One of the currently explored strategies for interference avoidance and improving Signal to Noise Ratio (SNR) for mobile communication systems is Coordinated MultiPoint (CoMP) transmission. The general idea of the strategy is to let two or more base stations serve the same user. Due to delay factors, the channels from each serving base station needs to be predicted to obtain an adaptive CoMP system. In this thesis, a user interface is created to act as an experimental platform for a set of measured downlink channel data. The user interface supports editing of the channel data, model estimation, Kalman filtering and prediction and evaluation of the channel statistics. The user interface and the measured channel downlink data is then used to examine how well we can predict the weakest channel in a CoMP setup with three base stations. The predictions are carried out using an m-step Kalman predictor which uses an AR4 model, estimated from previous channel data. For the investigation, the user moves at pedestrian speed and the signals from the three different base stations use orthogonal Common Reference Signals (CRS). A comparison of different CRS patterns is also included in the investigation. It is concluded that 5 ms predictions of the weakest channel achieves a normalized mean squared error (NMSE) of -8 dB or lower provided that the weakest signal has an SNR of at least 5 dB and is no more than 15 dB lower than the combined received signal. Additionally, it is found that predictions are more accurate for CRS patterns spread over time than over subcarriers.

In the first part of this dissertation, a novel medium access protocol for the Internet of Thing (IoT) networks is introduced. The Internet of things (IoT), which is the network of physical devices embedded with sensors, actuators, and connectivity, is being accelerated into the mainstream by the emergence of 5G wireless networking. This work presents an uncoordinated non-orthogonal random-access protocol, which is an enhancement to the recently introduced slotted ALOHA- NOMA (SAN) protocol that provides high throughput, while being matched to the low complexity requirements and the sporadic traffic pattern of IoT devices. Under ideal conditions it has been shown that slotted ALOHA-NOMA (SAN), using power- domain orthogonality, can significantly increase the throughput using SIC (Successive Interference Cancellation) to enable correct reception of multiple simultaneous transmitted signals. For this ideal performance, the enhanced SAN receiver adaptively learns the number of active devices (which is not known a priori) using a form of multi-hypothesis testing. For small numbers of simultaneous transmissions, it is shown that there can be substantial throughput gain of 5.5 dB relative to slotted ALOHA (SA) for 0.07 probability of transmission and up to 3 active transmitters. As a further enhancement to SAN protocol, the SAN with beamforming (BF-SAN) protocol was proposed. The BF-SAN protocol uses beamforming to significantly improve the throughput to 1.31 compared with 0.36 in conventional slotted ALOHA when 6 active IoT devices can be successfully separated using 2×2 MIMO and a SIC (Successive Interference Cancellation) receiver with 3 optimum power levels. The simulation results further show that the proposed protocol achieves higher throughput than SAN with a lower average channel access delay. In the second part of this dissertation a novel Machine Learning (ML) approach was applied for proactive mobility management in 5G Virtual Cell (VC) wireless networks. Providing seamless mobility and a uniform user experience, independent of location, is an important challenge for 5G wireless networks. The combination of Coordinated Multipoint (CoMP) networks and Virtual- Cells (VCs) are expected to play an important role in achieving high throughput independent of the mobile’s location by mitigating inter-cell interference and enhancing the cell-edge user throughput. User- specific VCs will distinguish the physical cell from a broader area where the user can roam without the need for handoff, and may communicate with any Base Station (BS) in the VC area. However, this requires rapid decision making for the formation of VCs. In this work, a novel algorithm based on a form of Recurrent Neural Networks (RNNs) called Gated Recurrent Units (GRUs) is used for predicting the triggering condition for forming VCs via enabling Coordinated Multipoint (CoMP) transmission. Simulation results show that based on the sequences of Received Signal Strength (RSS) values of different mobile nodes used for training the RNN, the future RSS values from the closest three BSs can be accurately predicted using GRU, which is then used for making proactive decisions on enabling CoMP transmission and forming VCs. Finally, the work in the last part of this dissertation was directed towards applying Bayesian games for cell selection / user association in 5G Heterogenous networks to achieve the 5G goal of low latency communication. Expanding the cellular ecosystem to support an immense number of connected devices and creating a platform that accommodates a wide range of emerging services of different traffic types and Quality of Service (QoS) metrics are among the 5G’s headline features. One of the key 5G performance metrics is ultra-low latency to enable new delay-sensitive use cases. Some network architectural amendments are proposed to achieve the 5G ultra-low latency objective. With these paradigm shifts in system architecture, it is of cardinal importance to rethink the cell selection / user association process to achieve substantial improvement in system performance over conventional maximum signal-to- interference plus noise ratio (Max-SINR) and Cell Range Expansion (CRE) algorithms employed in Long Term Evolution- Advanced (LTE- Advanced). In this work, a novel Bayesian cell selection / user association algorithm, incorporating the access nodes capabilities and the user equipment (UE) traffic type, is proposed in order to maximize the probability of proper association and consequently enhance the system performance in terms of achieved latency. Simulation results show that Bayesian game approach attains the 5G low end-to-end latency target with a probability exceeding 80%.

