Evolutionary Stable Strategy-Enabled Resource Allocation in 6G: A Strategy Integration-Based Game Theoretic Approach

In the rapidly advancing era of 6 G networks, an efficient resource allocation (RA) is necessitated. Consequently, our paper reveals a sophisticated mathematical model based on evolutionary game theory and replicator dynamics designed to optimize and stabilize resource distribution. The model delineates how evolutionary stable strategies (ESS) can be systematically identified and employed to enhance network efficiency and fairness significantly. Further, strategic interaction analysis and dynamic modeling integration demonstrate that ESS respond adeptly to changing network conditions and robustly guards against inefficiencies caused by signal degradation and user demand variability. Furthermore, we proposed a few algorithms, such as ESS sustainability and stabilization criteria for ESS, to depict the change in strategy population, which turns into the strategy fitness change and convergence of strategic population, respectively. Lastly, our empirical simulations validate the model’s effectiveness in fostering resilient and equitable RA, setting a foundation for future 6G network designs prioritizing adaptability and sustainability. In conclusion, our paper aims to highlight the innovative approach succinctly, as well as the theoretical foundation and practical outcomes of our research, focusing on engaging and addressing a more expansive audience effectively in the upcoming era of next-generation communication technologies.