Satellite communications can provide fourth generation (4G) networks with large-scale coverage. However, their integration to 4G is challenging because satellite networks have not been designed with handover in mind. The setup of satellite links takes time, and so, handovers must be anticipated long before. This paper proposes a generic scheme based on the Institute of Electrical and Electronics Engineers 802.21 standard to optimize handover and resource management in hybrid satellite-terrestrial networks. Our solution, namely optimized handover and resource management (OHRM), uses the terrestrial interface to prepare handover, which greatly speeds up the establishment of the satellite link. We propose two mechanisms to minimize the waste of bandwidth due to wrong handover predictions. First, we leverage the support of 802.21 in the terrestrial access network to shorten the path of the signaling messages towards the satellite resource manager. Second, we cancel the restoration of the satellite resources when the terrestrial link rolls back. We use OHRM to interconnect a digital video broadcasting and a wireless 4G terrestrial network. However for the simulation tool, we use a WiMAX as the terrestrial technology to illustrate the schemes. The simulation results show that OHRM minimizes the handover delay and the signaling overhead in the terrestrial and satellite networks.

The unprecedented success of wireless telecommunication systems has resulted in the wireless spectrum becoming a scarce resource. At the same time, extensive measurements conducted in the early 2000’s have shown that a significant part of the licensed spectrum, for instance that dedicated to TV broadcast services, is under-utilized. Cognitive Radio systems have been proposed as the enabling technology allowing unlicensed equipments, referred to as secondary users, to opportunistically access the licensed spectrum when not in use by the licensed users, referred to as primary users. Obviously, changing decades-old policies on spectrum access in the civilian and military domain will not happen overnight and many issues, technological and legal, will have to be ironed out first. However, the fundamental principle that we expect to underlie all solutions is that of access while doing no harm – secondary users should not interfere with primary users. The focus of this thesis is on heterogeneous tactical networks deploying cognitive radios in parts or in their entirety. Such networks can be organized in multiple sub-networks, each characterized by a specific topology, medium access scheme and spectrum access policy. As a result, providing end-to-end Quality of Service guarantees in terms of bandwidth, delay and jitter, emerges as a key challenge. We first address the admission control in multi-hop cognitive radio networks. We show that for this type of networks there is no algorithm capable of estimating the available end-to-end bandwidth in a distributed fashion. Therefore, we fill the gap by introducing a polynomial time algorithm that lands itself to a distributed implementation. Then, we focus on routing and propose a new metric that takes into account the specifics of such networks. Using empirical data from a USRP testbed we show that ETX, the de facto standard metric for wireless networks, fails in the cognitive radio context. Therefore, we revisit ETX by considering the effects of primary user activity and the implications of the principle of access while doing no harm. Finally, as quality of service requirements can be expressed using multiple metrics, we turn our attention to multi-constrained quality of service routing. With the underlying problem being NP-complete, we review the proposed heuristics and approximation algorithms. Our research reveals a trade-off between utilizing theoretically-proven but computably expensive algorithms and solutions that are fast but have poor worstcase bounds. To test the feasibility of solving multi-constrained routing in practice, we implement on a real testbed low complexity algorithms that extend the Dijkstra’s shortest path algorithm. We show that these algorithms can be incorporated in link state routing protocols, such as OSPF and OLSR. While these solutions suffer from poor worst-case performance bounds, in practice, they lead to satisfactory results when compared to exact but non tractable solutions.

