User Association and Load Balancing for Massive MIMO through Deep Learning

This work investigates the use of deep learning to perform user cell association for sum-rate maximization in Massive MIMO networks. It is shown how a deep neural network can be trained to approach the optimal association rule with a much more limited computational complexity, thus enabling to update the association rule in real-time, on the basis of the mobility patterns of users. In particular, the proposed neural network design requires as input only the users' geographical positions. Numerical results show that it guarantees the same performance of traditional optimization-oriented methods

A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication

Annulation des interférences inter-cellulaires pour les systèmes MIMO massif dans les réseaux hétérogènes 5G

De nos jours, le nombre des utilisateurs mobiles est en train d’exploser et cela va de même pour la demande en débit. En effet, cette demande croissante ainsi que le nombre considérable d’appareils qui sont appelés à être connectés (plus de 29 milliards d’ici 2022 selon Ericsson) oblige à entièrement repenser les technologies de communication mobile. De nouveaux systèmes doivent être développés afin de proposer une solution aux nouveaux usages qui vont naître de cette évolution. Le MIMO massif est une nouvelle technologie caractéristique de la 5G. Au lieu de mettre en place une seule antenne réceptrice-émettrice, le MIMO massif combine plusieurs antennes à la fois afin de renforcer le signal et réduire les interférences. Un tel système est très souvent étudié pour des transmissions multi-utilisateurs grâce à son potentiel à focaliser l’énergie. Parmi les nombreuses technologies caractéristiques de la 5G, nous considérons comme un bon candidat un système fonctionnant à des longueurs d’onde millimétriques afin de satisfaire le besoin du débit élevé sur des petites zones cibles. Cependant, plusieurs difficultés de conception apparaissent à une telle échelle de fréquence. Particulièrement, l’utilisation d’un nombre élevé de chaînes RF en parallèle semble plus compliquée. Pour remédier à ce problème, des systèmes dits hybrides ont vu le jour et ils sont identifiés comme des solutions pertinentes afin de contourner ces difficultés. Malgré les avantages apportés par les systèmes MIMO massifs à ondes millimétriques, il est important de comprendre ces innovations d’un point de vue d’évolution de l’architecture des réseaux. De nos jours, l’architecture moderne des réseaux cellulaires devient de plus en plus hétérogène, pour de bonnes raisons. Dans ces réseaux hétérogènes, les stations de base sont souvent augmentées avec un grand nombre de petites cellules. Ces dernières consistent en de petites stations de base, utilisées pour améliorer la couverture dans des environnements denses et pour augmenter la capacité du réseau. Cependant, plusieurs problèmes techniques naissent du déploiement dense de ces petites cellules. Particulièrement, leur coexistence avec les réseaux traditionnels et les différents niveaux de puissance de transmission peuvent être la source de fortes interférences entre les cellules. Le travail de ce mémoire se concentre sur la gestion des interférences intercellulaires dans un réseau hétérogène à spectre partagé. Ces interférences sont dues principalement au fait que les utilisateurs sont forcés de s’associer aux petites cellules en présence de macrocellules avoisinantes. Par conséquent, nous proposons une nouvelle architecture d’un réseau hétérogène comprenant plusieurs petites cellules qui coexistent avec une macrocellule équipée d’un grand nombre d’antennes au niveau de la macro station de base (MBS). L’objectif est de concevoir un nouveau schéma de précodage hybride permettant d’annuler les interférences intercellulaires sur le lien descendant (DL). Nous proposons d’appliquer uniquement un contrôle de phase pour coupler les sorties de la chaîne RF aux antennes d’émission, en utilisant des déphaseurs RF économiques. Un précodage numérique est ensuite effectué à la station de base pour gérer les interférences intercellulaires et multi-utilisateurs en s’appuyant sur l’espace nul des canaux d’interférences. Enfin, des résultats de simulations démontrant l’efficacité spectrale de l’approche proposée sont présentées et comparées avec diverses techniques de précodageNowadays, the number of mobile users and the demand for bandwidth are exploding. Indeed, this growing demand and the considerable number of devices to be connected (more than 29 billion by 2022 according to Ericsson) requires a complete rethink of the mobile communication technologies. New systems must be developed in order to provide a solution to the new uses that will emerge from this evolution. Massive MIMO is a new technology characteristic of 5G. Instead of implementing a single transmitting/receiving antenna, massive MIMO system combines several antennas to rein-force the signal and reduce the interference. Such a system is very often studied for multi-user transmissions thanks to its potential to focus energy. Among the many characteristic technologies of 5G, we consider as good candidates, those operating at millimetre wavelengths to satisfy the need for high throughput in small targeted areas. However, several design difficulties occur at such a frequency scale. In particular, the use of a large number of RF chains in parallel is more complicated. To remedy this problem, hybrid systems have emerged and are identified as relevant solutions to overcome these difficulties. Despite the benefits of massive MIMO systems and millimetre wave, it is important to understand these innovations from the perspective of network architecture evolution. Nowadays, the modern architecture of cellular networks is becoming more and more heterogeneous, for good reasons. In these heterogeneous networks, base stations are often augmented with a large number of small cells. It consists of small base stations, used to improve coverage in dense environments and increase network capacity. However, several technical problems arise from the dense deployment of these small cells. In particular, their coexistence with traditional networks and the different levels of transmission power can be the source of strong interferences between cells. In this thesis, we focus on the intercellular interference management in a heterogeneous shared spectrum network. This interference is mainly due to the fact that users are forced to be associated with small cells in the presence of surrounding macrocells. Therefore, we propose a new architecture of a heterogeneous network comprising several small cells that coexist with a macrocell equipped with a large number of antennas at the macro base station (MBS). The goal is to design a new hybrid precoding scheme to cancel intercellular interference on the downlink transmissions (DL). We propose to apply only phase control to couple the outputs of the RF chain to the transmitting antennas, using economical RF phase shifters. Digital precoding is then performed at the base station to manage intercellular and multi-user interference based on the null space of the interference channels. Finally, simulation results demonstrating the spectral efficiency of the proposed approach are presented and compared with various precoding technique

Radio Resource Management for New Application Scenarios in 5G: Optimization and Deep Learning

The fifth-generation (5G) New Radio (NR) systems are expected to support a wide range of emerging applications with diverse Quality-of-Service (QoS) requirements. New application scenarios in 5G NR include enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communications (URLLC). New wireless architectures, such as full-dimension (FD) massive multiple-input multiple-output (MIMO) and mobile edge computing (MEC) system, and new coding scheme, such as short block-length channel coding, are envisioned as enablers of QoS requirements for 5G NR applications. Resource management in these new wireless architectures is crucial in guaranteeing the QoS requirements of 5G NR systems. The traditional optimization problems, such as subcarriers and user association, are usually non-convex or Non-deterministic Polynomial-time (NP)-hard. It is time-consuming and computing-expensive to find the optimal solution, especially in a large-scale network. To solve these problems, one approach is to design a low-complexity algorithm with near optimal performance. In some cases, the low complexity algorithms are hard to obtain, deep learning can be used as an accurate approximator that maps environment parameters, such as the channel state information and traffic state, to the optimal solutions. In this thesis, we design low-complexity optimization algorithms, and deep learning frameworks in different architectures of 5G NR to resolve optimization problems subject to QoS requirements. First, we propose a low-complexity algorithm for a joint cooperative beamforming and user association problem for eMBB in 5G NR to maximize the network capacity. Next, we propose a deep learning (DL) framework to optimize user association, resource allocation, and offloading probabilities for delay-tolerant services and URLLC in 5G NR. Finally, we address the issue of time-varying traffic and network conditions on resource management in 5G NR