Teoria de jogos para utilização efetiva dos recursos em aplicações para 5G

Doutoramento em Engenharia Eletrotécnica - TelecomunicaçõesEsta tese tem como objetivo fornecer afirmações conclusivas em relação a utilização eficiente de recursos para redes e aplicações de 5G (5a geração) com recurso a teoria dos jogos. Neste contexto, investigamos dois cenários principais, um relativo a comunicações móveis e um outro relativo a redes inteligentes. Uma métrica importante para o desenho das redes móveis emergentes é a eficiência energética, com particular ênfase no lado do dispositivo móvel, onde as tecnologias das baterias são ainda limitadas. Alguns trabalhos de investigação relacionados têm demonstrado que a cooperação pode ser um paradigma útil no sentido de resolver o problema do défice energético. Contudo, pretendemos ir mais além, ao definir a cooperação e os utilizadores móveis como um grupo de jogadores racionais, que podem atuar sobre estratégias e utilidades, por forma a escolher a retransmissão mais apropriada para poupança de energia. Esta interpretação presta-se à aplicação da teoria dos jogos, e recorremos assim aos jogos coalicionais para solucionar conflitos de interesse entre dispositivos cooperantes, empregando Programação Linear (LP) para resolver o problema da selecção da retransmissão e derivar a principal solução do jogo. Os resultados mostram que a escolha do jogo de retransmissão coalicional proposto pode potencialmente duplicar a duração da bateria, numa era em que a próxima geração de dispositivos móveis necessitará de cada vez mais energia para suportar serviços e aplicações cada vez mais sofisticados. O segundo cenário investiga a resposta da procura em aplicações smart grid, que está a ganhar interesse sob a égide do 5G e que é considerada uma abordagem promissora, incentivando os utilizadores a consumir electricidade de forma mais uniforme em horas de vazio. Recorremos novamente à teoria dos jogos, imaginando as interacções estratégicas entre a empresa fornecedora de energia eléctrica e os potenciais utilizadores finais como um jogo de forma extensiva. São abordados dois programas em tempo real de resposta à procura: Day-Ahead Pricing (DAP) e Convex Pricing Tariffs. A resposta dos consumidores residenciais conscientes dos preços destas tarifas, é formulada como um problema de Mixed Integer Linear Programming (MILP) ou Quadratic Programming (QP), nos quais as soluções potenciais são o agendamento dos seus electrodomésticos inteligentes de modo a minimizar os seus gastos diários de electricidade, satisfazendo as suas necessidades diárias de energia e níveis de conforto. Os resultados demonstram que implementar o programa DAP pode reduzir a razão Peak-to-Average (PAR) at e 71% e as faturas de consumo das casas inteligentes at e 32%. Para além disso, a aplicação de tarifas convexas em tempo real pode melhorar ainda mais estas métricas de desempenho, alcançando uma redução de 80% do PAR e uma economia de mais de 50% na faturação da energia residencial.This research thesis aims to provide conclusive statements towards effective resource utilization for 5G (5th Generation) mobile networks and applications using game theory. In this context, we investigate two key scenarios pertaining to mobile communications and smart grids. A pivotal design driver for the upcoming era of mobile communications is energy efficiency, with particular emphasis on the mobile side where battery technology is still limited. Related works have shown that cooperation can be a useful engineering paradigm to take a step towards solving the energy deficit. However, we go beyond by envisaging cooperation and mobile users as a game of rational players, that can act on strategies and utilities in order to choose the most appropriate relay for energy saving. This interpretation lends itself to the application of game theory, and we look at coalitional games to settle conflicts of interest among cooperating user equipments, and employ Linear Programming (LP) to solve the relay selection problem and to derive the core solution of the game. The results reveal that adopting the proposed coalitional relaying game can potentially double battery lifetime, in an era where the next wave of next generation handsets will be more energy demanding supporting sophisticated services and applications. The second scenario investigates demand response in smart grid applications, which is also gaining momentum under the umbrella of 5G, which is a promising approach urging end-users to consume electricity more evenly during nonpeak hours of the day. Again, we resort to game theory and picture the strategic interactions between the electric utility company and the potential end-users as an extensive form game. Two real-time demand response programmes are addressed, namely Day-Ahead Pricing (DAP) and convex pricing tariffs. The response of price-aware residential consumers to these programmes is formulated as Mixed Integer Linear Programming (MILP) or Quadratic Programming (QP) problem, which optimally schedule their smart home appliances so as to minimise their daily electricity expenses while satisfying their daily energy needs and comfort levels. The results demonstrate that implementing the DAP programme can reduce the Peakto- Average Ratio (PAR) of demand by up to 71% and cut smart households bill by 32%. Moreover, applying real-time convex pricing tariffs can push these performance metrics even further, achieving 80% PAR reduction and more than 50% saving on the household electricity bill

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Game Theory in Communications:a Study of Two Scenarios

