Optimization of Wireless Network Performance Through Intelligent Resource Allocation: A Game Theory Approach

Increasing resources were allocated based on the demand for wireless network services. Game theory has recently been recognized as a potential solution for enhancing wireless networks by jointly optimizing resource allocation among users. Specifically, a common approach in this direction is to formulate wireless networks as multi-player games in which the users compete with each other for the available resources, e.g., bandwidth, power, time, etc. Applying the principles of game theory can lead to the creation of a Nash equilibrium, such that no one player can better their results if they change their strategy independently. Game-theoretic-based intelligent Resource Allocation Algorithms Enable This Type of Equilibrium, Whereby Users Employ Negotiation and Cooperation, Therefore Allocating Network Resources Efficiently and Achieving Higher Performance. A game theory approach for wireless network optimization: A technical paper By considering the changing network conditions along with user preferences, an efficient resource allocation method has been proposed. To do this, it intelligently schedules user transmissions, minimizing interference and maximizing throughput. Simulation results and experiments in the real world demonstrate that the game-theory unstable approach improves the performance of wireless networks over resource allocation based on classical methods. Furthermore, due to being scalable, robust, and resource-efficient, our approach can be deployed in different large-scale wireless networks. A part of this work is to implement smart allocation schemes of resource for wireless networks that will help to enhance more reliable and efficient wireless services in future.