La pénurie d'énergie et le manque d'infrastructures dans les régions rurales représentent une barrière pour le déploiement et l'extension des réseaux cellulaires. Les approches et techniques pour relier les stations de base (BSs) entre elles à faible coût et d'une manière fiable et efficace énergiquement sont l'une des priorités des opérateurs. Ces réseaux peu denses actuellement, peuvent évoluer rapidement et affronter une croissance exponentielle due principalement à l'utilisation des téléphones mobiles, tablettes et applications gourmandes en bande passante. La densification des réseaux est l'une des solutions efficaces pour répondre à ce besoin en débit élevé. Certes, l'introduction de petites BSs apporte de nombreux avantages tels que l'amélioration du débit et de la qualité du signal, mais entraîne des contraintes opérationnelles telles que le choix de l'emplacement des noeuds dans ces réseaux de plus en plus denses ainsi que leur alimentation. Les problèmes où la contrainte spatiale est prépondérante sont bien appropriés à la modélisation par la géométrie stochastique qui permet une modélisation réaliste de distribution des BSs. Ainsi, l'enjeu est de trouver de nouvelles approches de gestions d'interférence et de réductions de consommation énergétique dans les réseaux sans fil. Le premier axe de cette thèse s'intéresse aux méthodes de gestion d'interférence dans les réseaux cellulaires se basant sur la coordination entre les BSs, plus précisément, la technique Coordinated MultiPoint Joint Transmission (CoMP-JT). En CoMP-JT, les utilisateurs en bordure de cellules qui subissent un niveau très élevé d'interférences reçoivent plusieurs copies du signal utile de la part des BSs qui forment l'ensemble de coordination. Ainsi, nous utilisons le modèle r-l Square Point Process (PP) à fin de modéliser la distribution des BSs dans le plan. Le processus r-l Square PP est le plus adapté pour modéliser le déploiement réel des BSs d'un réseau sans fil, en assurant une distance minimale, (r - l), entre les points du processus. Nous discutons l'impact de la taille de l'ensemble de coordination sur les performances évaluées. Ce travail est étendu pour les réseaux denses WiFi IEEE 802.11, où les contraintes de portées de transmission et de détection de porteuse ont été prises en compte. Dans le deuxième axe du travail, nous nous intéressons à l'efficacité énergétique des réseaux mesh. Nous proposons l'utilisation des antennes directionnelles (DAs) pour réduire la consommation énergétique et améliorer le débit de ces réseaux mesh. Les DAs ont la capacité de focaliser la transmission dans la direction du récepteur, assurant une portée plus importante et moins d'énergie dissipée dans toutes les directions. Pour différentes topologies, nous dérivons le nombre de liens et montrons que ce nombre dépend du nombre de secteurs de l'antenne. Ainsi, en utilisant les simulations, nous montrons que le gain, en énergie et en débit, apporté par les DAs peut atteindre 70% dans certains cas. De plus, on propose un modèle d'optimisation conjointe d'énergie et du débit adapté aux réseaux WMNs équipés de DAs. La résolution numérique de ce modèle conforte les résultats de simulation obtenus dans la première partie de cette étude sur l'impact des DAs sur les performances du réseau en termes de débit et d'énergie consommée. Ces travaux de thèse s'inscrivent dans le cadre du projet collaboratif (FUI16 LCI4D), qui consiste à concevoir et à valider une architecture radio ouverte pour renforcer l'accès aux services broadband dans des lieux ne disposant que d'une couverture minimale assurée par un réseau macro-cellulaire traditionnel. / Today's networks continue to evolve and grow resulting more dense, complex and heterogeneous networks.This leads to new challenges such as finding new models to characterize the nodes distribution in the wireless network and approaches to mitigate interference. On the other hand, the energy consumption of WMNs is a challenging issue mainly in rural areas lacking of default electrical grids. Finding alternative technologies and approaches to reduce the consumed energy of these networks is a interesting task. This thesis focuses on proposing and evaluating interference management models for next generation wireless networks (5G and Very Dense High WLANs), and providing tools and technologies to reduce energy consumption of Wireless Mesh Networks (WMNs). Two different problems are thus studied; naturally the thesis is divided into two parts along the following chapters.The contribution of the first part of the thesis is threefold. Firstly, we develop our interference management coordination (CoMP-JT) model. The main idea of CoMP-JT is to turn signals generating harmful interference into useful signals. We develop a new model where BSs inside the coordinated set send a copy of data to border's users experiencing high interference. We consider the r-l Square point process to model the BSs distribution in the network. We derive network performance in terms of coverage probability and throughput. Additionally, we study