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            <title xml:lang="en">Study and design of codebooks for medium and high mobility millimetric communications systems</title>
            <title xml:lang="fr">Etude et conception de codebooks pour les systèmes de communications millimétriques à moyenne et grande mobilité</title>
            <title xml:lang="en" type="sub">applications to high-speed trains</title>
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                <term xml:lang="en">MIMO</term>
                <term xml:lang="en">Railways</term>
                <term xml:lang="en">High speed trains</term>
                <term xml:lang="en">Millimetric communications</term>
                <term xml:lang="fr">MIMO</term>
                <term xml:lang="fr">Ferroviaires</term>
                <term xml:lang="fr">trains à grande vitesse</term>
                <term xml:lang="fr">Communications millimétriques</term>
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              <p>The revolution in railway communication systems is underway, driven by the need forfaster, more reliable communication networks that can support the high-speed demandsof modern trains. At the heart of this transformation are millimeter-wave (mmWave)communication systems, which promise unprecedented data rates, ultra-low latency, andenhanced connectivity for dynamic environments like high-speed railways. This thesisexplores the pivotal role of mmWave technologies, MIMO architectures, and advancedbeamforming techniques in addressing the unique challenges of high-speed train communications, while also shaping the future of next-generation wireless networks. The workbegins by tracing the evolution of wireless communication, from 1G to 5G and beyond(B5G), and highlights how mmWave systems will play a central role in the transition toB5G/6Gnetworks. Special attention is given to the integration of these systems in the Future Railway Mobile Communication System (FRMCS), which seeks to enable seamless,high-performance connectivity for trains, passengers, and infrastructure. Focusing onbeamforming techniques, the research introduces predefined codebook-based approaches tailored to the dynamic conditions of railway environments. Through detailed simulations, the study examines how beam selection strategies impact system performance, showcasing how these methods can improve communication reliability and efficiency for high-speed trains. Building upon this, the thesis explores the integration of machine learning (ML) to enable smart beam prediction. Using ML algorithms like neural networks and support vector machines, a novel, adaptive beamforming solution is proposed, offering enhanced beam accuracy and improved spectral efficiency in real-time dynamic environments. Further advancing the technology, the thesis introduces a vision-aided 3D codebook design for beam tracking in Train-to-Infrastructure (T2I) communication systems. By leveraging location and visual data, this innovative method improves beam alignment, ensuring robust communication even over long distances between base stations and fast-moving trains. Simulation results validate the performance gains of this approach, particularly in line-of-sight (LoS) communication scenarios. The integration of artificial intelligence (AI) into hybrid beamforming techniques is also explored, offering an AI-driven approach to RF beam prediction and baseband precoding. This cutting edge technology promises to enhance communication efficiency, scalability, and reliability, addressing the growing needs of high-speed, complex communication networks. In conclusion, this thesis demonstrates how mmWave communication systems, coupled with advanced beamforming and AI techniques, are poised to revolutionize railway communication. The findings provide a roadmap for enhancing connectivity and performance in high-speed transportation systems, while laying the groundwork for future breakthroughs in B5G/6G wireless networks</p>
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              <p>La révolution des systèmes de communication ferroviaire est en cours, alimentée par le besoin de réseaux de communication plus rapides et plus fiables capables de répondre aux exigences de haute vitesse des trains modernes. Au cœur de cette transformation se trouvent les systèmes de communication à ondes millimétriques (mmWave), qui promettent des débits de données inédits, une latence ultra-faible et une connectivité améliorée pour des environnements dynamiques comme les chemins de fer à grande vitesse. Cette thèse explore le rôle clé des technologies mmWave, des architectures MIMO et des techniques avancées de formation de faisceau pour relever les défis uniques des communications dans les trains à grande vitesse, tout en façonnant l’avenir des réseaux sans fil de prochaine génération. Le travail commence par retracer l'évolution des communications sans fil, de la 1G à la 5G et au-delà, en mettant en évidence la manière dont les systèmes mmWave joueront un rôle central dans la transition vers les réseaux B5G/6G. Une attention particulière est portée à l’intégration de ces systèmes dans le Future Railway Mobile Communication System (FRMCS), qui vise à permettre une connectivité transparente et haute performance pour les trains, les passagers et les infrastructures.</p>
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