A fast and simple randomized parallel algorithm for maximal matching
Information Processing Letters
Matrix analysis
CDMA uplink power control as a noncooperative game
Wireless Networks
Convex Optimization
IEEE Transactions on Communications
Dynamic Spectrum Access and Management in Cognitive Radio Networks
Dynamic Spectrum Access and Management in Cognitive Radio Networks
Wireless Networking
A game-based self-organizing uplink tree for VoIP services in IEEE 802.16j networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Lifetime maximization via cooperative nodes and relay deployment in wireless networks
IEEE Journal on Selected Areas in Communications
Coalitions in Cooperative Wireless Networks
IEEE Journal on Selected Areas in Communications
Joint Channel and Power Allocation in Wireless Mesh Networks: A Game Theoretical Perspective
IEEE Journal on Selected Areas in Communications
Inefficient Noncooperation in Networking Games of Common-Pool Resources
IEEE Journal on Selected Areas in Communications
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Efficacy of commercial wireless networks can be substantially enhanced through large-scale cooperation among involved entities such as providers and customers. The success of such cooperation is contingent upon the design of judicious resource allocation strategies that ensure that the individuals' pay-offs are commensurate to the resources they offer to the coalition. The resource allocation strategies depend on which entities are decision-makers and whether and how they share their aggregate payoffs. Initially, we consider the scenario where the providers are the only decision-makers and they do not share their payoffs. We formulate the resource allocation problem as a nontransferable payoff coalitional game and show that there exists a cooperation strategy that leaves no incentive for any subset of providers to split from the grand coalition, i.e., the core of the game is nonempty. To compute this cooperation strategy and the corresponding payoffs, we subsequently relate this game and its core to an exchange market setting and its equilibrium, which can be computed by several efficient algorithms. Next, we investigate cooperation when customers are also decision-makers and decide which provider to subscribe to based on whether there is cooperation. We formulate a coalitional game in this setting and show that it has a nonempty core. Finally, we extend the formulations and results to the cases where the payoffs are vectors and can be shared selectively.