Game Theory for Networks: A tutorial on game-theoretic tools for emerging signal processing applications

Giacomo Bacci, Samson Lasaulce, Walid Saad, Luca Sanguinetti
2016 IEEE Signal Processing Magazine  
In this tutorial, the basics of game theory are introduced along with an overview of its most recent and emerging applications in signal processing. One of the main features of this contribution is to gather in a single paper some fundamental game-theoretic notions and tools which, over the past few years, have become widely spread over a large number of papers. In particular, both strategic-form and coalition-form games are described in details while the key connections and differences between
more » ... them are outlined. Moreover, a particular attention is also devoted to clarify the connections between strategic-form games and distributed optimization and learning algorithms. Beyond an introduction to the basic concepts and main solution approaches, several carefully designed examples are provided to allow a better understanding of how to apply the described tools. I. INTRODUCTION Game theory is a branch of mathematics that enables the modeling and analysis of the interactions between several decision-makers (called players) who can have conflicting or common objectives. A game is a situation in which the benefit or cost reaped by each player from an interactive situation does not only depend on its own decisions but also on those taken by the other players. For example, the time a car driver needs to get back home generally depends not only on the route he/she chooses but also on the decisions taken by the other drivers. Therefore, in a game, the actions and objectives of the players are tightly coupled. Until very recently, game theory (GT) has been used only marginally in signal processing, with notable examples being some applications in robust detection and estimation [1] as well as watermarking [2] (in which the watermarking problem is seen as a game between the data embedder and the attacker). However, the real catalyzer of the application of GT to signal processing (SP) has been the blooming of all issues related to networking in general, and distributed networks, in particular. The interactions that take place in a network can often be modeled as a game, in which the network nodes are the players that compete or form coalitions to get some advantage and enhance their quality-of-service. The main motivation behind formulating a game in a network is the large interdependence between the actions of the network nodes due to factors such as the use of common resources (e.g., computational, storage, or spectral resources), with interference across wireless networks being an illustrative case study. Paradigmatic examples of this approach can be found in the broad field of SP for communication networks in which GT is used to address fundamental networking issues such as: controlling the power of radiated signals in wireless networks, with the G. Bacci was with the University of Pisa, Pisa, Italy, and is now with MBI srl,
doi:10.1109/msp.2015.2451994 fatcat:mur5pyjsbzf33hzts3lx4yxeiy