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ETHER: Energy-and Cost-Efficient Framework for Seamless Connectivity over the Integrated Terrestrial and Non-terrestrial 6G Networks
Abstract
Several use cases already proposed for 5G networks cannot be facilitated by terrestrial infrastructure, either due to its small penetration in remote/rural areas or the harsh propagation conditions due to the terrain. Indicative applications include forestry, mining, agriculture, semi-autonomous control of long-range vehicles, industrial services, logistics, asset tracking, telemedicine, beyond visual-line-of-sight drone operations, and maritime insurance. Hence, such use cases necessitate the integration of terrestrial with non-terrestrial networks, which gives rise to several challenges to overcome. The project ETHER aims to provide a holistic approach for energy- and cost-efficient integrated terrestrial-non-terrestrial networks. To achieve this goal, ETHER develops solutions for a unified Radio Access Network and for Artificial Intelligence-enabled resource management across the terrestrial, aerial, and space domains while creating the business plans driving future investments. To that end, this paper discusses a series of key technologies that ETHER combines under a unique 3-Dimensional (3D) multi-layered architectural proposition that brings together: i) user terminal antenna design and implementation for direct handheld access in the integrated network, ii) a robust unified waveform, iii) energy-efficient seamless horizontal and vertical handover policies, iv) a zero-touch network/service management and orchestration framework, v) a flexible payload system to enable programmability in the aerial and space layers, vi) joint communication, compute, and storage resource allocation solutions targeting at end-to-end network performance optimisation leveraging novel predictive analytics, and vii) energy-efficient semantics-aware information handling techniques combined with edge computing and caching for reduced latency across the distributed 3D compute/storage continuum. The 3D ETHER architecture and the targeted use cases are also discussed, paving the way toward 6G networks.
... One of the key targets of the 6th Generation (6G) mobile network is ubiquitous coverage and broadband network access worldwide [1]. While extending the terrestrial infrastructure in remote locations is often infeasible due to financial, physical, or legal reasons, network omnipresence is expected to be achieved via the integration of Terrestrial Networks (TNs) and Non-Terrestrial Networks (NTNs) [2][3][4], including both aerial and satellite systems. Nowadays, carrier-grade aerial networks are largely limited and correspond mainly to High Altitude Platform Systems (HAPSs) or ad hoc networks based on Unmanned Aerial Vehicles (UAVs) (set up dynamically during natural disasters, mass events, etc.). ...
Ubiquitous connectivity is envisioned through the integration of terrestrial (TNs) and non-terrestrial networks (NTNs). However, NTNs face multiple routing and Quality of Service (QoS) provisioning challenges due to the mobility of network nodes. Distributed Software-Defined Networking (SDN) combined with Multi-Agent Deep Reinforcement Learning (MADRL) is widely used to introduce programmability and intelligent Traffic Engineering (TE) in TNs, yet applying DRL to NTNs is hindered by frequently changing state sizes, model scalability, and coordination issues. This paper introduces 3DQR, a novel TE framework that combines hierarchical multi-controller SDN, hierarchical MADRL based on Graph Neural Networks (GNNs), and network topology predictions for QoS path provisioning, effective load distribution, and flow rejection minimisation in future 3D networks. To enhance SDN scalability, introduced are metrics and path operations abstractions to facilitate domain agents coordination by the global agent. To the best of the authors’ knowledge, 3DQR is the first routing scheme to integrate MADRL and GNNs for optimising centralised routing and path allocation in SDN-based 3D mobile networks. The evaluations show up to a 14% reduction in flow rejection rate, a 50% improvement in traffic distribution, and effective QoS class prioritisation compared to baseline techniques. 3DQR also exhibits strong transfer capabilities, giving consistent performance gains in previously unseen environments.
... AI has transformed these domains by introducing techniques such as FL and secure multiparty computation (SMPC). These methods ensure robust privacy preservation while maintaining high performance in distributed environments [21]. FL enables the training of a global model without transferring raw data between nodes, thereby ensuring data privacy. ...
The seamless integration of terrestrial networks (TNs) and non-terrestrial networks (NTNs) is a cornerstone in achieving the vision of ubiquitous connectivity in 6G systems. This native integration of TN and NTN components enables global coverage, ultrareliable low-latency communications, and massive device connectivity, but it also presents significant challenges. These challenges include ensuring robust security in distributed architectures, safeguarding privacy during cross-domain data handling, and managing complex interference scenarios in shared and adjacent spectrum environments. Artificial intelligence (AI) serves as a transformative enabler in overcoming these challenges, providing advanced capabilities for real-time threat detection, adaptive authentication, privacy-preserving mechanisms, and dynamic spectrum management. By leveraging advanced techniques such as bidirectional long short-term memory (BiLSTM) networks, multi-agent reinforcement learning (MARL), and federated learning (FL), the proposed solutions enable robust anomaly detection, dynamic spectrum allocation, and scalable privacy-preserving model training. These techniques collectively improve key performance metrics, including a 30% enhancement in signal-to-interference-plus-noise ratio (SINR), over 90% spectrum efficiency, and a privacy budget of , while reducing latency to below 50 ms. This paper explores the vulnerabilities inherent to TN–NTN architectures, identifies limitations of traditional approaches, and examines cutting-edge AI-driven solutions tailored for integrated TN–NTN systems. Key contributions include insights into AI’s role in addressing security, privacy, and interference challenges, and the development of decentralized intelligence frameworks for scalable and efficient network operations.
