CFP last date
20 May 2024
Reseach Article

Performance Evaluation and Comparison of Various Channel Estimation Algorithms

Published on None 2011 by Divya Rao, Sanjeev Ghosh
journal_cover_thumbnail
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET - Number 3
None 2011
Authors: Divya Rao, Sanjeev Ghosh
b422681b-fd39-4147-970c-bc567d885f5d

Divya Rao, Sanjeev Ghosh . Performance Evaluation and Comparison of Various Channel Estimation Algorithms. International Conference and Workshop on Emerging Trends in Technology. ICWET, 3 (None 2011), 7-10.

@article{
author = { Divya Rao, Sanjeev Ghosh },
title = { Performance Evaluation and Comparison of Various Channel Estimation Algorithms },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { None 2011 },
volume = { ICWET },
number = { 3 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 7-10 },
numpages = 4,
url = { /proceedings/icwet/number3/2080-aca563/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Divya Rao
%A Sanjeev Ghosh
%T Performance Evaluation and Comparison of Various Channel Estimation Algorithms
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET
%N 3
%P 7-10
%D 2011
%I International Journal of Computer Applications
Abstract

This paper compares different channel estimation techniques used in OFDM. In order to exploit all these advantages and maximize the performance of OFDM systems, Channel state information (CSI) plays a very important role. Due to the multipath channel there is some intersymbol interference (ISI) in the received signal.Therefore a signal detector (like MLSE or MAP) needs to know channel impulse response (CIR) characteristics to ensure successful equalisation (removal of ISI).The Mean Squared Error and Signal-to-Noise Ratio (SNR) is used as a metric for comparing the results. The Simulation is done and comparison is shown using the simulation plots.

References
  1. Markku Pukkila L. 2000. Channel Estimation Modeling S-72.333 Postgraduate Course in radiocommunications
  2. Jiun Siew, Robert Piechocki, Andrew Nix, and Simon Armour . A Channel Estimation Method for MIMO-OFDM SystemsCentre for Communications Research, University of Bristol.
  3. Pradya Pornnimitkul, Suwich Kunaruttanapruk, Bamrung Tau Sieskul and Somchai Jitapunkul “Blind Channel Estimation Based on URV Decomposition Technique for Uplink of MC-CDMA” In Proceedings of the World Academy of Science, Engineering and Technology 2 2005, Chulalongkorn University, Bangkok, Thailand 10330
  4. Yushi Shen and Ed Martinez. 2006. Channel Estimation in OFDM Systems,in Freescale Semiconductor
  5. M. Belotserkovsky. An equalizer initialization algorithm for OFDM receivers. Digest of Technica Papers, International Conference on Consumer Electronics, 2002, pages 372–373, 2002.
  6. Luise M., Reggiannini, and Vitteta G., \Blind equalization/detection for ofdm signals over frequency selective channels," IEEE J. Selected Areas Commun., vol. 16, no. 8, Oct. 1998.
  7. Seshadri N., \Joint data and channel estimation using fast blind trellis search algorithms,"in Proc. Globecom, 1990, pp. 1659{1663
  8. N. Yee and J. Linnartz, “Multi-Carrier CDMA in an Indoor Wireless Radio Channel,” in Proc. IEEE Int. Symp. On Personal,Indoor and Mobile Radio Commun., Vol. 2, Sep. 1993, pp. 109-113.
  9. S. Hara and R. Prasad, “DS-CDMA, MC-CDMA and MTCDMA for Mobile Multimedia Communication,” in Proc. IEEE Vehic. Technol. Conf., Vol. 3, May 1996, pp. 106-111.
Index Terms

Computer Science
Information Sciences

Keywords

OFDM Pilot assisted channel estimation semi blind channel estimation semi blind channel estimation Iterative channel estimation MMSE SNR