Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization

In this paper, we design a novel architecture of distributed satellite cluster network (DSCN). In order to achieve a good trade-off between the energy consumption and the total capacity, we investigate the joint downlink power and time-slot allocation problem, taking into account the limitation of resource, collaborative coverage of multi-satellite, and dynamism, which is proved to be a Pareto optimization and NP-hard problem. Different from the existing 1-D multi-objective optimization algorithm (1D-MOA) based on meta-heuristics, such as immune clonal algorithm (ICA), we propose an improved 2-D dynamic immune clonal algorithm (TDICA) to search the solution space for approaching the Pareto front. From simulation results, several important concluding remarks are obtained as follows: 1) the proposed TDICA can obtain more non-dominated solutions in each iteration with better accuracy than existing algorithms; 2) with inter-satellite resource optimization, the total capacity can be improved; 3) compared with 1D-MOAs, the 2D-MOA can save more energy and achieve higher total capacity; d) MOAs can be transferred into multiple single-objective optimization algorithms (SOAs) under certain conditions.