Channel Allocation for Mega LEO Satellite Constellations in the MEO–LEO Networked Telemetry System

Abstract

Recently, numerous mega LEO satellite constellation plans have emerged as an indispensable part supporting the future 6G satellite communications. Since the traditional telemetry systems are inappropriate for monitoring the operation status of all satellites, a networked telemetry system is adopted to achieve full time, low delay telemetry for mega LEO satellite constellations, which is a significant scenario of satellite Internet of Things. Furthermore, this article formulates a channel allocation problem to maximize the overall transmitted data amount. Adopting the dual decomposition method, this problem can be decomposed and transformed into a dual problem and multiple path scheduling subproblems for each LEO satellite. This article develops an optimal dynamic programming algorithm to solve the path scheduling subproblems and an iterative algorithm to solve the channel allocation problem. Numerical simulations show that the proposed channel allocation algorithm improves the transmitted data amount and approximates the upper bound performance.