Browsing by Author "Moeneclaey, Marc"

Now showing 1 - 2 of 2

Citation Count: 1
Blind-phase noise estimation in OFDM systems by sequential Monte Carlo method
(John Wiley and Sons Ltd, 2006) Panayırcı, Erdal; Çırpan, Hakan Ali; Moeneclaey, Marc; Noels, Nele
One of the main drawbacks of orthogonal frequency division multiplexing (OFDM) systems is the phase noise (PN) caused by the oscillator instabilities. Unfortunately due to the PN the most valuable feature namely orthogonality between the carriers is destroyed resulting in a significant degradation in the performance of OFDM systems. In this paper based on a sequential Monte Carlo method (particle filtering) a computationally efficient algorithm is presented for estimating the residual phase noise blindly generated at the output of the phase tracking loop employed in OFDM systems. The basic idea is to treat the transmitted symbols as 'missing data' and draw samples sequentially of them based on the observed signal samples up to time t. This way the Bayesian estimates of the phase noise is obtained through these samples sequentially drawn together with their importance weights. The proposed receiver structure is seen to be ideally suited for highspeed parallel implementation using VLSI technology. The performance of the proposed approaches are studied in terms of average mean square error. Through experimental results the effects of an initialisation on the tracking performance are also explored. Copyright (c) 2006 AEIT.
Citation Count: 5
Monte Carlo Solutions for Blind Phase Noise Estimation
(Springer International Publishing Ag, 2009) Panayırcı, Erdal; Duyck, Dieter; Cirpan, Hakan Ali; Panayırcı, Erdal; Moeneclaey, Marc
This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN) channels. The main contributions of the paper are (i) the development of a Monte Carlo framework for phase noise estimation with special attention to sequential importance sampling and Rao-Blackwellization (ii) the interpretation of existing Monte Carlo solutions within this generic framework and (iii) the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that on one hand the Monte Carlo phase noise estimators outperform the existing estimators and on the other hand our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions. Copyright (C) 2009 Frederik Simoens et al.