the impact of the size of coordination set on the network performance. Secondly, we extend these results and provide a new model adopted for Dense Very high throughput WLANs. We take into consideration constraints of WLANs in our model such as carrier sensing range. Thirdly, we tackle resource allocation strategies to limit the interference in LTE networks. We study three cyclic allocation strategies: (i) the independent allocation, (ii) the static allocation and (iii) the load-dependent strategy. We derive tractable analytical expression of the first and second mean of interference. We validate the model using extensive simulations. Reducing the energy consumption and improving the energy efficiency of WMNs is our concern in the second part of the thesis. Indeed, we aim at studying the impact of directional antennas technology on the performance of WMNs, using both analysis and simulations. Fisrt, We derive the Number of Links (NLs) for the chain and grid topologies for different antennas beams. These results are based on the routing tables of nodes in the network. We consider different scenarios such as 1Source-NDestinations to model the downlink communications, NSources-1Destination to model the uplink communications and the 1Source-1Destination as a baseline scenario. Using ns-3 simulator, we simulate network performance in terms of Mean Loss Ratio, throughput, energy consumption and energy efficiency. Then, we study the impact of number of beams, network topology and size, the placement of the gateway on the network performance. Next, we go beyond simulations and propose an optimization framework minimizing the consumed energy while maximizing the network throughput for DAs WMNs. We consider a weighted objective function combining the energy consumption and the throughput. We use power control to adapt transmission power depending on the location of the next hop. This model is a first step to approve the obtained simulation results. We use ILOG Cplex solver to find the optimal solution. Results show that DAs improves the network throughput while reduce the energy consumption and that power control allows saving more energy. In this direction, the LCI4D Project aims at providing low cost infrastructure to connect isolated rural and sub-urban areas to the Internet. In order to reduce the installation and maintenance costs, LCI4D proposes the usage of self-configured Wireless Mesh Networks (WMNs) to connect multimode outdoor femtocells to the remote Marco cell (gateway).

The next generation wireless networks i.e. 5G aim to provide multi-Gbps data traffic, in order to satisfy the increasing demand for high-definition video, among other high data rate services, as well as the exponential growth in mobile subscribers. To achieve this dramatic increase in data rates, current research is focused on improving the capacity of current 4G network standards, based on Long Term Evolution (LTE), before radical changes are exploited which could include acquiring additional/new spectrum. The LTE network has a reuse factor of one; hence neighbouring cells/sectors use the same spectrum, therefore making the cell edge users vulnerable to inter-cell interference. In addition, wireless transmission is commonly hindered by fading and pathloss. In this direction, this thesis focuses on improving the performance of cell edge users in LTE and LTE-Advanced (LTE-A) networks by initially implementing a new Coordinated Multi-Point (CoMP) algorithm to mitigate cell edge user interference. Subsequently Device-to-Device (D2D) communication is investigated as the enabling technology for maximising Resource Block (RB) utilisation in current 4G and emerging 5G networks. It is demonstrated that the application, as an extension to the above, of novel power control algorithms, to reduce the required D2D TX power, and multihop transmission for relaying D2D traffic, can further enhance network performance. To be able to develop the aforementioned technologies and evaluate the performance of new algorithms in emerging network scenarios, a beyond-the-state-of-the-art LTE system-level simulator (SLS) was implemented. The new simulator includes Multiple-Input Multiple-Output (MIMO) antenna functionalities, comprehensive channel models (such as Wireless World initiative New Radio II i.e. WINNER II) and adaptive modulation and coding schemes to accurately emulate the LTE and LTE-A network standards. Additionally, a novel interference modelling scheme using the 'wrap around' technique was proposed and implemented that maintained the topology of flat surfaced maps, allowing for use with cell planning tools while obtaining accurate and timely results in the SLS compared to the few existing platforms. For the proposed CoMP algorithm, the adaptive beamforming technique was employed to reduce interference on the cell edge UEs by applying Coordinated Scheduling (CoSH) between cooperating cells. Simulation results show up to 2-fold improvement in terms of throughput, and also shows SINR gain for the cell edge UEs in the cooperating cells. Furthermore, D2D