This paper derives new closed-form expressions for the masses of negative multinomial distributions. These masses can be maximized to determine the maximum likelihood estimator of its unknown parameters. An application to polarimetric image processing is investigated. We study the maximum likelihood estimators of the polarization degree of polarimetric images using different combinations of images.

In this article, we evaluate the impact of link layer retransmissions on the performance of TCP in the context of aeronautical communications.We present the architecture of aeronautical networks, which is manly driven by an important channel access delay, and the various retransmission strategies that can be implemented at both link and transport layers. We consider a worst case scenario to illustrate the benefits provided by the ARQ scheme at the link layer in terms of transmission delay.We evaluate the trade-off between allowing a fast data transmission and a low usage of satellite capacity by adjusting link layer parameters.

We present an NS-2 module, Physical Channel Access (PCA), to simulate different access methods on a link shared with Multi-Frequency Time Division Multiple Access (MF-TDMA). This technique is widely used in various network technologies, such as satellite communication. In this context, different access methods at the gateway induce different queuing delays and available capacities, which strongly impact transport layer performance. Depending on QoS requirements, design of new congestion and ow control mechanisms and/or access methods requires evaluation through simulations. PCA module emulates the delays that packets will experience using the shared link, based on descriptive parameters of lower layers characteristics. Though PCA has been developed with DVB-RCS2 considerations in mind (for which we present a use case), other MF-TDMA-based applications can easily be simulated by adapting input parameters. Moreover, the presented implementation details highlight the main methods that might need modifications to implement more specific functionality or emulate other similar access methods (e.g., OFDMA).

This paper addresses the problem of estimating the Potts parameter  jointly with the unknown parameters of a Bayesian model within a Markov chain Monte Carlo (MCMC) algorithm. Standard MCMC methods cannot be applied to this problem because performing inference on  requires computing the intractable normalizing constant of the Potts model. In the proposed MCMC method, the estimation of  is conducted using a likelihood-free Metropolis–Hastings algorithm. Experimental results obtained for synthetic data show that estimating  jointly with the other unknown parameters leads to estimation results that are as good as those obtained with the actual value of . On the other hand, choosing an incorrect value of  can degrade estimation performance significantly. To illustrate the interest of this method, the proposed algorithm is successfully applied to real bidimensional SAR and tridimensional ultrasound images.

Spectral analysis along with the detection of harmonics and modulation sidebands are key elements in condition monitoring systems. Several spectral analysis tools are already able to detect spectral components present in a signal. The challenge is therefore to complete this spectral analysis with a method able to identify harmonic series and modulation sidebands. Compared to the state of the art, the method proposed takes the uncertainty of the frequency estimation into account. The identification is automatically done without any a priori, the search of harmonics is exhaustive and moreover the identification of all the modulation sidebands of each harmonic is done regardless of their energy level. The identified series are characterized by criteria which reflect their relevance and which allow the association of series in families, characteristic of a same physical process. This method is applied on real-world current and vibration data, more or less rich in their spectral content. The identification of sidebands is a strong indicator of failures in mechanical systems. The detection and tracking of these modulations from a very low energy level is an asset for earlier detection of the failure. The proposed method is validated by comparison with expert diagnosis in the concerned fields.

Vibration data acquired during system monitoring periods are rich in harmonics characterizing the presence of several mechanical parts in the system. Periodic variations of the torque or of the load create modulation sidebands around those harmonics. Even if the energy impact of the sidebands is small compared to the total energy of the signal, they are strong indicators of failures in mechanical systems. Unfortunately, these effects are of little concern in most condition monitoring systems. When considering the problem from a signal processing point of view, the demodulation of those sidebands allows for a time visualization of the modulating functions which are a precise image of the torque or the load variations. This demodulation can be done on the analytical signal directly derived from the original data. But to do that, data and specifically its spectrum should respect some constraints. The purpose of this paper is to underline those often neglected constraints. In particular, the respect of the non-overlapping condition in the Bedrosian theorem is discussed for signals and modulation rates that can be encountered on rotating machines. The respect of the constraints depends on the monitored phenomenon (e.g., gear mesh, rotating shaft), the modulation phenomenon (e.g., belt frequency, rotor current) and the type of medium (e.g., vibrations, electrical current). In the case where the constraints are not satisfied, we explain the consequences in terms of signal processing. These results are illustrated by an industrial case study.

Discontinuities at origin have been used to better approximate measured curves in recent papers but generally not explicitly and their physical validity has not always been demonstrated. In this communication, we show that these discontinuities can be explained by physically acceptable discontinuities in the real physical device. We propose simple criteria to accept or reject these discontinuities, in either passive or active devices, depending on the order of the discontinuity. In addition, we show that models having such discontinuities behave differently from classical models. In particular, these discontinuities explain non-integer dB/dB slopes of harmonic power and intermodulation power as a function of input power. Recent and older measurements of intermodulation products in passive devices, telephony base-station and RF transistors show such a behavior so that supposed lack of measurement cannot be used as a reason to reject discontinuities as non-physical.

Broadcasting systems have to deal with channel variability in order to offer the best spectrum efficiency to the receivers. However, the transmission parameters that optimize the spectrum efficiency generally leads to a large link unavailability. In this paper, we study the performance of hierarchical and non-hierarchical modulations in terms of spectrum efficiency and link unavailability for DVB-S2 systems. Our first contribution is the design of the hierarchical 16-APSK for the DVB-S2 standard. Then we introduce the link unavailability to compare the per- formance of hierarchical and non-hierarchical modulations in terms of spectrum efficiency and link unavailability. The results show that hierarchical modulation is a good alternative to non-hierarchical modulation for the DVB-S2 standard.

Content distribution over ad-hoc networks has been widely studied and numerous solutions can be adapted to VANETs (vehicular networks). VANETs, however, can also benefit from an infrastructure in order to improve the efficiency of any content dissemination technique, while allowing more transmissions resources to be available for safety applications. Unfortunately, so far, no such solution has been proposed. In this paper, we introduce the use of an 802.11p infrastructure based on Road Side Units (RSU) for downloading data (eg a map) to vehicles on a highway. At the application level, the main challenge is then how to deliver data to a large number of moving receivers with limited connectivity. While broadcasting data through each RSU should efficiently provide the cars with most of the data, one could believe that some specific transmissions based on vehicles needs could help to reach full downloads. Using simulations, we observed however that the best performances are achieved by a pure broadcasting system.

The kernel least-mean-square (KLMS) algorithm is a popular algorithm in nonlinear adaptive filtering due to its simplicity and robustness. In kernel adaptive filters, the statistics of the input to the linear filter depends on the parameters of the kernel employed. Moreover, practical implementations require a finite nonlinearity model order. A Gaussian KLMS has two design parameters, the step size and the Gaussian kernel bandwidth. Thus, its design requires analytical models for the algorithm behavior as a function of these two parameters. This paper studies the steady-state behavior and the transient behavior of the Gaussian KLMS algorithm for Gaussian inputs and a finite order nonlinearity model. In particular, we derive recursive expressions for the mean-weight-error vector and the mean-square-error. The model predictions show excellent agreement with Monte Carlo simulations in transient and steady state. This allows the explicit analytical determination of stability limits, and gives opportunity to choose the algorithm parameters a priori in order to achieve prescribed convergence speed and quality of the estimate. Design examples are presented which validate the theoretical analysis and illustrates its application.