... It is envisioned to provide a comprehensive solution for integrated terrestrial and non-terrestrial networks, focusing on global network coverage with high service continuity, ultra-high reliability, enhanced energy efficiency, and reduced total cost of ownership. As some of its developments in SDN, a cross-domain SDN architecture featuring distributed SDN controllers across all three layers is proposed in ETHER [50]. Furthermore, a hierarchical approach is employed, featuring a chief controller in each layer that manages the slave controllers within its respective layer. ...
... SDN and NFV paradigms are adopted to improve network flexibility and efficiency. They are also combined with AI techniques to offer intelligent network management [270]. Although the virtualization of the S-A-T networks offers seamless and ubiquitous connectivity, it increases the complexity of the related problems. ...
6G networks are envisioned to deliver a large diversity of applications and meet stringent Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial Networks (TN-NTNs) are anticipated to be key enabling technologies. However, the integration of TN-NTNs faces a number of challenges that could be addressed through network virtualization technologies, such as Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Network Slicing (NS). In this survey, we provide a comprehensive review of the adaptation of these networking paradigms in 6G networks. We begin with a brief overview of Non-Terrestrial Networks (NTNs) and virtualization techniques. Then, we highlight the integral role of Artificial Intelligence (AI) in improving network virtualization by summarizing major research areas where AI models are applied. Building on this foundation, we identify the main issues arising from the use of SDN, NFV, and NS in integrated TN-NTNs, and propose a taxonomy of integrated TN-NTNs virtualization offering a thorough review of relevant contributions. The taxonomy is built on a four-level classification that indicates — for each study — the level of TN-NTNs integration, the virtualization technology used, the problem addressed, the type of the study, and the proposed solution, which can be based on conventional or AI-enabled methods. Finally, we discuss open issues and give insights on future research directions for the advancement of integrated TN-NTNs virtualization in the 6G era.
... It should be noted that LEO satellites orbit with tangential velocities of 7.5 km/s (27,000 km/h) and orbital periods of 1.5-2 h [75], it is, therefore, necessary to develop new modulation schemes resistant to Doppler shift and robust UE mobility management mechanisms. Applicability of unified multi-tier UEs in AAM vehicles will also require reducing the dimensions of antennas for communication with LEO satellites without degradation of the link signal budget, e.g., through distributed beamforming from a large virtual array composed of LEO satellites swarms [76]. ...
Advanced Air Mobility (AAM) is a promising field of services based on Unmanned Aerial Vehicles (UAVs), which aims to provide people and cargo transportation services in underserved areas. The recent advancements in the fields of aviation and mobile telecommunication networks have opened up multiple opportunities for the development of disruptive AAM applications. This paper presents the overview and identifies the major requirements of emerging AAM use cases to confront them with the features provided by the 5G System (5GS), which is commonly considered the key enabler in providing commercial AAM services. The major benefits, gaps, and issues regarding using 5GS to serve AAM operations are identified and discussed. Finally, the future perspectives for AAM services are outlined with a focus on the potential benefit that can be provided as the mobile network evolves towards 6G.
In this work, we consider a real-time IoT monitoring system in which an energy harvesting sensor with a finite-size battery measures a physical process and transmits the status updates to an aggregator. The aggregator, equipped with caching capabilities, can serve the external requests of a destination network with either a stored update or a fresh update from the sensor. We assume the destination network acts as a gossiping network in which the update packets are forwarded among the nodes in a randomized setting. We utilize the Markov Decision Process framework to model and optimize the network’s average Version Age of Information (AoI) and obtain the optimal policy at the aggregator. We demonstrate analytically and verify numerically that the optimal policy structure conforms to a threshold policy regarding the Version AoI at the aggregator. Furthermore, we establish that the optimal policy is independent of the Version AoI value at the destination nodes. Through numerical results, we elucidate the impact of system parameters on the average Version AoI of the network and the rationale behind this impact. Additionally, the simulations unveil scenarios wherein the performance of the optimal policy significantly surpasses that of a set of baseline policies.
