2D regression channel estimation for equalizing OFDM signals

Ming X. Chang*, Yu-Ted Su

*Corresponding author for this work

Research output: Contribution to journalConference article

12 Scopus citations

Abstract

In this paper, we present a channel estimation method for Orthogonal Frequency Division Multiplexing (OFDM) signals. Our method is based on a two-dimensional nonlinear regression method, taking into account the correlations of the fading process in both time and frequency domains. We derive a general bit error rate (BER) expression which can also used to predict the performance of many other OFDM channel estimates. The performance of this new estimate is very close to the theoretical bit error probability lower bound that is obtained by assuming that the channel response is perfectly known. Unlike linear minimum mean-squared-error (LMMSE) channel estimates, it needs not to know or estimate channel statistics like channel correlation matrix and SNR hence is insensitive to additive white Gaussian noise (AWGN).

Original languageEnglish
Pages (from-to)240-244
Number of pages5
JournalIEEE Vehicular Technology Conference
Volume1
DOIs
StatePublished - 1 Jan 2000
EventVTC2000: 51st Vehicular Technology Conference 'Shaping History Through Mobile Technologies' - Tokyo, Jpn
Duration: 15 May 200018 May 2000

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