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ML BLIND CHANNEL ESTIMATION IN OFDM USING CYCLOSTATIONARITY AND SPECTRAL FACTORIZATION
 

Summary: ML BLIND CHANNEL ESTIMATION IN OFDM USING CYCLOSTATIONARITY AND
SPECTRAL FACTORIZATION
A. A. Quadeer and T. Y. Al-Naffouri
Electrical Engineering Department
King Fahd University of Petroleum & Minerals
Email: {aquadeer, naffouri}@kfupm.edu.sa
ABSTRACT
Channel estimation is vital in OFDM systems for efficient data
recovery. In this paper, we propose a blind algorithm for channel
estimation that is based on the assumption that the transmitted data
in an OFDM system is Gaussian (by central limit arguments). The
channel estimate can then be obtained by maximizing the output
likelihood function. Unfortunately, the likelihood function turns out
to be multi-modal and thus finding the global maxima is challeng-
ing. We rely on spectral factorization and the cyclostationarity of the
output to obtain the correct channel zeros. The Genetic algorithm is
then used to fine tune the obtained solution.
Index Terms-- Blind channel estimation, Maximum likelihood
estimation, Spectral factorization, and Genetic algorithm.
1. INTRODUCTION

  

Source: Al-Naffouri, Tareq Y. - Electrical Engineering Department, King Fahd University of Petroleum and Minerals

 

Collections: Engineering