The rapid development of cellular networks has been urged by the introduction of 3rd Generation (3G) wireless technologies, significantly boosting Ethiotelecom's energy usage and expenditures. Furthermore, mobile data explosion has occurred in recent decades because of an increase in the number of mobile users as well as the rise of bandwidth-hungry applications, hence aiming to utilize the available spectrum as eciently as possible is a good move. Many researches done on massive MIMO, spectrum sharing, device to device communication (D2D) and GREEN communication shows significant attention in aiding spectrum utilization along with power optimization. In this thesis, motivated by the development of a new Ethiotelecom's business model, infrastructure sharing, which allows emerging MNOs to have their trace served by other MNOs in the same geographic area, allowing them to share a portion of their network is investigated. This thesis work presents a social dilemma game theoretic framework that allows MNOs to share a portion of their network. Sequential social dilemma and particles swarm algorithm are implemented on Open AI Gym based adaptable frame work. The algorithm is implemented and optimized for 3 mobile network operator (N = 3), 3 base station sites with 3, 9 and 30 mobile users. Simulation result shows users are connected/linked to nearby base station considering optimization of the utility (reward) function of the MNO (Game players), distance between mobile users and base station sites when the proper cell allocates enough resources. The performance of our simulation is visualized by generating various hypothetical cellular network environments with different number of cell sites and mobile users. A more optimal solution is obtained by adding a particle swarm optimization over it. Simulation results are promising and provide a better direction to the future work.