Power control under best response dynamics for interference mitigation in a two-tier femtocell network

International audienceFemtocell networks are about to be extensively deployed with the aim of providing substantial improvements to cellular coverage and capacity. However, their deployment is nontrivial because of the extra interference that the femtocell nodes cause to the macrocell nodes with which they share the same portion of the spectrum. This paper proposes a noncooperative power control approach for interference mitigation in a two-tier femtocell network where the first tier is a conventional cellular network and the second tier is a set of (short-range) femtocells. We define objective functions that are different for Femtocell Mobile Nodes (FMNs) and macrocell Mobile Nodes (MNs). We then define a power control game, we prove the existence of a Nash Equilibrium (NE) for that game and we analyze the necessary and sufficient conditions so that the NE is unique. Based on the best response dynamics method, we propose a distributed iterative power control scheme that, starting from any initial power vector, converges to that NE. We simulate various scenarios that are based on realistic assumptions and topologies. Results show that, in many cases, in the NE, smooth coexistence of all entities of the topology is feasible

The co-existence of Femtocell with WiFi (in case of unlicensed spectrum splitting & sharing)

Les femtocellules et le WiFi sont souvent présentés comme étant deux technologies concurrentes. Cependant, la réalité dit totalement l'inverse; ces technologies sont supposées jouer des rôles complémentaires dans le but d'accompagner la croissance fulgurante du trafic mobile. De plus, elles sont souvent implémentées dans un même et unique équipement d'accès. Les équipements mobiles pourront ainsi choisir l'utilisation de la technologie qui représente la meilleure option. Le déploiement des femtocellules dans les hotspots WiFi permettra aux opérateurs de donner aux usagers la possibilité d'utiliser les technologies 3G. Par conséquent, grâce à ces deux technologies, la qualité de l'expérience de la communication pendant la mobilité sera sans doute meilleure. Toutefois, cette coexistence présente de nouveaux défis en vue de l'amélioration de performances en termes des débits de transmission et de qualité de service des usagers. Ainsi, nous croyons qu'un partitionnement efficace des ressources spectrales accompagné d'un réglage minutieux des paramètres de transmission permettra de maximiser les performances des deux technologies. Dans ce mémoire, nous nous intéressons à la coexistence des technologies femtocellule et WiFi : (i) Dans un premier lieu, nous proposons une technique de partage des bandes spectrales ouvertes entre le réseau WiFi et le réseau femtocellule. La technique proposée assure une qualité de service et une équité entre les transmissions concurrentes. En se basant sur plusieurs simulations, nous démontrons que la technique proposée assure un partage équitable du spectre. (ii) Dans un second lieu, nous proposons un Framework ayant pour objectif l'amélioration du débit total du réseau des femtocellules lorsque ces dernières utilisent simultanément des bandes de spectres ouvertes et d'autres sous licences. Le système étudié, comprenant le réseau WiFi et le réseau des femtocellules, a été modélisé analytiquement et ses performances ont été évaluées par plusieurs simulations. Ces dernières ont permis de quantifier l'effet de plusieurs paramètres de la technologie WiFi sur les performances du système étudié.\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Femtocellule, WiFi, allocation de spectre, qualité de service, équité, capacité, spectre sans licence, modèle de back-off

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond