# Research on Key Technologies of Elastic Satellite Optical Network Based on Optical Service Unit
## 1 Introduction  
The low Earth orbit (LEO) Internet constellation represents a critical strategic infrastructure for the 6G space-terrestrial-sea three-dimensional network. The intrinsic characteristics of transparent forwarding and high mobility introduce substantial complexity to maintaining stable quality of service in traditional network architectures, thereby presenting significant challenges to the deployment and advancement of delay-sensitive space-based applications [1, 2, 3]. Consequently, the evolution of service and data forwarding paradigms within satellite networks has become an inevitable trend to enhance the service capabilities of space-based networks. Investigating deterministic networking technology is crucial for improving the service quality of LEO satellite optical networks, ensuring national infrastructure security, and expanding information coverage capabilities. In the literature [4, 5], the concept of a novel optical service unit (OSU) and its associated requirements are introduced, with detailed descriptions of the primary technical elements of OSUs provided. In 2024, the China Communications Standards Association (CCSA) established an industry standard for OSUs [6]. Subsequently, China TELECOM developeda metro-optimized optical transport network (M-OTN) based on an OSU, enabling flexible transport for sub-1G applications [7; 8]. Furthermore, the 6G network system must consider multiple scheduling factors, including business requirements, network resources, and equipment energy consumption. Different services impose distinct quality-of-service (QoS) requirements, such as latency, jitter, isolation, security, and robustness [9], necessitating customized network communication and computational power supply solutions. Since then, researchers have been dedicated to exploring the potential scalability of OSUs in space-terrestrial networks. An AI-augmented hybrid framework has been proposed, integrating deep reinforcement learning (DRL) for adaptive network slicing and graph neural networks (GNNs) for autonomous self-healing, to facilitate joint resource-service orchestration in the intelligent evolution of 5G [10]. As demonstrated in our prior work, integrated satellite routing optimization algorithms leveraging OSUs and DRL methodologies, such as the depth deterministic policy gradient (DDPG), have been devised to address challenges related to resource allocation and cross-orbit traffic scheduling in multi-satellite networks [11]. The technical evolution of satellite optical networking, from IP (shared resource architecture), through OTNs (physical isolation architecture), to all-optical architecture (pure photonic operation) are summarized in Table 1.  
Currently, there exist several critical challenges in Internet protocol (IP)-based satellite optical networks:  
1. For IP over Consultative Committee for Space Data Systems (IPoC), IP-based optical satellite networks typically do not incorporate bandwidth resource information into their design;
2. IPoC fails to establish the transmission of overhead information, thereby precluding integration across physical, application, and network management layers, which hinders the realization of an intelligent network architecture;
3. Packet-forwarding optical satellite networks lack interoperability with terrestrial OTNs. To address these challenges, we propose an innovative satellite optical network architecture leveraging optical inter-satellite links based on OSU infrastructure, referred to as OISL-OSU. The primary contributions are summarized as follows:  
1. Considering the instability of the inter-satellite wireless communication environment, Reed-Solomon (RS(255,223)) coding is employed to enhance forward error correction