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We address the challenging problem of the joint estimation of transmitted symbols and phase distortions in standardized multicarrier systems, including pilot or virtual subcarriers. These subcarriers create time correlation on the useful transmitted OFDM signal that we propose to take into account by an autoregressive model. Because the phase distortions are nonlinear, we set the joint estimation algorithm on the framework of the Sequential Monte Carlo methods. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE); they highlight the efficiency and the robustness of the estimator.

Regarding the“Digital Subscriber lines’’ (DSLs), the “Digital Audio Broadcast’’ (DAB), the IEEE 802.11 “Wireless Local Area Network’’ (WLAN), or the IEEE 802.16, most of the recent communications systems are based on orthogonal multicarrier technologies. Unfortunately, such technologies are sensitive to phase noise (PHN) and carrier frequency offset (CFO) coming from the defaults of the oscillators. These phase distortions destroy the orthogonality between subcarriers and lead after Fourier Transform to both a common rotation of all the symbols and intercarrier interferences. In this paper, we propose to take into account the time evolution of the OFDM symbols for the joint estimation of the transmitted symbols, the phase noise and the frequency offset. The Sequential Monte-Carlo-based algorithm we have proposed in [

In this paper,

First, input i.i.d. bits are encoded into M-QAM symbols

After the Inverse Discrete Fourier Transform (IDFT), the samples of the transmitted signal can be written, for

The resulting signal is transmitted in a time varying frequency selective channel

Under matrix notation, the received signal

At the receiver, the cyclic prefix is first discarded, then, assuming

Due to the independence of the process between two different OFDM symbols, the process at time

They are obtained by solving both the noise variance equation

The correlation function

This correlation function clearly shows that, for

By using the dynamic evolution of the PHN (

In order to jointly estimate

The dynamic state space model (

The correlation of the unknown OFDM signal

We notice that the DSS model (

With regard to the system parameters, 16-QAM modulation is assumed and we have chosen

Figure

BER performance of the proposed JSCPE-MPF versus

With AR model

Without AR model

MSE of the multicarrier signal estimate using the proposed AR model (solid lines) and without the AR model (dashed lines) versus

In this paper, we address the difficult problem of data detection in pilot-aided multicarrier systems that suffer from the presence of phase noise and carrier frequency offset. The originality of this work consists in an autoregressive modeling of the OFDM signal from which we have deduced an SMC method for time domain processing of the nonlinear received signal. Numerical simulations show that even with significant PHN rates, the JSCPE-MPF achieves good performance in terms of both the phase distortion estimation and BER performance; moreover, it offers a significant performance gain in comparison to existing methods. Thus the JSCPE-MPF algorithm with AR modeling can be efficiently used with the channel estimator proposed in [