In this research, resource allocation in machine learning is used to analyze how cloud computing is being applied in smart agriculture. This chapter goes over the advantages of cloud computing for farming and how machine learning can enhance resource allocation for higher agricultural yields and less negative environmental impact. The chapter also examines implementation difficulties for cloud-based agricultural solutions and speculates on potential fixes. Insights for researchers and practitioners in the area are provided by the research, which demonstrates the potential for merging cloud computing and machine learning in smart agriculture to increase productivity and sustainability. The research also assessed the efficacy of the ML-based techniques using a variety of performance indicators, including reaction time and throughput. The management of cloud workloads has shown considerable promise when using machine learning-based methods. This chapter offers a thorough overview of current developments in ML-based cloud workload management and identifies areas for further research.
Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the recent technological advancements and manufacturing cost reduction opened up myriad applications of NTNs for 5G and beyond networks, especially when integrated into terrestrial networks (TNs). This article comprehensively surveys the evolution of NTNs highlighting their relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G ecosystem. We discuss important features of NTNs integration into TNs and the synergies by delving into the new range of services and use cases, various architectures, technological enablers, and higher layer aspects pertinent to NTNs integration. Moreover, we review the corresponding challenges arising from the technical peculiarities and the new approaches being adopted to develop efficient integrated ground-air-space (GAS) networks. Our survey further includes the major progress and outcomes from academic research as well as industrial efforts representing the main industrial trends, field trials, and prototyping towards the 6G networks.
The next phase of satellite technology is being characterized by a new evolution in non-geostationary orbit (NGSO) satellites, which conveys exciting new communication capabilities to provide non-terrestrial connectivity solutions and to support a wide range of digital technologies from various industries. NGSO communication systems are known for a number of key features such as lower propagation delay, smaller size, and lower signal losses in comparison to the conventional geostationary orbit (GSO) satellites, which can potentially enable latency-critical applications to be provided through satellites. NGSO promises a substantial boost in communication speed and energy efficiency, and thus, tackling the main inhibiting factors of commercializing GSO satellites for broader utilization. The promised improvements of NGSO systems have motivated this paper to provide a comprehensive survey of the state-of-theart NGSO research focusing on the communication prospects, including physical layer and radio access technologies along with the networking aspects and the overall system features and architectures. Beyond this, there are still many NGSO deployment challenges to be addressed to ensure seamless integration not only with GSO systems but also with terrestrial networks. These unprecedented challenges are also discussed in this paper, including coexistence with GSO systems in terms of spectrum access and regulatory issues, satellite constellation and architecture designs, resource management problems, and user equipment requirements. Finally, we outline a set of innovative research directions and new opportunities for future NGSO research.
As the fifth-generation (5G) mobile communication network may not meet the requirements of emerging technologies and applications, including ubiquitous coverage, industrial internet of things (IIoT), ubiquitous artificial intelligence (AI), digital twins (DT), etc., this paper aims to explore a novel space-air-ground integrated network (SAGIN) architecture to support these new requirements for the sixth-generation (6G) mobile communication network in a flexible, low-latency and efficient manner. Specifically , we first review the evolution of the mobile communication network, followed by the application and technology requirements of 6G. Then the current 5G non-terrestrial network (NTN) architecture in supporting the new requirements is deeply analyzed. After that, we proposes a new flexible, low-latency and flat SAGIN architecture, and presents corresponding use cases. Finally, the future research directions are discussed .
Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field.
Wireless connectivity has traditionally been regarded as an opaque data pipe carrying messages, whose context-dependent meaning and effectiveness have been ignored. Nevertheless, in emerging cyber-physical and autonomous networked systems, acquiring, processing, and sending excessive amounts of distributed real-time data, which ends up being stale or useless to the end user, will cause communication bottlenecks, increased latency, and safety issues. We envision a communication paradigm shift, which makes the semantics of information (i.e., the significance and usefulness of messages) the foundation of the communication process. This entails a goal-orient-ed unification of information generation, transmission, and reconstruction, by taking into account process dynamics, signal sparsity, data correlation, and semantic information attributes. We apply this structurally new, synergetic approach to a communication scenario where the destination is tasked with real-time source reconstruction for the purpose of remote actuation. Capitalizing on semantics-empowered sampling and communication policies, we show significant reduction in both reconstruction error and cost of actuation error, as well as in the number of uninformative samples generated.
Satellite communications (SatComs) have recently entered a period of renewed interest motivated by technological advances and nurtured through private investment and ventures. The present survey aims at capturing the state of the art in SatComs, while highlighting the most promising open research topics. Firstly, the main innovation drivers are motivated, such as new constellation types, on-board processing capabilities, non-terrestrial networks and space-based data collection/processing. Secondly, the most promising applications are described i.e. 5G integration, space communications, Earth observation, aeronautical and maritime tracking and communication. Subsequently, an in-depth literature review is provided across five axes: i) system aspects, ii) air interface, iii) medium access, iv) networking, v) testbeds & prototyping. Finally, a number of future challenges and the respective open research topics are described.