The unprecedented success of wireless telecommunication systems has resulted in the wireless spectrum becoming a scarce resource. At the same time, extensive measurements conducted in the early 2000’s have shown that a significant part of the licensed spectrum, for instance that dedicated to TV broadcast services, is under-utilized. Cognitive Radio systems have been proposed as the enabling technology allowing unlicensed equipments, referred to as secondary users, to opportunistically access the licensed spectrum when not in use by the licensed users, referred to as primary users. Obviously, changing decades-old policies on spectrum access in the civilian and military domain will not happen overnight and many issues, technological and legal, will have to be ironed out first. However, the fundamental principle that we expect to underlie all solutions is that of access while doing no harm – secondary users should not interfere with primary users. The focus of this thesis is on heterogeneous tactical networks deploying cognitive radios in parts or in their entirety. Such networks can be organized in multiple sub-networks, each characterized by a specific topology, medium access scheme and spectrum access policy. As a result, providing end-to-end Quality of Service guarantees in terms of bandwidth, delay and jitter, emerges as a key challenge. We first address the admission control in multi-hop cognitive radio networks. We show that for this type of networks there is no algorithm capable of estimating the available end-to-end bandwidth in a distributed fashion. Therefore, we fill the gap by introducing a polynomial time algorithm that lands itself to a distributed implementation. Then, we focus on routing and propose a new metric that takes into account the specifics of such networks. Using empirical data from a USRP testbed we show that ETX, the de facto standard metric for wireless networks, fails in the cognitive radio context. Therefore, we revisit ETX by considering the effects of primary user activity and the implications of the principle of access while doing no harm. Finally, as quality of service requirements can be expressed using multiple metrics, we turn our attention to multi-constrained quality of service routing. With the underlying problem being NP-complete, we review the proposed heuristics and approximation algorithms. Our research reveals a trade-off between utilizing theoretically-proven but computably expensive algorithms and solutions that are fast but have poor worstcase bounds. To test the feasibility of solving multi-constrained routing in practice,we implement on a real testbed low complexity algorithms that extend the Dijkstra’s shortest path algorithm. We show that these algorithms can be incorporated in link state routing protocols, such as OSPF and OLSR. While these solutions suffer from poor worst-case performance bounds, in practice, they lead to satisfactory results when compared to exact but non tractable solutions.

Delay/Doppler altimetry (DDA) aims at reducing the measurement noise and increasing the along-track resolution in comparison with conventional pulse-limited altimetry. In a previous paper, we have proposed a semi-analytical model for DDA, which considers some simplifications as the absence of mispointing antenna. This paper first proposes a new analytical expression for the flat surface impulse response (FSIR), considering antenna mispointing angles, a circular antenna pattern, no vertical speed effect, and uniform scattering. The 2-D delay/Doppler map is then obtained by a numerical computation of the convolution between the proposed analytical function, the probability density function of the heights of the specular scatterers, and the time/frequency point target response of the radar. The approximations used to obtain the semi-analytical model are analyzed, and the associated errors are quantified by analytical bounds for these errors. The second contribution of this paper concerns the estimation of the parameters associated with the multilook semi-analytical model. Two estimation strategies based on the least squares procedure are proposed. The proposed model and algorithms are validated on both synthetic and real waveforms. The obtained results are very promising and show the accuracy of this generalized model with respect to the previous model assuming zero antenna mispointing.

We consider the problem of estimating the absolute phase of a noisy signal when this latter consists of correlated dual-frequency measurements. This scenario may arise in many application areas such as global navigation satellite system (GNSS). In this paper, we assume a slow varying phase and propose accordingly a Bayesian filtering technique that makes use of the frequency diversity. More specifically, the method results from a variational Bayes approximation and belongs to the class of nonlinear filters. Numerical simulations are performed to assess the performance of the tracking technique especially in terms of mean square error and cycle-slip rate. Comparison with a more conventional approach, namely a Gaussian sum estimator, shows substantial improvements when the signal-to-noise ratio and/or the correlation of the measurements are low.

In this paper, we assess the potential of several forms of the postcoherent differential detectors for the detection of weak Global Navigation Satellite Systems (GNSS) signals. We analyze in detail two different detector forms, namely the pairwise differential (PWD) and noncoherent differential (NCDD) detectors. First, we follow a novel approach to obtain analytic expressions to characterize statistically the PWD detector. Then, we use these results to propose a polynomial-like model fitted by simulation to the sensitivity loss experienced by the differential operation with respect to coherent summing. This sensitivity loss formulai s also used to characterize the NCDD detector, shown to be more adequate than the PWD for the acquisition of GNSS signals. A comparison between the PWD, NCDD and the traditional noncoherent detector (NCD) is also carried in this study. The results highlight the superior performance of the NCDD over the NCD for the acquisition of weak signals. For the case of the PWD, its performance is sensitive to Doppler shift. The conclusions drawn from the simulation results are confirmed in the acquisition of real GPS L1 C/A signals.

