Cooperative communication resources scheduling of satellite network using a mixed vector encoding heuristic algorithm - Jiaxuan Xie; Linling Kuang; Shan Gao (Intelligent and Converged Networks, 2025)
The communication resources scheduling problem of the satellite network contains the user-satellite association problem, the user-beam matching problem, and the beam power allocation problem. Different optimization problems contain different types of variables. Mult-type variables and three coupling problems cause the cooperative scheduling problem to be complex. In this paper, we propose a mixed vector encoding heuristic algorithm (MVEHA) to optimize the joint resources allocation problem of the multiple beams satellite network. Specifically, we use the 0-1 encoding vector to represent the user-satellite association scheme, the user-beam matching scheme is denoted by the continuous vector with priority, and a normalization vector is designed to encoded the beam power allocation scheme. Due to the mixed vector encoding method, we design two optimization operators to guide the search direction of the population. Compared to the conventional optimization algorithm, the simulation experiment shows MVEHA has better solution performance and robustness to solve the communication resources allocation problem of the satellite network.