Mobile data offloading enables the mobile network operator (MNO) to deal with the explosive growth of cellular data by leasing third-party access points (APs) to partially deliver the mobile traffic. This study proposes a novel incentive framework for the mobile data offloading market under QoE-aware users. Considering user satisfaction, the authors formulate the interaction among the MNO, APs, and offloaded users as a three-stage Stackelberg game. Through the Stackelberg game, the APs determine their optimal contributions via the best response method and the offloaded users determine their optimal accepted prices via the proposed dynamic pricing mechanism. Then the MNO makes its decision for profit maximisation. Furthermore, based on contract theory, an optimal dynamic scheme between the MNO and the remaining users is established. Under the dynamic scheme, they prove the personal rationality and incentive compatibility properties. Moreover, the optimisation contract problem is transformed into a relaxed contract problem, and the proposed dynamic algorithm is subsequently used to handle non-feasible solutions. Thus, the proposed framework can improve user satisfaction without affecting MNO profits. Simulation results show that the proposed framework can achieve better performances in terms of user satisfaction and MNO profits compared with traditional algorithms.

中文翻译：

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QoE感知用户下的移动数据卸载市场激励框架

移动数据卸载使移动网络运营商（MNO）通过租赁第三方访问点（AP）来部分交付移动流量，从而应对蜂窝数据的爆炸性增长。这项研究为QoE感知用户下的移动数据卸载市场提出了一种新颖的激励框架。考虑到用户满意度，作者将MNO，AP和卸载的用户之间的交互关系公式化为三阶段Stackelberg游戏。通过Stackelberg博弈，接入点通过最佳响应方法确定其最佳贡献，而卸载用户则通过提议的动态定价机制确定其最佳接受价格。然后，MNO做出利润最大化的决策。此外，基于合同理论，建立了移动网络运营商与其余用户之间的最优动态方案。在动态方案下，他们证明了个人理性和激励相容性。此外，将优化合同问题转化为宽松合同问题，然后将所提出的动态算法用于处理不可行的解决方案。因此，提出的框架可以提高用户满意度，而不会影响MNO的利润。仿真结果表明，与传统算法相比，该框架在用户满意度和移动网络运营商利润方面都有较好的表现。建议的框架可以提高用户满意度，而不会影响MNO的利润。仿真结果表明，与传统算法相比，该框架在用户满意度和移动网络运营商利润方面都具有较好的性能。建议的框架可以提高用户满意度，而不会影响MNO的利润。仿真结果表明，与传统算法相比，该框架在用户满意度和移动网络运营商利润方面都具有较好的性能。