Abstract: To address the challenges of frequent link disruptions, long route recovery delays, and poor reliability of traditional single-path routing protocols in low earth orbit satellite networks, this paper constructs a network model that integrates orbital dynamics with link-state awareness and proposes an adaptive routing optimization method based on the multipath ad hoc on-demand distance vector (MAODV) protocol. The proposed method employs an on-demand route discovery mechanism to simultaneously acquire and maintain multiple feasible paths during distance-vector propagation, thereby forming a candidate path set. By further considering link availability fluctuations induced by orbital dynamics, cross-layer parameters—including hop count, link quality, node load, and residual energy—are collected in real time to construct a comprehensive path cost metric, which is used to select both primary and backup paths that are better suited to highly dynamic topologies. A joint simulation environment is established using MATLAB and STK (Satellite Tool Kit), and comparative experiments with representative routing protocols are conducted to evaluate the performance of the proposed method. Simulation results demonstrate that, under identical constellation and traffic conditions, the proposed method achieves average throughput improvements of approximately 4.29%, 4.77%, and 3.82% over the ad hoc on-demand distance vector (AODV), dynamic source routing (DSR), and optimized link state routing (OLSR) protocols, respectively. Moreover, the average end-to-end delay is significantly reduced compared with these baseline protocols, thereby confirming the effectiveness of the proposed approach in dynamic LEO satellite network scenarios.

Key words: low earth orbit (LEO), satellite network, ad hoc on-demand distance vector (AODV) routing protocol, multipath routing, load balancing