LAUSR

The ever-increasing densification of the low-Earth orbit constellation makes it possible to boost the data rate via multi-satellite cooperative transmission. However, the large spatial scale of satellite networks makes the time asynchrony non-negligible. In this paper, we exploit the asynchronous non-orthogonal transmission for multi-satellite cooperative communication to improve the fairness-aware rate. The asynchronous capacity is extended to the multi-satellite cooperation scenario and then utilized to formulate the optimization problem, which jointly considers the satellite-to-terminal association, power allocation, and decoding order. To dissect those coupled variables, we propose a preference-list-based algorithm that iterates between the following two stages. First, the many-to-many two-sided matching is solved by a Gale-Shapley algorithm based strategy given prespecified preference lists. Then, transmit power and decoding order are jointly optimized by a Dinkelbach-like algorithm. Based on the above results, the preference lists are updated to reflect the inter-satellite interference for iterative refinement. Simulation results show that introducing cooperative transmission improves the fairness rate by 12%, and exploiting time asynchrony provides another 7% gain.