Most nonlinear behavioural models of amplifiers are based on functions that are analytic at the origin and thus can be replaced by their Taylor series development around this point, e.g. polynomials of the input signal. Chebyshev Transforms can be used to compute the harmonic response of the model to a sine input signal. These responses are polynomials of the input signal amplitude. A second application of the Chebyshev transform to the first harmonic response or RF characteristic will lend the carriers and intermodulation (IM) products for a 2-carrier input signal, again polynomials. An important class of non-analytic nonlinear behaviour encountered in practice, such as hard limiters and detectors are either empirically treated or only approximated by an analytic function such as the hyperbolic tangent. This work proposes to generalize the polynomial nonlinearity theory by adding non-analytic at the origin functions that, like polynomials, are invariant elements of the Chebyshev Transform. Devices modelled with these non-analytic at the origin functions exhibit intermodulation behaviour significantly different from that of classical polynomial models, giving theoretical foundation to a number of important unexplained practical measurement observations.

This paper describes existing and new criteria for comparison and optimization of non-linear power amplifiers such as RF or microwave transmitters. In addition to intermodulation, receiver noise, and losses in the transmission system, the proposed new criteria take into account efficiency or consumed power. This results in the global optimization of a combined signal-to-noise-plus-intermodulation ratio as a function of saturated or nominal power but also consumed or dissipated power. Saturated power is limited by available technology. Consumed power and dissipated power are some of the main constraints in telecommunication satellite payloads, mobile phone handsets, and RFID (Radio Frequency IDentification). Another constraint comes from the limited size of antennas, which limits the system equivalent isotropic radiated power and gain-to-temperature ratio. With the proposed criteria the designer will be able to compare different amplifier technologies and to optimize the design and operating point of each stage of a multistage amplifier or a linearizer for a given amplifier. Interference from same or other systems is also introduced in the optimization through the use of signal-to-noise-plus-IM-plus-interference ratio criteria.

EVM (Error Vector Measurement) is used to measure the end-to-end quality of digital communication links. It comes from noise, linear and non-linear distortion, and interference if any. I propose a method to discriminate between random noise that is independent of the signal and distortion that depends on the signal. Interference is more complex to discriminate as it is not random but can be either synchronous with the signal or not. Echoes such as multipath cause linear distortion if they are static. However, variable echoes, such as those created in a reverberation chamber must be treated specifically.

Low-frequency radio interferometry is crucial to understanding the universe and its very early days. Unfortunately, most of the current instruments are ground-based and thus impacted by the interferences massively produced by the Earth. To alleviate this issue, scientific missions aim at using Moonorbiting nano-satellite swarms as distributed radio-telescopes in outer space, keeping them out of Earth interference range. However, swarms of nano-satellites are systems with complex dynamics and need to be appropriately characterized to achieve their scientific mission. This paper presents a methodology based on graph theory for characterizing the swarm network system by computing graph theory metrics around three properties: the node density, network connectivity and ISL availability. We show that these properties are well-suited for highlighting a possible heterogeneity in a network and adapt a routing strategy accordingly. This work is the first milestone in defining the best-suited routing strategy within the swarm from the derived network properties.

We address the problem of partitioning a network of nano-satellites to distribute fairly the network load under energy consumption constraints. The study takes place in a context where this swarm of nano-satellites orbits the Moon and works as, but not limited to, a distributed radio-telescope for low-frequency radio interferometry. During an interferometry mission, each nano-satellite collects observation data, then shares them with the other swarm members to compute a global image of space. However, the simultaneous transmission of large volumes of data can cause communication issues by overloading the radio channel, leading to potential packet loss. In this context, we investigate three division algorithms based on graph sampling techniques. We prove that random walk-based algorithms overall perform the best in terms of conservation of graph properties and fairness for group sizes down to 10% of the original graph.

The exponential increase in the number of satellites along with the hazards of the space environment they encounter endangers the sustainability of low earth orbit (LEO). The consequences of events such as collisions, fragmentations and fatal failures are then becoming more than ever a threat to any kind of space activity. Therefore, the space situational awareness is of utter importance in all its aspects, i.e., assessing and predicting the risks from space weather and SST (Space Surveillance and Tracking), in addition to implementing mitigation measures. In this context, this paper covers the benefits of in-orbit inspection combined with the aggregation and processing of existing space data, proposed by the French company SpaceAble for low earth orbit sustainability. Collision risk awareness for a LEO constellation is raised in this paper through the analysis of the conjunction risks of the Starlink constellation. An inspection plan is also derived in terms of the number of inspections for different scenarios, and with respect to different LEO altitudes.

In this paper, we propose hybrid GaN-FDSOI Front-End-Modules (FEMs) combined with lens-based mmWave antenna modules for energy-efficient multi-beamforming systems. X-topology Lattice-based balanced (LB) and unbalanced (LU) differential switches are designed and fabricated using FDSOI platforms for building scalable multi-beamforming FEMs. Unified mmWave and Baseband correlation technologies based on energy density and EVM (Error Vector Magnitude) metrics are introduced for low complexity (leveraging sparsity of MIMO channels) cost-effective multi-beamforming systems. Combination of convolutional accelerators with analog signal processing for linking beam-selection algorithms to stochastic-wave-shaping (SWS) will create new paradigms for eliminating the concept of “elements” in arrays and replacing it by the vision of “radiating current flows” over a textured surface (metasurface or metavolume). The radiating metasurfaces or metavolumes which can be conformal to the patterned optical lenses are fed by a limited number of emitting/receiving points. The use of time-modulated correlation functions will foster new system architectures with critical functionalities including direction of arrival (DOA) estimation and secure communications.