Game Theory Algorithms for Resource Allocation in 5G MIMO

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.