Multi-user communication theory typically studies the fundamental limits of communication systems, and considers communication schemes that approach or even achieve these limits. The functioning of many such schemes assumes that users always cooperate, even when it is not in their own best interest. In practice, this assumption need not be fulfilled, as rational communication participants are often only interested in maximizing their own communication experience, and may behave in an undesirable manner from the system's point of view. Thus, communication systems may operate differently than intended if the behavior of individual participants is not taken into account. In this thesis, we study how users make decisions in wireless settings, by considering their preferences and how they interact with each other. We investigate whether the outcomes of their decisions are desirable, and, if not, what can be done to improve them. In particular, we focus on two related issues. The first is the decision-making of communication users in the absence of any central authority, which we consider in the context of the Gaussian multiple access channel. The second is the pricing of wireless resources, which we consider in the context of the competition of wireless service providers for users who are not contractually tied to any provider, but free to choose the one offering the best tradeoff of parameters. In the first part of the thesis, we model the interaction of self-interested users in a Gaussian multiple access channel using non-cooperative game theory. We demonstrate that the lack of infrastructure leads to an inefficient outcome for users who interact only once, specifically due to the lack of coordination between users. Using evolutionary game theory, we show that this inefficient outcome would also arise as a result of repeated interaction of many individuals over time. On the other hand, if the users correlate their decoding schedule with the outcome of some publicly observed (pseudo) random variable, the resulting outcome is efficient. This shows that sometimes it takes very little intervention on the part of the system planner to make sure that users choose a desirable operating point. In the second part of the thesis, we consider the competition of wireless service providers for users who are free to choose their service provider based on their channel parameters and the resource price. We model this situation as a two-stage game where the providers announce unit resource prices in the first stage and the users choose how much resource they want to purchase from each provider in the second stage. Under fairly general conditions, we show that the competitive interaction of users and providers results in socially optimal resource allocation. We also provide a decentralized primal-dual algorithm and prove its convergence to the socially optimal outcome

Distributed radio resource allocation in wireless heterogeneous networks

This dissertation studies the problem of resource allocation in the radio access network of heterogeneous small-cell networks (HetSNets). A HetSNet is constructed by introducing smallcells(SCs) to a geographical area that is served by a well-structured macrocell network. These SCs reuse the frequency bands of the macro-network and operate in the interference-limited region. Thus, complex radio resource allocation schemes are required to manage interference and improve spectral efficiency. Both centralized and distributed approaches have been suggested by researchers to solve this problem. This dissertation follows the distributed approach under the self-organizing networks (SONs) paradigm. In particular, it develops game-theoretic and learning-theoretic modeling, analysis, and algorithms. Even though SONs may perform subpar to a centralized optimal controller, they are highly scalable and fault-tolerant. There are many facets to the problem of wireless resource allocation. They vary by the application, solution, methodology, and resource type. Therefore, this thesis restricts the treatment to four subproblems that were chosen due to their significant impact on network performance and suitability to our interests and expertise. Game theory and mechanism design are the main tools used since they provide a sufficiently rich environment to model the SON problem. Firstly, this thesis takes into consideration the problem of uplink orthogonal channel access in a dense cluster of SCs that is deployed in a macrocell service area. Two variations of this problem are modeled as noncooperative Bayesian games and the existence of pure-Bayesian Nash symmetric equilibria are demonstrated. Secondly, this thesis presents the generalized satisfaction equilibrium (GSE) for games in satisfaction-form. Each wireless agent has a constraint to satisfy and the GSE is a mixed-strategy profile from which no unsatisfied agent can unilaterally deviate to satisfaction. The objective of the GSE is to propose an alternative equilibrium that is designed specifically to model wireless users. The existence of the GSE, its computational complexity, and its performance compared to the Nash equilibrium are discussed. Thirdly, this thesis introduces verification mechanisms for dynamic self-organization of Wireless access networks. The main focus of verification mechanisms is to replace monetary transfers that are prevalent in current research. In the wireless environment particular private information of the wireless agents, such as block error rate and application class, can be verified at the access points. This verification capability can be used to threaten false reports with backhaul throttling. The agents then learn the truthful equilibrium over time by observing the rewards and punishments. Finally, the problem of admission control in the interfering-multiple access channel with rate constraints is addressed. In the incomplete information setting, with compact convex channel power gains, the resulting Bayesian game possesses at least one pureBayesian Nash equilibrium in on-off threshold strategies. The above-summarized results of this thesis demonstrate that the HetSNets are amenable to self-organization, albeit with adapted incentives and equilibria to fit the wireless environment. Further research problems to expand these results are identified at the end of this document

Network Science for IoT

The research work presented in this thesis is based on the concept and defintion of network that can spread in several and different real world contexts. Indeed, we can refer to a network in a telecommunications sense considering a collection of transmitters, receivers, and communication channels that send or are used to send information to one another. However, as a matter of fact, in nature there are other several examples of networks: the human brain is one of them. The relationship between the actors in Hollywood can be studied in terms of network as well, a generic social community can be compared to a network, eco-systems are networks of species. The recent Network Science aims at studying all these systems using a set of common mathematical methods. In the following of the thesis, we will focus on some of well known telecommunications networks issues using standard telecommunications procedures to address them, with relevant reference to video flow transmissions and management of electric vehicles networks. At the same time, different models aiming at reach the same goals in contexts that may differ from a telecommunications setup can be used. In more details, we will evaluate queueing systems, jamming problems, groups recognition in networks, and mobile computing using game theoretic approaches. It is worth noting that this aspect can be also seen in a reverse order. Indeed, we will discuss how standard telecommunications analysis can be used to investigate on problems not directly related to a telecommunications background. In particular, one of our future purposes is to investigate on the brain connectivity that is raising significant interest in the recent scientific society