To address the spectrum resource contention issue in heterogeneous wireless networks, a priority-based spectrum interference analysis and adaptive optimization method is proposed. A dual-layer heterogeneous communication system model considering spatiotemporal characteristics is constructed. An interference quantification mechanism integrating time-frequency overlap and Signal-to-Interference Ratio(SIR) evaluation is established, and a weighted interference evaluation model accounting for device priority is proposed. On this basis, a parameter-adaptive Particle Swarm Optimization(PSO) algorithm is designed to achieve dynamic optimal allocation of spectrum resources. Simulation results demonstrate that the proposed method reduces the overall system interference level by an average of 63.3% while ensuring the communication quality of high-priority devices, with the suppression effect on severe interference reaching 81.4%. Compared with existing methods, the proposed approach exhibits significant advantages in both interference suppression and computational efficiency, providing a novel technical solution for spectrum management in complex electromagnetic environments.