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Research on Novel Type of Non Terrestrial Network Architecture for 6G

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... The study into NTN cooperation with the TN network progresses towards the definition of workable architecture between both. The prominent candidate of NTN technology is satellite technology, and multiple integration types are discussed in [11]. The 3GPP in Release 17 (R17) specified the enhanced functions for the foundational technologies that include coverage and capacity. ...
... The 3GPP in Release 17 (R17) specified the enhanced functions for the foundational technologies that include coverage and capacity. Specifically, the integrated satellite-terrestrial network (ISTN) proposed in [11] provides a novel ISTN architecture for different scenarios. Ref. [11] also highlights the challenge of coordinating unified technical standards to enable ISTN because of the uncertain time of 6G commercialization and the reconciliation efforts within the satellite industry. ...
... Specifically, the integrated satellite-terrestrial network (ISTN) proposed in [11] provides a novel ISTN architecture for different scenarios. Ref. [11] also highlights the challenge of coordinating unified technical standards to enable ISTN because of the uncertain time of 6G commercialization and the reconciliation efforts within the satellite industry. Ref. [12] performs a survey and highlights the challenges involved in the ISTN categorically from the network architecture, technical performance, and optimization together with the findings of key technology enablers to successfully have ISTN for 6G. ...
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Machine learning is taking on a significant role in materializing a new vision of 6G. 6G aspires to provide more use cases, handle high-complexity tasks, and improvise the current 5G and beyond 5G infrastructure. Artificial Intelligence (AI) and machine learning (ML) are the optimal candidates to support and deliver these aspirations. Traffic steering functions encompass many opportunities to help enable new use cases and improve overall performance. The emergence and advancement of the non-terrestrial network is another driving factor for creating an intelligence selection scheme to have a dynamic traffic steering function. With service-based architecture, 5G and 6G are data-driven architectures that use massive transactional data to emerge a new approach to handling highly complex processes. A highly complex process, a massive volume of data, and a short timeframe require a scheme using machine learning techniques to resolve the challenges. In this paper, the study creates a scheme to use the massive historical data and provide a decision scheme that enables dynamic traffic steering functions addressing the future emergence of the heterogeneous transport network and aligns with the Open Radio Access Network (O-RAN). The proposed scheme in this paper gives an inference to be programmed in the telecommunication nodes. It provides a novel scheme to enable dynamic traffic steering functions for the 6G transport network. The study shows an appropriate data size to create a high-performance multi-output classification model that produces more than 90% accuracy for traffic steering functions.
... NTN communication expands the application of 5G communication from terrestrial communication to space/air communication. The transformative advancement in communication technology promoted the shift from fifth-generation communication to sixth-generation, which highlights the vision of ubiquitous networks and space-air-ground coverage [24][25][26][27]. NTN technology represents new prospects in wireless communication applications such as satellite communications and low-altitude communication utilizing unmanned aerial vehicles and airships for internet of things devices or autonomous systems. ...
... NTN communication expands the application of 5G communication from terrestrial communication to space/air communication. The transformative advancement in communication technology promoted the shift from fifth-generation communication to sixth-generation, which highlights the vision of ubiquitous networks and space-air-ground coverage [24][25][26][27]. ...
... In addition, driven by the requirements of time-sensitive missions of UAIS, massive data generated from UAIS must be processed as quickly as possible. Therefore, non-terrestrial communicationsbased multi-access edge computing is essential and requires the help of UAVs to build high-speed links between UAIS users and UAVs [25][26][27]. Depending on the role of UAIS platforms in NTNs, the architecture of NTNs can be defined as follows: ...
