# Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network
## 1 Introduction  
The concept of non-terrestrial networks (NTNs) that are capable of providing wireless communication coverage in complex and non-ideal environments is a popular topic, especially for conditions where a reliable means of wireless connections for time-critical tasks is urgently needed. Previously, wireless cellular communication services were designed to offer coverage to human users with smart phones or other portable devices; however, recently, machine-type communication is also in significant demand, such as with internet of things (IoT) devices and machine-type communication (MTC) devices. The demand for communication services further drives network evolution and expansion into non-traditional areas such as industry applications, remote surgery, AR/VR and so on [1; 2; 3; 4; 5; 6]. Unmanned autonomous Intelligent system (UAISs), such as self-driving vehicles,multi-robot systems, unmanned aerial vehicles, and unmanned ground vehicles have experienced increasing demand in terms of ubiquitous wireless connection requirements to fulfill tasks such as perception, localization, navigation, collaboration with nearby agents in a multi-agent system, and the offload of computation-intensive tasks to back-end or resource-abundant facilities [7]. In recent years, the development of unmanned aerial vehicles (UAVs) and satellites has brought about extensive opportunities for NTN applications with low cost and deployment flexibility. Furthermore, 4G/5G infrastructural deployments on the ground have steadily increased across the globe, with numerous cellular base stations around cites and along highways. However, in remote or unreachable regions, such as deserts and mountainous areas, ground cellular network coverage is not available due to high cost or environment limitations [8; 9; 10; 11; 12]. In addition, the use of NTNs is beneficial when ground networks are overloaded during special events like sports games or due to the sudden failure of base station infrastructure due to natural disasters in specific areas. Therefore, in the scenarios mentioned above, non-terrestrial networks (NTNs) are a promising solution for providing communication coverage in areas that are unable to be covered via traditional ground infrastructure. In some cases, especially in conditions such as power failures caused by disasters or a sudden increase in the number of users, the need for ubiquitous network access can only be met using non-terrestrial communication methods such as unmanned aerial vehicles (UAVs) or satellites [13; 14; 15; 16; 17; 18]. Owing to the extensive applications of UAIS in conjunction with 6G NTN communications, ranging from autonomous self-driving vehicles, unmanned aerial vehicles to multi-purpose robots for precise agriculture and disaster rescue scenarios. Efforts have been made in research toward 6G and beyond NTN technology to provide connectivity and intelligence. Therefore, a comprehensive and in-depth review of 6G NTN technology from the perspective of unmanned autonomous intelligent systems is crucial for undertaking further research in this domain. Numerous publications concerning the challenges and opportunities of UAIS in NTNs have been presented. However, the present work mostly emphasizes NTN communication itself or applications in a particular domain, such as intelligent transportation systems, autonomous vehicles and unmanned aerial vehicles. A systematic review of the existing work related to various UAIS in 6G NTN is required. The purpose of the paper is to provide a systematic review of the current trends and state of the art of UAIS in the context of 5G/6G NTN communication. We will discuss the role of UAVs in NTN communications and provide a comprehensive summary of various UAIS applications in UAV NTN, including unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), and connected and automated vehicles (CAVs). The rest of the paper is organized as follows. Firstly, in Section 2, the current status and development of NTN are analyzed.