Joint Rate and Coverage Optimization for the THz/RF Multi-Band Communications of Space-Air-Ground Integrated Network in 6G

Space-air-ground integrated networks (SAGIN) incorporating multi-band terahertz (THz) and radio frequency (RF) communication have gained increasing attention in the 6G era. However, the heterogeneity, self-organization, and time-variability of SAGIN pose challenges in accurately modeling, quantitatively analyzing, and optimizing these networks. Additionally, the dynamic topology and randomness of the nodes, including low-earth orbit satellites and high-altitude platforms, make the conventional THz/RF channel allocation method of terrestrial networks unsuitable for SAGIN. To address these challenges, we construct an accurate model of SAGIN based on the binomial point process (BPP) model in stochastic geometry. Subsequently, we analyze the network performance, specifically the joint coverage and transmission rate, through the proposed model. We then propose a simulated annealing algorithm-based optimization algorithm to achieve the optimal THz and RF channel allocation, effectively improving the joint coverage and transmission rate performance. Our simulation results demonstrate the effectiveness of the optimization algorithm and provide insights into the deployment rules of SAGIN.