Game-Theoretic Models for Vehicular Networks
Dusit Tao Niyato, Ekram Hossain, Mahbub Hassan · Wireless networks and mobile communications · 2011
Contents 1.1 A Brief Survey: Multiuser Games in Wireless Communications . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.1 Noncooperative Games and Nash Equilibria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.1.2 Cooperative Games: Nash Bargaining and Other Bargaining Solutions . . . . . . . . . . . 7 1.1.3 Multiuser Systems: Generalized Signal Model and Game Model . . . . . . . . . . . . . . . . . . 8 1.2 Power Allocation Games: Competition versus Cooperation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.1 Power Allocation on Flat Fading Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.2 Power Allocation on Frequency Selective Fading Channels . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3 Beamforming Games on MISO Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.3.1 Beamforming on the MISO Channel: Noncooperative Games . . . . . . . . . . . . . . . . . . . . 15 1.3.2 Cooperative Beamforming: Time Sharing, Convex Hull, and Nash Bargaining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.3.3 Pareto-Optimality: Competition and Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.4 Matrix Games: Precoding Games and Others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.4.1 Precoding Games on the MIMO Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.4.2 Other Matrix Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.5 Further Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.5.1 Efficiency and Fairness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.5.2 Uniqueness and Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.5.3 Implementation: Centralized versus Distributed Structure . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.6 Open Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.6.1 On the User Number. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.6.2 On the Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.6.3 On the Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Wireless communications are always resource limited. In multiuser wireless systems, all users compete for resources and can interfere with each other. The conflicting objectives of users make it highly unlikely for any user to gain more profit without harming other users. The possibility of exploiting interactions among wireless users was not considered in traditional information-theoretic studies of the multiuser systems. Therefore, the results obtained from the information-theoretic perspectives might lead to unstable or even infeasible solutions for multiuser systems when the selfish nature of the users is taken into account. Indeed, it is reasonable to assume that all users compete for the maximum achievable benefit at all time. Then, the competition among the users should be analyzed and regulated to improve the overall performance of the whole multiuser system.