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Cognitive radio (CR) is the solution to the spectrum scarcity issue faced in wireless communications. It allows unlicensed secondary users (SUs) to opportunistically access the spectrum assigned to licensed primary users (PUs), but unused, on a non-interfering basis. Spectrum sensing is the process by which the CR node becomes aware of the spectrum occupancy, in order to decide which frequency bands to use. In the first part of this thesis, we consider the Bayesian changepoint detection theory to propose a new spectrum sensing algorithm that exploits the mobility of the SU and works for practical scenarios where the PU’s signal power is unknown to the SU. Simulation results show that the derived algorithm is a good choice when the SU could be required to detect very low signal-to-noise ratio (SNR) signals. In the second part, we introduce a new framework for joint transmission and sensing in mobile CR, by using changepoint detection for spectrum sensing. The optimal system parameters (sensing time, transmission time and detection threshold) that maximize the spectrum utilization are numerically computed and analyzed. In the last part, a new spectrum sensing algorithm, that exploits geolocation information about existing PUs by using the Bayesian block-based detection theory, is introduced. An approximate closed-form expression, based on Taylor series expansion, is provided. Numerical results show that the derived algorithm gives the minimum error probability when compared with an algorithm that does not use geolocation information., (FSA - Sciences de l'ingénieur) -- UCL, 2022

Conducted disturbances in the frequency range 2-150 kHz have gained more interest over the last few years due to the evolution of the power grid. The traditional low frequency harmonics are indeed replaced by emissions in this frequency range due to the technological evolution towards self-commutating topologies. Furthermore, Power Line Communication is one of the chosen options as a means of communication for smart metering infrastructures. This technology uses the power network and works in the same frequency range, i.e. 2-150 kHz. At the same time, the standardization on this issue is still incomplete. This thesis brings a contribution towards a better understanding of this kind of electromagnetic compatibility issue. This work adopts a theoretical approach for the development of the required models of the disturbing devices and the grid. The two main categories of disturbing devices have been modelled. First, self-commutated inverters, such as those met in solar panels or in wind turbines, are considered. Both single-phase and three-phase configurations are investigated. The other category concerns rectifiers with Active Power Factor Correction as in Compact Fluorescent Lamps or in some electric vehicle chargers. The obtained models offer an interesting compromise between accuracy and simplicity. The low voltage grid model consists of several elements in series where each element is in turn represented by three chain matrices for the positive, negative and zero sequence components. Finally, the thesis provides an accurate method to study theoretically the propagation of one or several disturbances in that frequency range., (FSA - Sciences de l'ingénieur) -- UCL, 2021

Passive coherent location (PCL) radars employ illuminators of opportunity to detect and track targets. This silent operating mode provides many advantages such as low cost and interception immunity. Many radiation sources have been exploited as illumination sources such as broadcasting and telecommunication transmitters. The classical architecture of the bistatic PCL radars involves two receiving channels: a reference channel and a surveillance channel. The reference channel captures the direct-path signal from the transmitter, and the surveillancesignal collects the possible target echoes. The two major challenges for the PCL radars are the reference signal noise and the surveillance signal static clutter. A noisy reference signal degrades the detection probability by increasing the noise-floor level of the detection filter output. And the static clutter presence in the surveillance signal reduces the detector dynamic range and buries low magnitude echoes.In this thesis, we consider a PCL radar based on the digital video broadcasting-terrestrial (DVB-T) signals, and we propose a set of improved methods to deal with the reference signal noise and the static clutter in the surveillance signal. The DVB-T signals constitute an excellentcandidate as an illumination source for PCL radars; they are characterized by a wide bandwidth and a high radiated power. In addition, they provide the possibility of reconstructing the reference signal to enhance its quality, and they allow a straightforward static clutter suppressionin the frequency domain. This thesis proposes an optimum method for the reference signal reconstruction and an improved method for the static clutter suppression.The optimum reference signal reconstruction minimizes the mean square error between the reconstructed signal and the exact one. And the improved static clutter suppression method exploits the possibility of estimating the propagation channel. These two methods extend thefeasibility of a single rece, Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished

Satellite communication system designers are continuously struggling to improve the channel capacity. A critical challenge results from the limited power available aboard the satellite.Because of this constraint, the onboard power amplifier must work with a small power supply which limits its maximum output power. To ensure a sufficient Signal-to-Noise power Ratio (SNR) on the receiver side, the power amplifier must work close to its saturation point. This is power efficient but unfortunately adds non-linear distortions to the communication channel. The latters are very penalizing for high order modulations.In the literature, several equalization algorithms have been proposed to cope with the resulting non-linear communication channel. The most popular solution consists in using baseband Volterra series in order to build non-linear equalization filters. On the other hand, the Recurrent Neural Networks (RNNs), which come from the artificial neural network field, are also interesting candidates to generate such non-linear filters. But they are difficult to implement in practice due to the high complexity of their training. To simplify this task, the Echo State Network (ESN) paradigm has been proposed. It has the advantage of offering performances similar to classical RNNs but with a reduced complexity.The purpose of this work is, first, to compare this solution to the state-of-the-art baseband Volterra filters. We show that the classical ESN is able to reach the same performances, evaluated in terms of Bit Error Rate (BER), and has similar complexity. Secondly, we propose a new design for the ESN which achieves a strong reduction in complexity while conserving a similar BER.To compensate for the channel, the literature proposes to adapt the coefficients of these equalizers with the help of a training sequence in order to recover the transmitted constellation points. We show that, in such a case, the usual symbol detection criterion, based on Euclidean distances, is no, Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished