. L'histoire, Évolution des Communications Sans Fil La communication sans fil [2]-[5] est communément considérée comme le transfert électromagnétique d'informations entre des points qui ne sont pas connectés par un conducteur électrique, vol.6

É. Le-transfert, Marconi a mis en place un télégraphe sans fil et breveté un système sans fil complet en 1897. Avec le développement des circuits intégrés, la communication sans fil électromagnétique s'est développée rapidement à mesure que la radiodiffusion et la télévision se répandaient dans le monde entier. Les systèmes sans fil sont passés de la transmission de signaux analogiques à la transmission de signaux numériques composés de bits, Maxwell a postulé la transmission des ondes électromagnétiques en 1864, puis Heinrich Hertz l'a vérifiée et démontrée en 1880 et 1887, respectivement, 1980.

, Depuis les années 1980, l'évolution des systèmes sans fil mobiles progresse d'une génération à l'autre tous les dix ans environ. Chaque génération présente une réglementation

, Les réseaux 5G sont censés prendre en charge un grand nombre et une grande hétérogénéité des terminaux, c'est-à-dire l

, Les trois principaux cas d'utilisation visés par la 5G sont les communications mobiles à large bande améliorées (eMBB), les communications ultra-fiables à faible latence (URLLC) et les communications massives de type machine (mMTC), vol.13

, Les réseaux 5G ont été testés dans de nombreux pays et en sont maintenant aux premiers stades du déploiement commercial, vol.14

, Entre-temps, les activités de recherche vers la sixième génération (6G) ont été lancées. Bien que l'on ne sache pas exactement ce que sera la 6G, de nombreuses visions (spéculatives) pour la 6G ont été fournies sous différents angles

A. , Propagation Sans Fil Les ondes électromagnétiques sont émises par une antenne au niveau de l'émetteur, se propagent à travers un canal sans fil et sont interceptées par une antenne au niveau du récepteur, En principe, on pourrait résoudre les équations du champ électromagnétique En supposant d'évanouissement Rayleigh IID, ils ont montré deux résultats importants comme suit

, Pour l'évanouissement rapide (T = 1), ils ont montré que la capacité totale pour K > 1 utilisateurs est égale à la capacité pour K = 1 utilisateur, donc l'accès multiple par répartition dans le temps (TDMA) est optimal. Pour l'évanouissement par bloc (T > 1), ils ont supposé que la capacité de somme maximale ne peut être atteinte que par plus de K = T utilisateurs, ce qui est soutenu par une analyse asymptotique, A.2.3.a Limites Fondamentales Shamai et Marzetta ont étudié la capacité du MAC à entrée unique et sorties multiples (SIMO) (M k = 1, k ? [K]) dans l'évanouissement Rayleigh IID dans, vol.84

, Étant donné que la capacité de somme du MAC peut être supérieure par la capacité du canal P2P en permettant la coopération de l'utilisateur, la capacité de somme du MAC sous l'évanouissement rapide peut être montrée à l'échelle comme un double logarithme du SNR plus un nombre d'évanouissement. Le nombre décroissant de le MAC à entrées multiples sortie unique (MISO) dans l'évanouissement Ricienne a été dérivé par Lin et Moser dans, Devassy et al. fourni des limites supérieures et inférieures non asymptotiques sur la capacité de somme du MAC MIMO sous l'évanouissement, vol.86

C. Dans-ce,

, Une région DoF réalisable pour le MAC MIMO à deux utilisateurs sous l'évanouissement Rayleigh IID a été proposée dans [88] en utilisant une approche géométrique, Les travaux susmentionnés portent sur la capacité totale du MAC non-cohérent. La région de pleine capacité est inconnue et seules quelques régions réalisables du DoF ont été proposées, vol.37

T. Dans-cette, nous étudierons la région DoF optimale du MAC non-cohérent et répondrons à la question ouverte suivante

, Quelle est la région DoF optimale pour le MAC MIMO non-cohérent dans l'évanouissement générique par bloc?

