In recent years, game-theoretic tools have been increasingly used to study many important resource allocation problems in communications and networking. When it comes to (distributed) computation of equilibria, two common issues arise from current approaches, namely: i) the best-response mapping of each player must be unique and is required to be computed in closed form; and ii) convergence of proposed algorithms is obtained only under conditions implying the uniqueness of the Nash Equilibrium. Even thought these assumptions simplify considerably the analysis of the games under investigation, they may be too demanding in many practical situations, thus strongly limiting the applicability of current methodologies to games with arbitrary objective functions and strategy sets. In this paper, we overcome these limitations and propose novel distributed algorithms for arbitrary noncooperative games having (possibly) multiple solutions. The new methods, whose convergence analysis is based on variational inequality techniques, are able to select, among all the equilibria of a game, those which optimize a given performance criterion, at the cost of limited signaling among the players. We then apply the developed methods to solve a MIMO game in cognitive radios, showing a considerable performance improvement over classical pure noncooperative schemes.

Equilibrium selection in MIMO communication games / Scutari, Gesualdo; Facchinei, Francisco; Pang, Jong Shi. - STAMPA. - (2012), pp. 80-84. (Intervento presentato al convegno 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012 tenutosi a Cesme; Turkey nel 17-20 June 2012) [10.1109/SPAWC.2012.6292984].

Equilibrium selection in MIMO communication games

FACCHINEI, Francisco;
2012

Abstract

In recent years, game-theoretic tools have been increasingly used to study many important resource allocation problems in communications and networking. When it comes to (distributed) computation of equilibria, two common issues arise from current approaches, namely: i) the best-response mapping of each player must be unique and is required to be computed in closed form; and ii) convergence of proposed algorithms is obtained only under conditions implying the uniqueness of the Nash Equilibrium. Even thought these assumptions simplify considerably the analysis of the games under investigation, they may be too demanding in many practical situations, thus strongly limiting the applicability of current methodologies to games with arbitrary objective functions and strategy sets. In this paper, we overcome these limitations and propose novel distributed algorithms for arbitrary noncooperative games having (possibly) multiple solutions. The new methods, whose convergence analysis is based on variational inequality techniques, are able to select, among all the equilibria of a game, those which optimize a given performance criterion, at the cost of limited signaling among the players. We then apply the developed methods to solve a MIMO game in cognitive radios, showing a considerable performance improvement over classical pure noncooperative schemes.
2012
2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012
Electrical and Electronic Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Information Systems
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Equilibrium selection in MIMO communication games / Scutari, Gesualdo; Facchinei, Francisco; Pang, Jong Shi. - STAMPA. - (2012), pp. 80-84. (Intervento presentato al convegno 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012 tenutosi a Cesme; Turkey nel 17-20 June 2012) [10.1109/SPAWC.2012.6292984].
File allegati a questo prodotto
File Dimensione Formato  
VE_2012_11573-951030.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 184.61 kB
Formato Adobe PDF
184.61 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/951030
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 6
social impact