Eric Pierre Simon

Joint Carrier Frequency Offset and Channel Estimation for OFDM Systems via the EM Algorithm in the Presence of Very High Mobility

In this paper, the problem of joint carrier frequency offset (CFO) and channel estimation for OFDM systems over the fast time-varying frequency-selective channel is explored within the framework of the expectation-maximization (EM) algorithm and parametric channel model. Assuming that the path delays are known, a novel iterative pilot-aided algorithm for joint estimation of the multipath Rayleigh channel complex gains (CG) and the carrier frequency offset (CFO) is introduced. Each CG time-variation, within one OFDM symbol, is approximated by a basis expansion model (BEM) representation. An autoregressive (AR) model is built to statistically characterize the variations of the BEM coefficients across the OFDM blocks. In addition to the algorithm, the derivation of the hybrid Cramer-Rao bound (HCRB) for CFO and CGs estimation in our context of very high mobility is provided. We show that the proposed EM has a lower computational complexity than the optimum maximum a posteriori estimator and yet incurs only an insignificant loss in performance.

Impulsive Noise Characterization of In-Vehicle Power Line

Impulsive noise can have a great influence on the performance of in-vehicle power line communication systems. Intensive noise measurements in the time domain were thus carried out on five different vehicles. Preliminary trials were first made on a stationary vehicle and the motor idling, but the characteristics of the measured low-amplitude pulses greatly vary from one car to another. We thus emphasize the characteristics of high-amplitude pulses, greater than 70 mV, observed when the vehicles were moving in traffic, during a 20-min trip. Noise is statistically characterized in terms of duration, frequency content, peak amplitude, and time interval between successive pulses. Stochastic models based on mathematical distribution functions and fitting the experimental distribution of the various pulse characteristics are proposed. It has been found that interarrival time, i.e., the time interval between two successive pulses, is rather short and would be thus the most critical parameter when optimizing the power line communication physical layer.

Joint Carrier Frequency Offset and Fast Time-Varying Channel Estimation for MIMO-OFDM Systems

In this paper, a novel pilot-aided iterative algorithm is developed for MIMO-OFDM systems operating in fast time-varying environment. An L-path channel model with known path delays is considered to jointly estimate the multi-path Rayleigh channel complex gains and Carrier Frequency Offset (CFO). Each complex gain time-variation within one OFDM symbol is approximated by a Basis Expansion Model (BEM) representation. An auto-regressive (AR) model is built for the parameters to be estimated. The algorithm performs recursive estimation using Extended Kalman Filtering. Hence, the channel matrix is easily computed and the data symbol is estimated with free inter-sub-carrier-interference (ICI) when the channel matrix is QR-decomposed. It is shown that only one iteration is sufficient to approach the performance of the ideal case for which the knowledge of the channel response and CFO is available.

Synchronization Over Rapidly Time-Varying Multipath Channel for CDMA Downlink RAKE Receivers in Time-Division Mode

In this paper, we consider a time-division code-division multiple-access (CDMA) system operating in downlink mode in a multiuser multipath channel scenario. In order to implement RAKE reception, the delays, phases, and magnitudes of the different paths need to be estimated and the estimates updated. In the context of burst transmissions, delays do not vary during a burst, and only phases and magnitudes need to be tracked. In this paper, we investigate the issue of phase tracking over rapidly time-varying multipath channels. We propose a new version of the conventional phase loop that mitigates the interpath interference effect. The optimization is based on the concept of prefiltering. The analysis shows improved tracking performance in comparison with the standard phase recovery algorithm.

Iterative Soft-Kalman Channel Estimation for Fast Time-Varying MIMO-OFDM Channels

This letter addresses the problem of channel estimation in fast time-varying frequency selective channels. Considering orthogonal frequency division multiplexing in a multiple-input multiple-output system, we perform soft-Kalman filtering for channel estimation in conjunction with soft-interference canceling at the receiver to reduce the inter-carrier interference. We also propose two simplified implementations of the soft-Kalman filter for the case of constant-modulus signal constellations that allow considerable reductions in the receiver computational complexity, while performing more or less closely to the exact soft-Kalman estimator, depending on channel conditions. For non-constant-modulus signal constellations, however, the exact formulation of the soft-Kalman filter should be used.

Blind digital modulation identification for time-selective MIMO channels

This paper addresses the problem of blind digital modulation identification in time-selective multiple-input multiple-output channels. Our objective is to recognize modulation schemes in highly-mobile communication environments, for military or high-speed railway applications, without signal knowledge or Channel State Information at the receiver. The proposed identification process is based on Blind Source Separation (BSS) and feature classification. We introduce a sliding window technique for the BSS of a faded-mixture to overcome the effect of the high mobility. Then, to improve the recognition of modulation schemes, we adopt a specific multi Artificial-Neural-Network (ANN) classifier, where each ANN is trained to be used within a particular Signal-to-Noise Ratio range. The proposed identifier has a good probability for achieving correct identifications under high velocity for typical carrier frequency and bandwidth.

On the possibility of using PLC in aircraft

Possible applications of PLC in aircraft are investigated. The scenario which has been selected is a data transmission for the remote control of the lighting system of the cabin. Indeed, the tree-shaped architecture of the cabling is complicated enough to be representative of many other harness aircraft configurations. Narrow band and wide band channel characteristics are deduced from a theoretical model of the propagation on multi-wire transmission lines. A software tool simulating a PLC transmission based on OPERA specifications was developed and examples on the performances of the OFDM link are presented.

Broadband wireless channel measurements for high speed trains

We describe a channel sounding measurement campaign for cellular broadband wireless communications with high speed trains that was carried out in the context of the project CORRIDOR. The campaign combines MIMO and carrier aggregation to achieve very high throughputs. We compare two different scenarios, the first one reflects a cellular deployment, where the base station is about 1km away from the railway line. The second scenario corresponds to a railway deployed network, where the base station is located directly next the railway line. We present the general parameters of the measurement campaign and some results of Power Delay Profiles and Doppler Spectra and their evolution over time. Finally we present a simple channel model that captures the main effects observed in the measurements.

On classifiers for blind feature-based automatic modulation classification over multiple-input–multiple-output channels

Modulation recognition is crucial for a good environmental awareness required by cognitive radio systems. In this study, the authors design and compare models of four among the most commonly used classifiers for feature-based automatic modulation classification (FB-AMC) algorithms. Classifiers whose models will be designed are classification tree, K-nearest neighbours, artificial neural networks (ANNs), and support vector machines. In this study, they apply some statistical pattern recognition techniques in the context of blind FB-AMC over multiple-input–multiple-output channels. Comparison criteria are classification accuracy and computational complexity. To improve the impartiality of this comparison, each classifier is optimally deployed by selecting its optimal model with respect to their context. Model selection for the classifiers is done using the ‘k-fold cross-validation’ model validation technique. The comparison study, within the considered context, shows that ANN classifiers have the best performance/complexity tradeoff.

Joint Estimation of Carrier Frequency Offset and Channel Complex Gains for OFDM Systems in Fast Time-Varying Vehicular Environments

In this paper, the physical nature of the radio-channel is considered by using an