, Comme dans le cas d'un utilisateur unique (P2P), les signaux transmis X X X k de l'utilisateur k sont normalement tirés d'une constellation discrète finie X k , donc X := {

X. ,

M. X-x-x-k-?-x-k-,-k-?-[k]}-est-la-constellation-conjointe-du, Une extension simple du schéma pilote pour le cas d'un utilisateur unique consiste à diviser le bloc cohérent en deux parties: 1) la partie d'apprentissage dans laquelle des séquences pilotes mutuellement orthogonales sont envoyées pour estimer le CSI pour chaque utilisateur, et 2) le partie de transmission de données dans laquelle différents utilisateurs communiquent simultanément [89] en utilisant une constellation scalaire (par exemple, PAM, QAM, PSK). L'optimalité de cette approche en termes de taux réalisable et d'erreur de détection reste incertaine. De plus

, Dans le canal à évanouissement par blocs (un mot de code de canal s'étend sur plusieurs, mais un nombre fini, de blocs de cohérence), des limites non asymptotiques pour le débit de codage maximal non-cohérent ont été présentées pour le cas SISO dans, vol.219

, Un schéma de communication non-cohérent dans lequel les informations sont modulées sur les zéros de la transformée z du signal de bande de base transmis a été proposé pour la communication par paquets courts dans, vol.221

, ? Communication de type machine non-cohérente et accès aléatoire massif : Dans la communication de type machine et l'accès aléatoire massif, le système doit prendre en charge un très grand nombre d'utilisateurs et seul un sous-ensemble aléatoire d'entre eux est actif à la fois. L'ensemble des utilisateurs actifs peut ne pas être connu à l'avance et il est impossible de pré-affecter des pilotes mutuellement orthogonaux à chaque utilisateur. Par conséquent, une communication sans pilote non-cohérente peut être une stratégie appropriée. Un protocole d'accès aléatoire non-cohérent basé sur des trames de Gabor

;. Dans and . Senel, Comparé à une transmission cohérente, ce schéma non-cohérent fonctionne nettement mieux, surtout lorsque le nombre de bits est petit. Récemment, notre constellation cube-split a été utilisée pour construire un schéma d'accès aléatoire massif basé

, en particulier l'apprentissage en profondeur, dans les communications sans fil se développe rapidement et profondément dans de nombreux aspects des communications de la couche physique, de l'utilisation de l'apprentissage pour une tâche spécifique telle que l'estimation de canal, l'égaliseur de symboles, détection de signal, codage / décodage de canal, vers une transmission complète basée sur l'apprentissage de bout en bout, ? Apprentissage automatique pour les communications non-cohérentes : L'utilisation de l'apprentissage automatique, vol.228

. Par-exemple and . Du, utilisé des algorithmes de regroupement de données sur la variété Grassmann pour concevoir un schéma de reconnaissance de modulation automatique pour les constellations Grassmanniennes dans, vol.230

, Dans l'apprentissage de bout en bout des systèmes de communication via des auto-encodeurs basés sur un réseau de neurones, l'estimation de canal peut être effectuée même avec un modèle de canal inconnu, vol.231

, Lorsque le modèle de canal est inconnu, on peut utiliser l'apprentissage basé sur les données pour ajuster la probabilité conditionnelle d'entréesortie empirique à un modèle paramétrique. Nous avons proposé un cadre utilisant un modèle gaussien généralisé à cette fin dans, vol.130

, Un autoencodeur pour une communication basée sur l'énergie non-cohérente dans un système SIMO multi-porteuses multi-utilisateurs a été proposé dans, vol.232

, L'article [233] présente la conception de formes d'ondes pour les systèmes MIMO multi-utilisateurs non-cohérents grâce à l'apprentissage en profondeur

K. Ngo, S. Yang, and M. Guillaud, The optimal degrees of freedom for the point-to-point and multiple-access channels in generic block fading, IEEE Trans. Inf. Theory, 2020.

