# Resource Mapping Allocation Scheme in 6G Satellite Twin Network
## 2 Related Work  
With the development of 6G, there are a large number of complex and diverse application scenarios for future 6G mobile communication systems to provide users with an extreme performance experience. For the complex 6G satellite twin network, accurate extrapolation of network performance requires system-level simulation, as well as carefully designed simulation scenarios to better understand the impact of complex relationships between system configuration parameters and corresponding network operations [35]. A semi-physical simulation system is constructed in [36], which uses a server to simulate a satellite and relies on cables and servers to model the channel of the satellite network. The coordinate model to reduce the communication latency of low Earth orbit (LEO) satellites is proposed. However, a large number of servers are required to simulate large-scale constellations under this architecture, which is costly to build. A fifth generation (5G) system-level simulation platform that meets the requirements of IMT-2020 is produced in [1], and its simulation results are verified by the 3 rd Generation Partnership Project (3 GPP) calibration and published. The modeling of the MAC layer in satellite communications is described in [37; 38]. An event-driven satellite performance simulation framework is introduced to simulate the dynamic behavior of the network in the Brazilian region. The user's operation scenarios are customized in combination with collision detection and different coverage scenarios, but this framework is difficult to scale. The challenges of building a 5G simulation platform based on 4G evaluation methods are described in [39], where a cloud-based framework for a two-level system-level simulation platform framework is proposed and novel techniques in 5G are validated in this platform. A 5G terrestrial system-level simulation platform is introduced in [2], which tests the performance of large-scale multiple-in multiple-out (MIMO) in 5G by varying the number of antenna ports and the number of spatial multiplexing layers in different experimental environments, focusing on the effect of vertical beamforming on full-dimensional MIMO interference, demonstrating that the modular and flexible platform structure is easy to reconfigure and simulate. However, the above simulation platforms are all separate satellite systems or ground systems. The 6 Gnetwork has flexible and variable protocol stack functions and network architecture, which requires a scalable, multi-compatible, and highly flexible system-level platform for network simulation. In addition, to guarantee transmission stability for the 6G satellite network, low-density parity-check (LDPC) codes and polar codes are selected as the error-correction codes in 5G mobile communications and a lot of standards [40; 41; 42]. For large-scale simulation systems, some ideas are proposed in current research. A fast, scalable, and parallel simulator to accelerate the simulation of multicore co-processors on a graphics processing unit (GPU) platform is proposed in [43], but this platform depends on hardware conditions. A docker container-based software-as-a-service system is described in [44]. The study demonstrates the feasibility of emulating complete packet-level transmission and protocols on a serverless platform with built-in docker containers and proposes a generic queueing network approach to model the deployment behavior of application-layer software-as-a-service. A serverless cloud computing framework in which applications are modeled as functions of different granularity is proposed in [45]. These functions interact with each other to implement complex task processes. Serverless platforms are mainly used for stateless, data-parallel tasks, and the study verifies the advantages of serverless platforms in solving large-scale optimization problems [46]. For resource allocation of large-scale simulation systems, several studies have been proposed.