Knee point driven Evolutionary Algorithm with MIMO satellite uplink Multi objective optimization

Low-orbit satellite constellations, with short communication delay, low power consumption, and high information transmission rate, are the core of next-generation communication technology. But they have many satellites, so ground measurement and control stations need MIMO to register multiple satellites. Allocating energy and spectrum, reducing co-channel interference and information leakage while ensuring satellite info rates is a difficult problem. This paper proposes a knee-driven multi-objective optimization method (KnEA) for this problem. First, it models high-dimensional multi-objective dominance in MIMO satellite uplinks and calculates knee points. Using crowded distance for comparison, it jointly optimizes energy and spectral efficiency, transmission quality, and security in MIMO satellite links. Compared with mainstream algorithms, the KnEA algorithm has better convergence and distribution, and better system performance.