The explosive growth in mobile data demand and the proliferation of advanced mobile devices have driven a phenomenal level of investment in next-generation networks. The successful development of next-generation networks relies on various enabling technologies. On the other hand, these network paradigms inevitably introduce economic challenges, such as incentives, information asymmetry, and strategic manipulation. These challenges also make economic enablers an indispensable role and require the joint design of economic mechanisms and algorithms for realizing the full potential of future networks.
In this talk, we first study a wireless powered network, in which energy users harvest the power carried by the broadcast signal and share the system transmission cost. Such a problem is challenging since the broadcast nature of wireless signal makes it a public good, which potentially incentivizes free-riders. We propose a low-complexity Power and Taxation Mechanism to overcome this challenge and to achieve efficient wireless power provision. Second, we study a general framework of network sharing, characterized by Network Utility Maximization (NUM). Network sharing introduces the issue of constraint information asymmetry; limited closely related studies provided solutions only applicable to specific application scenarios. To tackle these issues, we design the DeNUM Mechanism, the first mechanism in the literature for optimally solving general NUM Problems accounting for both private utility and constraint information. Third, motivated by the proliferation of real-time applications, we propose the concept of the fresh data market. We use the age-of-information (AoI) metric to characterize data freshness. We design the optimal fresh data acquisition mechanism that minimizes a destination platform’s AoI cost plus payments while ensuring the truthfulness and incentives for the data sources.