K. Ngo, S. Yang, M. Guillaud, and A. Decurninge, Joint constellation design for the noncoherent MIMO multiple-access channel, IEEE Trans. Wireless Commun, 2020.

F. Zhang, K. Ngo, S. Yang, and A. Nosratinia, Transmit correlation diversity: Generalization, new techniques, and improved bounds, IEEE Trans. Inf. Theory, 2020.

K. Ngo, M. Guillaud, A. Decurninge, S. Yang, and P. Schniter, Multi-user detection based on expectation propagation for the noncoherent SIMO multiple access channel, IEEE Trans. Wireless Commun, 2020.

K. Ngo, A. Decurninge, M. Guillaud, and S. Yang, Cube-split: A structured Grassmannian constellation for noncoherent SIMO communications, IEEE Trans. Wireless Commun, vol.19, issue.3, pp.1948-1964, 2020.

, Préimpression

K. Ngo, S. Yang, M. Guillaud, and A. Decurninge, Joint constellation design for the two-user noncoherent multiple-access channel, 2020.

K. Ngo, M. Guillaud, A. Decurninge, S. Yang, S. Sarkar et al., Noncoherent multi-user detection based on expectation propagation, 53rd Asilomar Conference on Signals, Systems, and Computers, 2019.

K. Ngo, A. Decurninge, M. Guillaud, and S. Yang, A multiple access scheme for noncoherent SIMO communications, 52nd Asilomar Conference on Signals, Systems, and Computers, pp.1846-1850, 2018.

K. Ngo, S. Yang, and M. Guillaud, The optimal DoF region for the two-user noncoherent SIMO multiple-access channel, IEEE Information Theory Workshop (ITW), 2018.

K. Ngo, S. Yang, and M. Guillaud, An achievable DoF region for the two-user noncoherent MIMO broadcast channel with statistical CSI, IEEE Information Theory Workshop (ITW), pp.604-608, 2017.

K. Ngo, A. Decurninge, M. Guillaud, and S. Yang, Design and analysis of a practical codebook for noncoherent communications, 51st Asilomar Conference on Signals, Systems, and Computers, pp.1237-1241, 2017.

K. Ngo, A. Decurninge, M. Guillaud, and S. Yang, Transmitter and receiver communication apparatus for noncoherent communication, 2018.

. Au-cours-de-la-thèse, nous avons également publié quelques autres contributions qui ne sont pas incluses dans le résultat principal de cette thèse

K. Ngo, S. Yang, and M. Guillaud, Generalized Gaussian model for data-driven learning in communications, International Zurich Seminar on Information and Communication (IZS), poster, 2020.

K. Ngo, S. Yang, and M. Kobayashi, Scalable content delivery with coded caching in multi-antenna fading channels, IEEE Trans. Wireless Commun, vol.17, issue.1, pp.548-562, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01656408

A. Ghorbel, K. Ngo, R. Combes, M. Kobayashi, and S. Yang, Opportunistic content delivery in fading broadcast channels, IEEE Global Communications Conference (GLOBECOM ), 2017.
URL : https://hal.archives-ouvertes.fr/hal-01568780

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S. Xue, Y. Ma, N. Yi, and R. Tafazolli, On deep learning solutions for joint transmitter and noncoherent receiver design in MU-MIMO systems, About the Author Khac-Hoang NGO, 2020.

, France Email: khachoang.ngo@supelec.fr Homepage: sites.google.com/site/khachoangngo Education 2017 -2020 Ph.D., Wireless Communications, 2010.

, Global Young Vietnamese Scholars Forum, 2019.

, Participant, 7th Heidelberg Laureate Forum, 2019.

, Scientific Committee Member, Junior Conference on Wireless and Optical Communications, 2015.

, 2017 -now Reviewer for IEEE Journals and Conferences 2019 -now Copyeditor, ICT Research Journal, Vietnam Ministry of Information and Communications Honors, 2016.

, Univ. Paris-Saclay scholarship for international master students 2014 Graduate with first-class honors, UET, VNU 2013 Honda Young Engineers and Scientists Award in, 2015.