One of the main issues in using a Low Earth Orbit (LEO) satellite constellation to extend a Low-Powered Wide Area Network is the frequency synchronization. Using a link based on random access solves this concern, but also prevents delivery guarantees, and implies less predictable performance. This paper concerns the estimation of Bit Error Rate (BER) and Packet Error Rate (PER) using physical layer abstractions under a time and frequency random scheme, namely Time and Frequency Aloha. We first derive a BER calculation for noncoded QPSK transmission with one collision. Then, we use the 3GPP LTE NB-IoT coding scheme. We analyze the interference that could be induced by repetition coding scheme and propose an efficient summation to improve the decoder performance. Finally, to estimate a PER for any collided scenario, we propose a physical layer abstraction, which relies on an equivalent Signal-to-Noise Ratio (SNR) calculation based on Mutual Information.

Les modulations à phase continue (CPMs) sont des methodes de modulations robuste à la non-cohérence du canal de propagation. Dans un context spatial, les CPM sont utilisées dans la chaîne de transmission de télémesure de la fusée. Depuis les années 70, la modulation la plus usitée dans les systèmes de télémesures est la modulation CPFSK continuous phase frequency shift keying filtrée. Historiquement, ce type de modulation est concaténée avec un code Reed-Solomon (RS) afin d’améliorer le processus de décodage. Côté récepteur, les séquences CPM non-cohérentes sont démodulées par un détecteur Viterbi à sortie dure et un décodeur RS. Néanmoins, le gain du code RS n’est pas aussi satisfaisant que des techniques de codage moderne capables d’atteindre la limite de Shannon. Actualiser la chaîne de communication avec des codes atteignant la limite de Shannon tels que les codes en graphe creux, implique de remanier l’architecture du récepteur usuel pour un détecteur à sortie souple. Ainsi, on propose dans cette étude d’ élaborer un détecteur treillis à sortie souple pour démoduler les séquences CPM non-ohérentes. Dans un deuxième temps, on concevra des schémas de pré-codages améliorant le comportement asymptotique du récepteur non-cohérent et dans une dernière étape on élabora des codes de parité à faible densité (LDPC) approchant la limite de Shannon.

In this paper, we present two Data-Aided channel estimators for Continuous Phase Modulation (CPM) in the case of transmissions over doubly-selective channels. They both capitalize on the Basis Expansion Model (BEM), widely used for OFDM systems and for Single Carrier transmission with linear modulation. However, in the case of CPM signals, we need to work on a over-sampled received signal (fractionally-spaced representation) as the equalization techniques are also working on the over-sampled received signal. The first one is a classical Least Squares (LS) estimation of the BEM parameters whereas the second channel estimator introduces first a parametric dependence on the paths delays. Indeed, in the case where those delays are known (by estimation or by geometrical consideration as for the aeronautical channel by satellite), the second LS estimation on the BEM parameters is improved and less computationally demanding. Simulations results are provided and show good performance of our parametric LS estimation.

Non-coherent trellis based receiver (TBR) is an effective method to demodulate noncoherent continuous-phase modulated sequences. However it requires to increase the observation length to reach the performance of classical coherent TBRs. Furthermore it appears that both receivers offers different behaviours when considered in a bit-interleaved coded modulation (BICM) system using iterative decoding. Indeed, trellis based outer coding schemes performing well in coherent regime generate error floors in non-coherent regime. In this paper, we show that precoding of the continuous phase modulation (CPM) encoder can deal with the latter issue. The optimization of this non-coherent precoding relies on different objectives than the existing precoding methods introduced in the coherent case. The optimization relies on some asymptotic arguments enabling an efficient BICM scheme using iterative decoding. Using the proposed precoding approach enables to remove error floors in the non-coherent regime while enabling transparent use in the coherent case.

This paper studies a statistical approach to detect and diagnose a particular type of vibration impacting the control surfaces of civil aircraft. The considered phenomenon is called Limit Cycle Oscillation (LCO). It consists of an unwanted sustained oscillation of a control surface due to the combined effect of aeroelastic phenomena and an increased level of mechanical free play in the elements that connect the control surface to the aerodynamic surface. The state-of-the-art for LCO prevention is mainly based on regular free play checks performed on ground during maintenance operations. The detection is mainly achieved by the crew, and especially the pilot who can fill in a so-called "vibration reporting sheet" to describe the phenomena felt during the flight. Thus, the pilot sensitivity to vibration is still the only reference for LCO detection. In the Flight Control System (FCS) of modern aircraft there exist already several certified algorithms for the detection of vibrations of different nature, which use dedicated local sensors to monitor the control surface behaviour. The same kind of sensors have been chosen in a local approach, which eases the isolation of the vibration sources. This paper studies a new statistical approach based on the Generalized Likelihood Ratio Test (GLRT) in order to improve the state-of-the-art for LCO detection and diagnosis. The test and its theoretical performance are derived and validated. A straightforward method compliant with real-time implementation constraint for LCO prediction is proposed. A Monte Carlo test campaign is performed in order to assess the robustness and the detection/diagnosis performance of the proposed algorithm under different operating conditions.