogonal Frequency Division and Space Division Multiple Access Scheme
Nächster Artikel On Efficient Channel Modeling for Video Transmission over Cognitive Radio Networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
1
Note here that we do not make any assumption about the statistical model of the diffuse component of Ricean channel model. So, we avoid any a priori knowledge about the statistical model of \(\tilde{c}_i\). Of course, it has to be zero mean complex Gaussian process.
 
2
For the SNR estimation, we first estimate the noise power at each antenna element, then, we average it over all antenna elements.
 
3
Of course, we can use an \(\omega _m\) estimator among the literature (see [18] and references therein) and combined with DA-ACF one, but this increases the overall computational complexity.
 
4
These parameters correspond to narrowband channels.
 
Literatur
1.
Stüber, G. L. (2001). Principles of mobile communication (2nd ed.). Boston: Kluwer.MATH
2.
Steele, R., & Hanzo, L. (1999). Mobile radio communications: Second and third generation cellular and WATM systems (2nd ed.). New York: Wiley.CrossRef
3.
Simon, M. K., & Alouini, M. S. (2000). Digital communication over fading channels: A unified approach to performance analysis (2nd ed.). New York: Wiley.CrossRef
4.
Cui, T., Tang, J., Gao, F., & Tellambura, C. (2011). Moment-based parameter estimation and blind spectrum sensing for quadrature amplitude modulation. IEEE Transactions on Communications, 59(2), 613–623.CrossRef
5.
Tepedelenlioglu, C., Abdi, A., & Giannakis, G. B. (2003). The Ricean K-factor: Estimation and performance analysis. IEEE Transactions on Wireless Communications, 2(4), 799–810.CrossRef
6.
Azemi, G., Senadji, B., & Boashash, B. (2004). Ricean K-factor estimation in mobile communication systems. IEEE Communications Letters, 8(10), 550–560.CrossRef
7.
Baddour, K., & Willink, T. (2008). Improved estimation of the Ricean K-factor from I/Q fading channel samples. IEEE Transactions on Wireless Communications, 7(12), 5051–5057.CrossRef
8.
Ramesh, A., Chockalingam, A., & Milstein, L. B. (2002). SNR estimation in Nakagami-m fading with diversity combining and its application to turbo decoding. IEEE Transactions on Communications, 50(11), 1719–1724.CrossRef
9.
Beaulieu, N. C., & Chen, Y. (2005). Maximum likelihood estimation of local average SNR in Ricean fading channels. IEEE Communications Letters, 9(3), 219–222.
10.
Chen, Y., & Beaulieu, N. C. (2007). Estimation of Ricean K parameter and local average SNR from noisy correlated channel samples. IEEE Transactions on Wireless Communications, 6(2), 640–648.CrossRef
11.
Bousnina, I., Ben Salah, M. B., Samet, A., & Dayoub, I. (2012). Ricean K-factor and SNR estimation for M-PSK modulated signals using the fourth-order cross-moments matrix. IEEE Communications Letters, 16(8), 1236–1239.CrossRef
12.
Bousnina, I., Bellili, F., Samet, A., & Affes, S. (2011). Joint estimation of the Ricean K-factor and the SNR for SIMO systems using higher order statistics. In Proceedings on IEEE GLOBECOM (pp. 1–5). Houston, TX, USA, Dec. 2011.
13.
Felhauer, T., Baier, P. W., König, W., & Mohr, W. (1994). Wideband characterisation of fading outdoor radio channels at 1800 MHz to support mobile radio system design. Wireless Personal Communications, 1(2), 137–149.CrossRef
14.
Ziółkowski, C., & Kelner, J. M. (2015). Geometry-based statistical model for the temporal, spectral, and spatial characteristics of the land mobile channel. Wireless Personal Communications, 83(1), 631–652.CrossRef
15.
Bingham, J. A. C. (1990). Multicarrier modulation for data transmission: An idea whose time has come. IEEE Communications Magazine, 28(5), 5–14.MathSciNetCrossRef
16.
Wang, Z., & Giannakis, G. B. (2000). Wireless multicarrier communications: Where Fourier meets Shannon. IEEE Signal Processing Magazine, 17(3), 29–48.CrossRef
17.
Stéphenne, A., Bellili, F., & Affes, S. (2010). Moment-based SNR estimation over linearly-modulated wireless SIMO channels. IEEE Transactions Wireless Communications, 9(2), 714–722.CrossRef
18.
Ben Rejeb, N., Bousnina, I., Ben Salah, M. B., & Samet, A. (2015). Mean angle of arrival, angular and Doppler spreads estimation in MIMO system. IET Signal Processing, 9(5), 395–402.CrossRef
19.
Ben Salah, M. B., & Samet, A. (2015). Modulation identification using moment features for communications via Ricean fading SIMO channels. Wireless Personal Communications, 83(4), 2683–2692.CrossRef
Metadaten
Titel
Moment-Based Joint Estimation of Ricean K-Factor and SNR Over Linearly-Modulated Wireless SIMO Channels
verfasst von
M. Bassem Ben Salah
Abdelaziz Samet
Publikationsdatum
22.07.2016
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2016
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3503-6

Weitere Artikel der Ausgabe 2/2016

Wireless Personal Communications 2/2016 Zur Ausgabe

OriginalPaper

Local Tuning of a Site-Specific Propagation Path Loss Model for Microcell Environments

OriginalPaper

Performance of Cognitive Radio Network with Novel Hybrid Spectrum Access Schemes

OriginalPaper

Iterative Frequency Domain Maximum Likelihood OFDM Carrier Frequency Offset Estimation

OriginalPaper

Defeating the Eavesdropper: On the Achievable Secrecy Capacity Using Reconfigurable Antennas

OriginalPaper

Empirical Models of the Azimuthal Reception Angle—Part I: Comparative Analysis of Empirical Models for Different Propagation Environments

OriginalPaper

Performance of DF Based Dual-Hop Dual-Path Hybrid RF/FSO Cooperative System

Neuer Inhalt

    Bildnachweise