Non-uniform Pricing and Resource Allocation Economics for HetNet Based on Stackelberg Game

Efficient resource allocation in cognitive radio network (CRN) remains a challenge due to dynamic nature of available spectrum in working band and implementation in nano-computing environment. Adoption of game theory in power allocation based on pricing model requires the formulation of strategy of the players as profit/loss function which may lead to Nash equilibrium. Earlier research focuses on the impact of game models such as Cournot, and Bertrand in formulating the utility function under the constraint power and service quality. In Cournot and Bertrand game the users play simultaneously that may not be acquainted with the other user’s action. It suits for common regimes such as all user are to be unlicensed (SU) and they may simultaneously try to access a set of available channels. In this paper, we formulate the condition for optimal power allocation in CRN using Stackelberg game where the previous user decides its output and then the erstwhile user does so, knowing the output characteristics by the former user. Based on the profit of PU (as a leader) and SU (as a follower), the optimized solution is formulated for power and interference price and it is modelled as a convex function of transmission power achieved by Nash equilibrium which involves backward induction. By means of a uniform pricing scheme every PU aims to maximize its profit under channel data rate and interference power constraint. The proposed Resource Allocation using Stackelberg Game (RASG) algorithm tries to optimize uniform pricing and power allocation among SUs such that maximizing throughput and fairness. The simulation results show a significant enhancement in throughput and fairness compared to power optimization based on Bertrand and Cournot game theory.

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Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

Applied Sciences ◽

10.3390/app10051557 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1557

Author(s):

Weijia Feng ◽

Xiaohui Li

Keyword(s):

Resource Allocation ◽

Incomplete Information ◽

Stackelberg Game ◽

Superior Performance ◽

Channel Gain ◽

Mobile Users ◽

Pricing Strategies ◽

Game Equilibrium ◽

Allocation Process ◽

Realistic Situation

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.

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Resource Allocation Algorithms of Vehicle Networks with Stackelberg Game

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications ◽

10.1007/978-3-030-48513-9_18 ◽

2020 ◽

pp. 221-230

Author(s):

Ying Zhang ◽

Guang-Shun Li ◽

Jun-Hua Wu ◽

Jia-He Yan ◽

Xiao-Fei Sheng

Keyword(s):

Resource Allocation ◽

Stackelberg Game ◽

Vehicle Networks ◽

Allocation Algorithms

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Dynamic SPICE-model of resource allocation in marketing networks

Contributions to Game Theory and Management ◽

10.21638/11701/spbu31.2020.02 ◽

2020 ◽

Vol 13 ◽

pp. 8-23

Author(s):

Movlatkhan T. Agieva ◽

◽

Olga I. Gorbaneva ◽

Keyword(s):

Resource Allocation ◽

Stackelberg Game ◽

Target Audience ◽

Opinion Leaders ◽

Stackelberg Equilibrium ◽

Common Interest ◽

Theoretic Model ◽

Goods And Services ◽

Spice Model ◽

Private Interests

We consider a dynamic Stackelberg game theoretic model of the coordination of social and private interests (SPICE-model) of resource allocation in marketing networks. The dynamics of controlled system describes an interaction of the members of a target audience (basic agents) that leads to a change of their opinions (cost of buying the goods and services of firms competing on a market). An interaction of the firms (influence agents) is formalized as their differential game in strategic form. The payoff functional of each firm includes two terms: the summary opinion of the basic agents with consideration of their marketing costs (a common interest of all firms), and the income from investments in a private activity. The latter income is described by a linear function. The firms exert their influence not to all basic agents but only to the members of strong subgroups of the influence digraph (opinion leaders). The opinion leaders determine the stable final opinions of all members of the target audience. A coordinating principal determines the firms' marketing budgets and maximizes the summary opinion of the basic agents with consideration of the allocated resources. The Nash equilibrium in the game of influence agents and the Stackelberg equilibrium in a general hierarchical game of the principal with them are found. It is proved that the value of opinion of a basic agent is the same for all influence agents and the principal. It is also proved that the influence agents assign less resources for the marketing efforts than the principal would like.

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