Guillaume Gelle

Secure digital communication using discrete-time chaos synchronization

Abstract In this paper we propose some secure digital communication schemes using discrete chaotic systems. In our approach a message is encrypted at the transmitter using chaotic modulation. Next, the driving signal synchronizes the receiver using discrete observer design or drive-response concept. Finally, by reverting the coding procedure the transmitted message is reconstructed. To demonstrate the efficiency of our communication schemes a modified Henon’s map is considered as an illustrative example.

FFT-Based BP Decoding of General LDPC Codes Over Abelian Groups

We introduce a wide class of low-density parity-check (LDPC) codes, large enough to include LDPC codes over finite fields, rings, or groups, as well as some nonlinear codes. A belief-propagation decoding procedure with the same complexity as for the decoding of LDPC codes over finite fields is also presented. Moreover, an encoding procedure is developed

Channel impulse response length and noise variance estimation for OFDM systems with adaptive guard interval

A new algorithm estimating channel impulse response (CIR) length and noise variance for orthogonal frequency-division multiplexing (OFDM) systems with adaptive guard interval (GI) length is proposed. To estimate the CIR length and the noise variance, the different statistical characteristics of the additive noise and the mobile radio channels are exploited. This difference is due to the fact that the variance of the channel coefficients depends on the position within the CIR, whereas the noise variance of each estimated channel tap is equal. Moreover, the channel can vary rapidly, but its length changes more slowly than its coefficients. An auxiliary function is established to distinguish these characteristics. The CIR length and the noise variance are estimated by varying the parameters of this function. The proposed method provides reliable information of the estimated CIR length and the noise variance even at signal-to-noise ratio (SNR) of 0 dB. This information can be applied to an OFDM system with adaptive GI length, where the length of the GI is adapted to the current length of the CIR. The length of the GI can therefore be optimized. Consequently, the spectral efficiency of the system is increased.

Blind source separation: a new pre-processing tool for rotating machines monitoring?

Blind source separation (BSS) is a general signal processing method, which consists of recovering from a finite set of observations recorded by sensors, the contributions of different physical sources independently of the propagation medium and without any a priori knowledge of the sources. Recently, these methods paved a new way for the monitoring or the diagnosis of mechanical systems in a working environment. Actually, we show that BSS allows recovering the vibratory information issued from a single rotating machine working in a noisy environment by freeing the sensor signal from the contribution of other working machines. In that way, BSS can be used as a pre-processing step for rotating machine fault detection and diagnosis.

Optimized irregular low-density parity-check codes for multicarrier modulations over frequency-selective channels

This paper deals with optimized channel coding for OFDM transmissions (COFDM) over frequency-selective channels using irregular low-density parity-check (LDPC) codes. Firstly, we introduce a new characterization of the LDPC code irregularity called “irregularity profile.” Then, using this parameterization, we derive a new criterion based on the minimization of the transmission bit error probability to design an irregular LDPC code suited to the frequency selectivity of the channel. The optimization of this criterion is done using the Gaussian approximation technique. Simulations illustrate the good performance of our approach for different transmission channels.

Asymptotic performance of LDPC codes in impulsive non-Gaussian channel

Advancements in channel coding theory over the past decades have been accomplished considering simple channel such as Additive White Gaussian Noise channels. Much less is known about the consequences when the standard Gaussian assumption is not fulfilled in realistic environments and, more importantly, the appropriate countermeasures. This paper studies and analyzes the performance of low-density parity-check codes (LDPC) in heavy-tailed, non-Gaussian noise channels that can be well adapted to impulsive noise modeling. This non-Gaussian noise are modeled by an indefinite variance symmetric alpha stable noise and the channel is Additive White Symmetric Alpha-Stable Noise channel. The asymptotic Performances of LDPC codes using different demappers over this channel and its capacity are proposed and studied.

Turbo decision aided reconstruction of clipping noise in coded OFDM

High peak average to power ratio (PAPR) is one of the main drawback of the OFDM systems currently used in high rate communication standards. One way to reduce PAPR consists in clipping the amplitude of the OFDM signals introducing an additional noise that degrades the system performances. This work presents two iterative reconstruction algorithms of the clipped samples in coded OFDM systems in presence of channel noise. These two algorithms combine, a classical DAR procedure with an iterative decoding of the channel code in a turbo-like way.

On Detection Method for Soft Iterative Decoding in the Presence of Impulsive Interference

This paper deals with the performance improvement of soft iterative decoders in impulsive interference modeled by additive noise. In case of α-stable noise, the inputs of the belief propagation decoder are too complex to compute. We propose to use an approximation of the log likelihood ratio in an impulsive environment. Even with this simplification, we show that the performance stays close to the one obtained using the true probability density function. Moreover, the robustness of our solution against the parameter estimation is investigated.

Clipping Demapper for LDPC Decoding in Impulsive Channel

Low-Density Parity-Check codes, are a class of linear block codes and have recently received a great deal of attention owing to their excellent performances over Additive White Gaussian Noise channels. However they are not well investigated in non-Gaussian environments, for instance when the noise is impulsive. In this paper we discuss the use of clipping to mitigate the effect of impulsive noise modeled as an α-stable random variable. The slope in the linear section of the demapper and the threshold have a significant impact on the Belief Propagation decoder performance. We show that judicious choices of those parameters can result in an important performance improvement.

Turbo decision aided receivers for clipping noise mitigation in coded OFDM

Orthogonal frequency division multiplexing (OFDM) is the modulation technique used in most of the high-rate communication standards. However, OFDM signals exhibit high peak average to power ratio (PAPR) that makes them particularly sensitive to nonlinear distortions caused by high-power amplifiers. Hence, the amplifier needs to operate at large output backoff, thereby decreasing the average efficiency of the transmitter. One way to reduce PAPR consists in clipping the amplitude of the OFDM signal introducing an additional noise that degrades the overall system performance. In that case, the receiver needs to set up an algorithm that compensates this clipping noise. In this paper, we propose three new iterative receivers with growing complexity and performance that operate at severe clipping: the first and simplest receiver uses a Viterbi algorithm as channel decoder whereas the other two implement a soft-input soft-output (SISO) decoder. Each soft receiver is analyzed through EXIT charts for different mappings. Finally, the performances of the receivers are simulated on both short time-varying channel and AWGN channel.