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Non-terrestrial network (NTN) is a trending topic in the field of communication, as it shows promise for scenarios in which terrestrial infrastructure is unavailable. Unmanned autonomous intelligent systems (UAISs), as a physical form of artificial intelligence (AI), have gained significant attention from academia and industry. These systems have various applications in autonomous driving, logistics, area surveillance, and medical services. With the rapid evolution of information and communication technology (ICT), 5G and beyond-5G communication have enabled numerous intelligent applications through the comprehensive utilization of advanced NTN communication technology and artificial intelligence. To meet the demands of complex tasks in remote or communication-challenged areas, there is an urgent need for reliable, ultra-low latency communication networks to enable unmanned autonomous intelligent systems for applications such as localization, navigation, perception, decision-making, and motion planning. However, in remote areas, reliable communication coverage is not available, which poses a significant challenge for intelligent systems applications. The rapid development of non-terrestrial networks (NTNs) communication has shed new light on intelligent applications that require ubiquitous network connections in space, air, ground, and sea. However, challenges arise when using NTN technology in unmanned autonomous intelligent systems. Our research examines the advancements and obstacles in academic research and industry applications of NTN technology concerning UAIS, which is supported by unmanned aerial vehicles (UAV) and other low-altitude platforms. Nevertheless, edge computing and cloud computing are crucial for unmanned autonomous intelligent systems, which also necessitate distributed computation architectures for computationally intensive tasks and massive data offloading. This paper presents a comprehensive analysis of the opportunities and challenges of unmanned autonomous intelligent systems in UAV NTN, along with NTN-based unmanned autonomous intelligent systems and their applications. A field trial case study is presented to demonstrate the application of NTN in UAIS.
... UAM communication systems must adapt to the unique challenges posed by the operating environment [13]. They must ensure uninterrupted service across urban [14], rural, or remote terrains at a typical altitude range of 600 to 5000 feet, even necessitating transitions to satellite communications (SATCOM) when terrestrial networks are unavailable [15][16][17]. Introducing SATCOMs also brings many challenges, including interference management and resource optimization [18][19][20][21]. High-speed UAV operation requires the system to accommodate Doppler shifts without failure. ...
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This paper presents an analytical exploration of sixth-generation (6G) satellite–terrestrial integrated networks, focusing specifically on their applications within air mobility operations, such as those involving unmanned aerial vehicles (UAVs). As the integration of satellite and terrestrial networks promises to revolutionize mobile communication by extending coverage and enhancing connectivity, this study delves into two critical aspects: link budget analysis and handover and mobility analysis for UAVs. The link budget analysis assesses the communication requirements necessary to ensure robust and consistent connectivity between satellites and UAVs, accounting for factors such as path loss, antenna gains, and power transmission. Meanwhile, the handover and mobility analysis investigates the challenges and solutions associated with UAVs transitioning between different network nodes and layers in a dynamic aerial environment. This paper utilizes theoretical models and simulations to provide insights into the design and optimization of these networks, aiming to enhance the reliability and efficiency of UAV operations in the context of the emerging 6G landscape. The findings propose not only technological advancements in network architecture but also practical guidelines for the deployment of UAVs in complex environments, marking a significant step toward the realization of a fully integrated, satellite-terrestrial ecosystem.
... Beyond 5G and 6G, next-generation wireless network technologies have attracted attention. Beyond 5G and 6G include the requirement of extending the communication area to the sea, sky, and space, which is different from a terrestrial network [2][3][4][5][6][7][8][9][10][11]. Communication networks that satisfy these requirements are called non-terrestrial networks (NTN) [12][13][14][15][16][17][18]. ...
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Networks constructed in the sky are known as non-terrestrial networks (NTNs). As an example of an NTN, relay transmission using drones as radio stations enables flexible network construction in the air by performing handovers with ground stations. However, the presence of structures or obstacles in the flight path causes multipath interference; consequently, the propagation environment fluctuates significantly based on the flight. In such a communication environment, it is difficult for a drone to select an optimal ground station for a handover. Moreover, unlike a terrestrial network, the propagation environment of a flying drone is affected by structures and other factors that cause multipaths based on the flight speed and altitude, making the conditions of the propagation environment even more complex. To solve these problems, we propose handover schemes between drones and the ground that consider the multipath interference caused by obstacles. The proposed methods are used to perform handovers based on an optimal threshold of received power considering interference and avoid unnecessary handovers based on the moving speed, which makes the handover seamless. Finally, we develop a simulator that evaluates the cross layer from propagation to upper network protocols in a virtual space, including buildings, evaluate the communication quality of a drone flying in a three-dimensional space, and confirm the effectiveness of the proposed methods as well as the evaluation of the real environment.
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Overlay satellite-terrestrial networks for iot under hybrid interference environments
  • sharma
Overlay satellite-terrestrial networks for iot under hybrid interference environments
  • P K Sharma
  • B Yogesh
  • D Gupta
  • D I Kim