Multi-objective Resource Optimization in Space-Aerial-Ground-Sea Integrated Networks

Sixth-generation (6G) networks envision space-air-ground-sea integrated (SAGSI) networks connecting satellite, aerial, ground, and sea networks to provide constant connectivity. A mathematical framework for maximizing energy efficiency, resource utilization, and user association in SAGSI networks is formulated. Different algorithms are analyzed to optimize user association while satisfying transmit power, data rate, and computation resources constraints. The binary decision variable associates users with ground, aerial, or satellite networks. Since the decision variable is binary and constraints are linear, the formulated problem is a binary linear programming problem. To solve the formulated optimization problem using the branch and bound algorithm (BBA), interior point method (IPM), and barrier simplex algorithm (BSA). The results for BBA are used as a benchmark to evaluate the performance of the other two algorithms. Simulation results show that the performance of IPM and BSA is comparable to the BBA with low complexity.