At the forefront of cutting-edge technologies, this text provides a comprehensive treatment of a crucial network performance metric, ushering in new opportunities for rethinking the whole design of communication systems. Detailed exposition of the communication and network theoretic foundations of Age of Information (AoI) gives the reader a solid background, and discussion of the implications on signal processing and control theory shed light on the important potential of recent research. The text includes extensive real-world applications of this vital metric, including caching, the Internet of Things (IoT), and energy harvesting networks. The far-reaching applications of AoI include networked monitoring systems, cyber-physical systems such as the IoT, and information-oriented systems and data analytics applications ranging from the stock market to social networks. The future of this exciting subject in 5G communication systems and beyond make this a vital resource for graduate students, researchers and professionals.
With the rapid development of low earth orbit (LEO) satellites, the ultra-dense LEO satellite-terrestrial integrated networking has become a promising paradigm to provide wide coverage, high capacity and flexible services for the sixth generation (6G) mobile communication networks. However, the natural heterogeneity, high dynamics, and large scale of ultradense LEO satellite networks pose new challenges to network control and management. To this end, in this article, we propose a medium earth orbit (MEO), low earth orbit (LEO) and satellite Earth stations (SESs) integrated multi-layered management architecture for the ultra-dense LEO satellite network, where global controllers and local controllers are introduced to reduce the network management complexity. With the aid of this hybrid multi-layered management framework, we can efficiently implement the network status control, mobility management, resource management, and service management in the satelliteterrestrial integrated network. To obtain proper global and local controllers with high management efficiency in the hybrid multilayered network management architecture, we further propose a novel and efficient grouping and clustering method for the ultradense LEO satellite network, where each group manager MEO satellite and cluster head (CH) LEO satellites are respectively considered as the global and local controllers of each LEO satellite group. Numerical simulations are carried out to evaluate the superiority and effectiveness of the proposed hybrid multilayered ultra-dense LEO networking management architecture.
Today, 5G networks are being worldwide rolled out, with significant benefits in our economy and society. However, 5G systems alone are not expected to be sufficient for the challenges that 2030 networks will experience, including, e.g., always-on networks, 1 Tbps peak data rate, <10 cm positioning, etc. Thus, the definition of evolutions of the 5G systems and their (r)evolutions are already being addressed by the scientific and industrial communities, targeting 5G-Advanced (5G-A) and 6G. In this framework, Non-Terrestrial Networks (NTN) have successfully been integrated in 3GPP Rel. 17 and it is expected that they will play an even more pivotal role for 5G-A (up to Rel. 20) and 6G systems (beyond Rel. 20). In this paper, we explore the path that will lead to 5G-A and 6G NTN communications, providing a clear perspective in terms of system architecture, services, technologies, and standardisation roadmap.
To realize global coverage of 5G, non-terrestrial networks (NTN) is proposed as an vital solution. Satellite based NTN has high communication latency and limited performance. Aerial NTN needs to launch too many airborne communication platforms, which is expensive. Aiming at the problems existing in the classic NTN architecture, civil aircraft assisted space-air-ground integrated network (CAA-SAGIN) is proposed. CAA-SAGIN consists of civil aircrafts and satellites. Civil aircrafts carry airborne base stations, which provide services for users along the route while carrying out tasks. CAA-SAGIN ensures the global coverage of the network, and uses civil aircrafts to provide high throughput and low latency services for hot spot areas. Through the coverage analysis and link budget, the full coverage of CAA-SAGIN for hot spot areas and the reduction of transmission loss are determined. Finally, as an inspiration, the open issues and challenges in the new architecture are summarized.
Many organizations recognize non-terrestrial networks (NTNs) as a key component to provide cost-effective and high-capacity connectivity in future 6th generation (6G) wireless networks. Despite this premise, there are still many questions to be answered for proper network design, including those associated to latency and coverage constraints. In this article, after reviewing research activities on NTNs, we present the characteristics and enabling technologies of NTNs in the 6G landscape and shed light on the challenges in the field that are still open for future research. As a case study, we evaluate the performance of an NTN scenario in which aerial/space vehicles use millimeter wave (mmWave) frequencies to provide access connectivity to on-the-ground mobile terminals as a function of different networking configurations.
A Holistic Flagship Towards The 6G Network Platform And System, To Inspire Digital Transformation, For The World To Act Together In Meeting Needs In Society And Ecosystems With Novel 6G Services
- X Hexa
- Ii
- A Guidotti
- A Vanelli-Coralli
- V Schena
- N Chuberre
- M E Jaafari
- J Puttonen