A statistical model for detecting changes in remote sensing images has recently been proposed in (Prendes et al., 2014, 2015). This model is sufficiently general to be used for homogeneous images acquired by the same kind of sensors (e.g., two optical images from Pléiades satellites, possibly with different acquisition conditions), and for heterogeneous images acquired by different sensors (e.g., an optical image acquired from a Pléiades satellite and a synthetic aperture radar (SAR) image acquired from a TerraSAR-X satellite). This model assumes that each pixel is distributed according to a mixture of distributions depending on the noise properties and on the sensor intensity responses to the actual scene. The parameters of the resulting statistical model can be estimated by using the classical expectation-maximization algorithm. The estimated parameters are finally used to learn the relationships between the images of interest, via a manifold learning strategy. These relationships are relevant for many image processing applications, particularly those requiring a similarity measure (e.g., image change detection and image registration). The main objective of this paper is to evaluate the performance of a change detection method based on this manifold learning strategy initially introduced in (Prendes et al., 2014, 2015). This performance is evaluated by using results obtained with pairs of real optical images acquired from Pléiades satellites and pairs of optical and SAR images.

Global Navigation Satellite Systems (GNSS) are increasingly present in our everyday life. New users are emerging with further operational needs implying a constant evolution of the current GNSS systems. A significant part of the new applications are found in environments with difficult reception conditions such as urban areas, where there are many obstacles such as buildings or trees. Therefore, in these obstructed environments, the signal emitted by the satellite is severely degraded. The signal received by the user has suffered from attenuations, as well as refractions and diffractions, making difficult the data demodulation and the user position calculation. GNSS signals being initially designed in an open environment context, their demodulaton performance is thus generally studied in the associated AWGN propagation channel model. But nowadays, GNSS signals are also used in degraded environments. It is thus essential to provide and study their demodulation performance in the urban propagation channel models. Nevertheless, GNSS modernization with new signals design such as GPS L1C or Galileo E1 OS, takes into account these new obstructed environments constraints. Since they have been designed especially for urban propagation channels [1], they are expected to have better demodulation performance compared with current GNSS signals. It is thus particularly interesting to firstly provide their demodulation performance in urban environments (not available in the literature) and secondly to compare it with the new GNSS signal designed in this PhD research context. In this way, their performance could be used as a benchmark for the future signals design. However these modernized signals are not yet available for this moment (for example, GPS L1C is expected to be operational over the entire constellation in 2026). It is thus essential to provide and study their demodulation performance in urban environments through simulations. It is in this context that this PhD thesis is related, the final goal being to improve GNSS signals demodulation performance in urban areas, proposing a new signal. In order to be able to provide and study GNSS signals demodulation performance in urban environments, a simulation tool has been developed : SiGMeP for "Simulator for GNSS Message Performance". It allows simulating the entire emission/reception GNSS signal chain in urban environment getting away from dependence of real signals availability, controlling the simulation parameters and testing new configurations. Existing and modernized signals demodulation performance has thus been computed with SiGMeP in urban environments. Since the classical way to compute and represent GNSS signals demodulation performance assumes an AWGN propagation channel model, and since the urban environments are really different from the AWGN channel, this classical method is not satisfactory in our urban context. Thus, in order to represent GNSS signals demodulation performance faithfully to reality, a new methodology more adapted to the user environment is proposed. It is based on the fundamental characteristics of a GNSS system, as well as on the urban environment impact on the received signal analysis. GNSS signals demodulation performance is thus provided in urban environments thanks to this new methodology, and compared with the classic methodology used in the AWGN case. Then, to improve GNSS signals demodulation performance in urban environments, many strategies are possible. However, the research axis on this thesis focuses on the "Channel Coding" aspect. It is thus this field which will be privileged to improve GNSS signals demodulation performance in urban environments. Each message, in addition to containing the useful information, carries redundant informaton, which is in fact the channel coding result, applying to the useful information. The message thus needs to be decoded at the reception. In order to decode the transmitted useful information, the receiver computes a detection function at the decoder imput. But the detection function used in classic receivers correspond to an AWGN propagation channel. This dissertation thus proposes an advanced detection function which is adapting to the propagation channel where the user is moving. This advanced detection function computation considerably improves demodulation performance, just in modifying the receiver part system. Finally, in order to design a new signal with better demodulation performance in urban environments than one of existing and future signals, a new LDPC channel code profile has been proposed, optimizing for a CSK modulation in an AWGN channel for iterative decoding. Indeed, the CSK modulation is a promising modulation in the spread signals world, which permits to free from limitations in terms of data rate implied by current GNSS signals modulations. Moreover, LDPC codes belong to the modern codes family, the first being able to approach the channel capacity.They thus represent promising achievable performance.