communication underlaying the LTE network (and future generation of wireless networks) was investigated. The technology exploits the proximity of users in a network to achieve higher data rates with maximum RB utilisation (as the technology reuses the cellular RB simultaneously), while taking some load off the Evolved Node B (eNB) i.e. by direct communication between User Equipment (UE). Simulation results show that the proximity and transmission power of D2D transmission yields high performance gains for a D2D receiver, which was demonstrated to be better than that of cellular UEs with better channel conditions or in close proximity to the eNB in the network. The impact of interference from the simultaneous transmission however impedes the achievable data rates of cellular UEs in the network, especially at the cell edge. Thus, a power control algorithm was proposed to mitigate the impact of interference in the hybrid network (network consisting of both cellular and D2D UEs). It was implemented by setting a minimum SINR threshold so that the cellular UEs achieve a minimum performance, and equally a maximum SINR threshold to establish fairness for the D2D transmission as well. Simulation results show an increase in the cell edge throughput and notable improvement in the overall SINR distribution of UEs in the hybrid network. Additionally, multihop transmission for D2D UEs was investigated in the hybrid network: traditionally, the scheme is implemented to relay cellular traffic in a homogenous network. Contrary to most current studies where D2D UEs are employed to relay cellular traffic, the use of idle nodes to relay D2D traffic was implemented uniquely in this thesis. Simulation results show improvement in D2D receiver throughput with multihop transmission, which was significantly better than that of the same UEs performance with equivalent distance between the D2D pair when using single hop transmission.

L'interférence entre stations de base est considérée comme le principal facteur limitant les performances des réseaux cellulaires. Nous nous intéressons aux différents schémas de coordination multi-point (CoMP) proposés dans la norme LTE-A pour y faire face, en tenant compte de l'aspect dynamique du trafic et de la mobilité des utilisateurs. Les résultats sont obtenus par l'analyse mathématique de modèles markoviens et par des simulations du système. Nous montrons l'importance de l'algorithme d'ordonnancement sur les performances en présence d'utilisateurs mobiles, pour des services de téléchargement de fichier et de streaming vidéo. Nous proposons un nouvel algorithme d'ordonnancement basé sur la dé-priorisation des utilisateurs mobiles se trouvant en bord de cellule, afin d'améliorer l'efficacité globale du système. Nous montrons ensuite qu'il est intéressant d'activer la technique dite Joint Processing uniquement dans un réseau à forte interférence, son activation dans un réseau à faible interférence pouvant conduire à une dégradation des performances. Nous proposons un nouveau mécanisme de coordination où une cellule ne coopère que lorsque sa coopération apporte un gain moyen de débit suffisant pour compenser les pertes de ressources engendrées. Nous considérons enfin la technique de formation de faisceaux coordonnée. Nous montrons notamment que la coordination n'est pas nécessaire lorsque l'on dispose d'un grand nombre d'antennes par station de base, un simple mécanisme d'ordonnancement opportuniste permettant d'obtenir des performances optimales. Pour un nombre limité d’antennes parstation de base, la coordination est nécessaire afin d’éviter l’interférence entre les faisceaux activés, et permet des gains de performance substantiels. / Interference is still the main limiting factor in cellular networks. We focus on the different coordinated multi-point schemes (CoMP) proposed in the LTE-A standard to cope with interference, taking into account the dynamic aspect of traffic and users’ mobility. The results are obtained by the analysis of Markov models and system-level simulations. We show the important impact of the scheduling strategy on the network performance in the presence of mobile users considering elastic traffic and video streaming. We propose a new scheduler that deprioritizes mobile users at the cell edge, in order to improve the overall system efficiency. We show that it is interesting to activate Joint Processing technique only in a high-interference network, its activation in a low-interference network may lead to performance degradation. We propose a new coordination mechanism, where a cell cooperates only when its cooperation brings a sufficient mean throughput gain, which compensates the extra resource consumption. Finally, we show that the coordination of beams is not necessary when a large number of antennas is deployed at each base station; a simple opportunistic scheduling strategy provides optimal performance. For a limited number of antennas per base station,coordination is necessary to avoid interference between the activated beams, allowing substantial performance gains.