A game theoretic framework is developed in this paper to facilitate inter-cell interference management through cognitive sensing distributively performed by mobile stations (MSs). Using stochastic geometry, we reveal the relationship between the effectiveness of interference management and MSśẅillingnessẗo perform cognitive sensing. Such cognitive sensing performed by MS is motivated by the associated beneficial results as well as by the rewards from base stations (BS) that encourage sensing. Different tradeoffs for BS and MSs exist in their interactions, which are modeled as a stackelberg game in this paper. While both BS and MS seek to manage interference at its own minimum cost, we design algorithm to achieve nash Equilibrium in such a game and investigate the optimal strategies taken by the players (BS and MSs).
ICC 2008This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract: A game theoretic framework is developed in this paper to facilitate inter-cell interference management through cognitive sensing distributively performed by mobile stations (MSs). Using stochastic geometry, we reveal the relationship between the effectiveness of interference management and MS's "willingness" to perform cognitive sensing. Such cognitive sensing performed by MS is motivated by the associated beneficial results as well as by the rewards from base station(BS) that encourage sensing. Different tradeoffs for BS and MSs exist in their interactions, which are modeled as a Stackelberg game in this paper. While both BS and MS seek to manage interference at its own minimum cost, we design algorithm to achieve Nash Equilibrium in such a game and investigate the optimal strategies taken by the players (BS and MSs).