Bayesian Coalition Game for Overlay D2D Spectrum Sharing in Cellular Networks

In this paper, we present a Bayesian coalition game model for spectrum sharing in order to increase the overall spectrum resource capacity in a cellular network with device-to-device (D2D) communication capabilities. The coalition game is used to enforce cooperation among D2Ds competing for the use of the limited spectrum resource. In this paper, D2D users can access the network in an overlaid mode and share their allocated sub-bands with other D2D users using the proposed game which enables coalition formation that guarantee an optimal rate for all users in the network. The paper establishes sufficient conditions needed for stability in the coalitions formed and present simulation results to show that it is possible to increase the overall capacity of the D2D-enabled cellular network without reducing the performance of the licensed cellular users using the proposed game. D2D spectrum sharing using our proposed algorithm was compared with spectrum sharing using the random pairing method to validate our game model. Results show that there was a 44% and 36% increase in cell sum-rate, when our proposed sub-band allocation game was deployed compared to the random pairing method, for the 50 and 100 cells respectively. The proposed sub-band allocation game also performed better with an increased number of users in the network because of the effective coordination offered by the algorithm.Keywords— Cellular, coalition game, D2D, overlay, spectrum.

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A multi-responsibility–oriented coalition formation framework for dynamic task allocation in mobile–distributed multi-agent systems

International Journal of Advanced Robotic Systems ◽

10.1177/1729881418813037 ◽

2018 ◽

Vol 15 (6) ◽

pp. 172988141881303 ◽

Cited By ~ 1

Author(s):

Bing Xie ◽

Xueqiang Gu ◽

Jing Chen ◽

LinCheng Shen

Keyword(s):

Coalition Formation ◽

Task Allocation ◽

Game Model ◽

Multi Agent Systems ◽

Coalition Game ◽

Task Execution ◽

Agent Systems ◽

Dynamic Task ◽

Dynamic Task Allocation ◽

Multi Agent

In this article, we study a problem of dynamic task allocation with multiple agent responsibilities in distributed multi-agent systems. Agents in the research have two responsibilities, communication and task execution. Movements in agent task execution bring changes to the system network structure, which will affect the communication. Thus, agents need to be autonomous on communication network reconstruction for good performance on task execution. First, we analyze the relationships between the two responsibilities of agents. Then, we design a multi-responsibility–oriented coalition formation framework for dynamic task allocation with two parts, namely, task execution and self-adaptation communication. For the former part, we integrate our formerly proposed algorithm in the framework for task execution coalition formation. For the latter part, we develop a constrained Bayesian overlapping coalition game model to formulate the communication network. A task-allocation efficiency–oriented communication coalition utility function is defined to optimize a coalition structure for the constrained Bayesian overlapping coalition game model. Considering the geographical location dependence between the two responsibilities, we define constrained agent strategies to map agent strategies to potential location choices. Based on the abovementioned design, we propose a distributed location pruning self-adaptive algorithm for the constrained Bayesian overlapping coalition formation. Finally, we test the performance of our framework, multi-responsibility–oriented coalition formation framework, with simulation experiments. Experimental results demonstrate that the multi-responsibility oriented coalition formation framework performs better than the other two distributed algorithms on task completion rate (by over 9.4% and over 65% on average, respectively).

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Coalition Game Model of FANET Grouping Control Based on the Method of Local Threats and Counter-Threats and Swarm-Leader Model

Studies in Systems, Decision and Control - Smart Electromechanical Systems ◽

10.1007/978-3-030-68172-2_13 ◽

2021 ◽

pp. 151-162

Author(s):

Evgeny M. Voronov ◽

Vladimir A. Serov ◽

Dmitry A. Kozlov

Keyword(s):

Game Model ◽

Coalition Game

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The three kinds of degree distributions and nash equilibrium on the limiting random network

Stochastics and Dynamics ◽

10.1142/s0219493720500331 ◽

2019 ◽

Vol 20 (05) ◽

pp. 2050033

Author(s):

Dong Han ◽

Min Xia

Keyword(s):

Nash Equilibrium ◽

Random Network ◽

Sufficient Conditions ◽

Curved Surface ◽

High Dimensional ◽

Game Model ◽

Curved Surfaces

A generalized dynamically evolving random network and a game model taking place on the evolving network are presented. We show that there exists a high-dimensional critical curved surface of the parameters related the probabilities of adding or removing vertices or edges such that the evolving network may exhibit three kinds of degree distributions as the time goes to infinity when the parameters belong to the super-critical, critical and sub-critical curved surfaces, respectively. Some sufficient conditions are given for the existence of a regular Nash equilibrium which depends on the three kinds of degree distributions in the game model on the limiting random network.

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