Game Theory Algorithms for Resource Allocation in 5G MIMO

Tsachrelias Konstantinos; Chrysostomos Athanasios Katsigiannis; Vasileios Kokkinos; Apostolos Gkamas; Christos Bouras; Philippos Pouyioutas

doi:10.3991/ijim.v19i13.56051

Game Theory Algorithms for Resource Allocation in 5G MIMO

Tsachrelias Konstantinos
, Chrysostomos Athanasios Katsigiannis
, Vasileios Kokkinos
, Apostolos Gkamas
, Christos Bouras
, Philippos Pouyioutas

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

Efficient resource allocation is essential in 5G MIMO networks due to increasing demands for high-quality communications. This paper compares four game theory algorithms: Stackelberg, Nash Bargaining, Mean Field Game, and Potential Game, evaluating their effectiveness in allocating resources dynamically. A simulation environment is developed to represent realistic user mobility by continuously updating user equipment (UE) positions. Each algorithm is assessed based on UE distribution, fairness, bandwidth consumption, and energy efficiency. The simulation results show clear differences among the algorithms, highlighting specific advantages and limitations that help inform resource allocation strategies in practical 5G network scenarios.

Original language	English
Pages (from-to)	183-203
Number of pages	21
Journal	International Journal of Interactive Mobile Technologies
Volume	19
Issue number	13
DOIs	https://doi.org/10.3991/ijim.v19i13.56051
Publication status	Published - 14 Jul 2025

Keywords

5G networks
Game theory
Mean Field Game
multiple input multiple output (MIMO)
Nash Bargaining
potential
resource allocation
Stackelberg

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3991/ijim.v19i13.56051

Cite this

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title = "Game Theory Algorithms for Resource Allocation in 5G MIMO",

abstract = "Efficient resource allocation is essential in 5G MIMO networks due to increasing demands for high-quality communications. This paper compares four game theory algorithms: Stackelberg, Nash Bargaining, Mean Field Game, and Potential Game, evaluating their effectiveness in allocating resources dynamically. A simulation environment is developed to represent realistic user mobility by continuously updating user equipment (UE) positions. Each algorithm is assessed based on UE distribution, fairness, bandwidth consumption, and energy efficiency. The simulation results show clear differences among the algorithms, highlighting specific advantages and limitations that help inform resource allocation strategies in practical 5G network scenarios.",

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AU - Bouras, Christos

AU - Pouyioutas, Philippos

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Game Theory Algorithms for Resource Allocation in 5G MIMO

Abstract

Keywords

UN SDGs

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