Abstract
Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.
Highlights
Rapid proliferation of intelligent objects in the Internet of Things (IoT) brings a tremendous data traffic increase in 5G and beyond networks
In Reference [19], cooperative game theory is utilized for solving the fair-awareness resource sharing problem in 5G environments and Xie et al [20] address the caching resource allocation problem based on a competitive game
We can study the follower game with two classes of users; users covered by multi-networks and the other users covered only by one network
Summary
Rapid proliferation of intelligent objects in the Internet of Things (IoT) brings a tremendous data traffic increase in 5G and beyond networks. Numerous works have been conducted to solve the above issues, especially game-based methods, proving to be efficient and practical for improving the allocation of limited resources in realistic situations, where the strategies of mobile users or networks are interacted with mutually. Zhang et al [2] propose a potential game-based distributed resource allocation optimization algorithm in HetNets with mobile edge computing. In Reference [19], cooperative game theory is utilized for solving the fair-awareness resource sharing problem in 5G environments and Xie et al [20] address the caching resource allocation problem based on a competitive game. In order to solve the realistic problem that game players, i.e., the HetNets and mobile users in this paper, cannot acquire complete information about others, a distributed pricing and resource allocation method, based on the Stackelberg game with incomplete information, is proposed in this paper.
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