Adaptive Spectrum Optimization Algorithm Inspired by 5G and 6G Communication Technologies

With the rapid development of fifth-generation (5G) and sixth-generation (6G) communication technologies, spectrum management, energy utilization, and low-latency optimization of communication systems have become research focuses. This paper proposes an adaptive spectrum optimization algorithm inspired by 5G and 6G communication mechanisms. This algorithm comprehensively considers channel state information, user density, bandwidth fluctuations, and dynamic interference factors, achieving optimal allocation of spectrum resources through a novel heuristic mathematical structure. The algorithm introduces a "quantitative cognitive potential field model," using the communication channel information entropy and distribution gradient to dynamically correct the spectrum allocation probability, thereby maintaining stable transmission rates and low latency even under high-load network conditions. This paper provides a detailed derivation of the algorithm's mathematical model, presents the dynamic optimization formula and convergence proof, and analyzes its complexity and communication characteristics at the theoretical level.