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The multiple-user terminals in a satellite transponder’s communication channel compete for limited radio resources to meet their own data rate needs. Because inter-user interference limits on the satellite transponder’s performance, the transponder’s power-control system needs to coordinate all its users to reduce interference and maximizes overall performance of this channel. This paper studies Stackelberg competition among the asymmetrical users in a transponder’s channel, where some users called leader have priority to choose their power control strategy, but other users called followers have to optimize their power control strategy with given leader’s controls. A Stackelberg Differential Game (SDG) is set up to model the Stackelberg competition in a transponder’s communication channel. Each user’s utility function is a trade-off between transmission data rate and power consumption. The dynamics of the system is the changing of channel gain. The optimality condition of Stackelberg equilibrium of leaders and followers is a set of Differential Algebraic Equations (DAE) with an imbedded control strategies from its counterpart. In order to solve for Stackelberg equilibrium, an algorithm based on optimizing leaders’ and followers’ Hamiltonians iteratively is developed. The numerical solution of the SDG model provides the transponder’s power control system with each user’s power-control strategy at the Stackelberg equilibrium.
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Maintaining Information Freshness under Jamming
In UAV communication with a ground control station, mission success requires maintaining the freshness of the received information, especially when the communication faces hostile interference. We model this problem as a game between a UAV transmitter and an adversarial interferer. We prove that in contrast with the Nash equilibrium, multiple Stackelberg equilibria could arise. This allows us to show that reducing interference activity in the Stackelberg game is achieved by higher sensitivity of the transmitter in the Stackelberg equilibrium strategy to network parameters relative to the Nash equilibrium strategy. All the strategies are derived in closed form and we establish the condition for when multiple strategies arise.
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- Award ID(s):
- 1717041
- PAR ID:
- 10109345
- Date Published:
- Journal Name:
- IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/INFCOMW.2019.8845146