Global Navigation Satellite Systems (GNSS) are increasingly present in our everyday life. New users are emerging with further operational needs implying a constant evolution of the current GNSS systems. A significant part of the new applications are found in environments with difficult reception conditions such as urban areas, where there are many obstacles such as buildings or trees. Therefore, in these obstructed environments, the signal emitted by the satellite is severely degraded. The signal received by the user has suffered from attenuations, as well as refractions and diffractions, making difficult the data demodulation and the user position calculation. GNSS signals being initially designed in an open environment context, their demodulaton performance is thus generally studied in the associated AWGN propagation channel model. But nowadays, GNSS signals are also used in degraded environments. It is thus essential to provide and study their demodulation performance in the urban propagation channel models. Nevertheless, GNSS modernization with new signals design such as GPS L1C or Galileo E1 OS, takes into account these new obstructed environments constraints. Since they have been designed especially for urban propagation channels [1], they are expected to have better demodulation performance compared with current GNSS signals. It is thus particularly interesting to firstly provide their demodulation performance in urban environments (not available in the literature) and secondly to compare it with the new GNSS signal designed in this PhD research context. In this way, their performance could be used as a benchmark for the future signals design. However these modernized signals are not yet available for this moment (for example, GPS L1C is expected to be operational over the entire constellation in 2026). It is thus essential to provide and study their demodulation performance in urban environments through simulations. It is in this context that this PhD thesis is related, the final goal being to improve GNSS signals demodulation performance in urban areas, proposing a new signal. In order to be able to provide and study GNSS signals demodulation performance in urban environments, a simulation tool has been developed : SiGMeP for "Simulator for GNSS Message Performance". It allows simulating the entire emission/reception GNSS signal chain in urban environment getting away from dependence of real signals availability, controlling the simulation parameters and testing new configurations. Existing and modernized signals demodulation performance has thus been computed with SiGMeP in urban environments. Since the classical way to compute and represent GNSS signals demodulation performance assumes an AWGN propagation channel model, and since the urban environments are really different from the AWGN channel, this classical method is not satisfactory in our urban context. Thus, in order to represent GNSS signals demodulation performance faithfully to reality, a new methodology more adapted to the user environment is proposed. It is based on the fundamental characteristics of a GNSS system, as well as on the urban environment impact on the received signal analysis. GNSS signals demodulation performance is thus provided in urban environments thanks to this new methodology, and compared with the classic methodology used in the AWGN case. Then, to improve GNSS signals demodulation performance in urban environments, many strategies are possible. However, the research axis on this thesis focuses on the "Channel Coding" aspect. It is thus this field which will be privileged to improve GNSS signals demodulation performance in urban environments. Each message, in addition to containing the useful information, carries redundant informaton, which is in fact the channel coding result, applying to the useful information. The message thus needs to be decoded at the reception. In order to decode the transmitted useful information, the receiver computes a detection function at the decoder imput. But the detection function used in classic receivers correspond to an AWGN propagation channel. This dissertation thus proposes an advanced detection function which is adapting to the propagation channel where the user is moving. This advanced detection function computation considerably improves demodulation performance, just in modifying the receiver part system. Finally, in order to design a new signal with better demodulation performance in urban environments than one of existing and future signals, a new LDPC channel code profile has been proposed, optimizing for a CSK modulation in an AWGN channel for iterative decoding. Indeed, the CSK modulation is a promising modulation in the spread signals world, which permits to free from limitations in terms of data rate implied by current GNSS signals modulations. Moreover, LDPC codes belong to the modern codes family, the first being able to approach the channel capacity.They thus represent promising achievable performance.