6G Enabled Advanced Transportation Systems

The 6th generation (6G) wireless communication network is envisaged to be able to change our lives drastically, including transportation. In this paper, two ways of interactions between 6G communication networks and transportation are introduced. With the new usage scenarios and capabilities 6G is going to support, passengers on all sorts of transportation systems will be able to get data more easily, even in the most remote areas on the planet. The quality of communication will also be improved significantly, thanks to the advanced capabilities of 6G. On top of providing seamless and ubiquitous connectivity to all forms of transportation, 6G will also transform the transportation systems to make them more intelligent, more efficient, and safer. Based on the latest research and standardization progresses, technical analysis on how 6G can empower advanced transportation systems are provided, as well as challenges and insights for a possible road ahead.Comment: Submitted to an open access journa

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Self-Evolving Integrated Vertical Heterogeneous Networks

6G and beyond networks tend towards fully intelligent and adaptive design in order to provide better operational agility in maintaining universal wireless access and supporting a wide range of services and use cases while dealing with network complexity efficiently. Such enhanced network agility will require developing a self-evolving capability in designing both the network architecture and resource management to intelligently utilize resources, reduce operational costs, and achieve the coveted quality of service (QoS). To enable this capability, the necessity of considering an integrated vertical heterogeneous network (VHetNet) architecture appears to be inevitable due to its high inherent agility. Moreover, employing an intelligent framework is another crucial requirement for self-evolving networks to deal with real-time network optimization problems. Hence, in this work, to provide a better insight on network architecture design in support of self-evolving networks, we highlight the merits of integrated VHetNet architecture while proposing an intelligent framework for self-evolving integrated vertical heterogeneous networks (SEI-VHetNets). The impact of the challenges associated with SEI-VHetNet architecture, on network management is also studied considering a generalized network model. Furthermore, the current literature on network management of integrated VHetNets along with the recent advancements in artificial intelligence (AI)/machine learning (ML) solutions are discussed. Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are identified. Finally, the potential future research directions for advancing the autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table

High-Throughput Air-to-Ground Connectivity for Aircraft

Permanent connectivity to the Internet has become the defacto standard in the second decade of the 21st century. However, on-board aircraft connectivity is still limited. While the number of airlines offering in-flight connectivity increases, the current performance is insufficient to satisfy several hundreds of passengers simultaneously. There are several options to connect aircraft to the ground, i.e. direct air-to-ground, satellites and relaying via air-to-air links. However, each single solution is insufficient. The direct air-to-ground coverage is limited to the continent and coastal regions, while the satellite links are limited in the minimum size of the spot beams and air-to-air links need to be combined with a link to the ground. Moreover, even if a direct air-to-ground or satellite link is available, the peak throughput offered on each link is rarely achieved, as the capacity needs to be shared with other aircraft flying in the same coverage area. The main challenge in achieving a high throughput per aircraft lies in the throughput allocation. All aircraft should receive a fair share of the available throughput. More specifically, as an aircraft contains a network itself, a weighted share according to the aircraft size should be provided. To address this problem, an integrated air-to-ground network, which is able to provide a high throughput to aircraft, is proposed here. Therefore, this work introduces a weighted-fair throughput allocation scheme to provide such a desired allocation. While various aspects of aircraft connectivity are studied in literature, this work is the first to address an integrated air-to-ground network to provide high-throughput connectivity to aircraft. This work models the problem of throughput allocation as a mixed integer linear program. Two throughput allocation schemes are proposed, a centralized optimal solution and a distributed heuristic solution. For the optimal solution, two different objectives are introduced, a max-min-based and a threshold-based objective. The optimal solution is utilized as a benchmark for the achievable throughput for small scenarios, while the heuristic solution offers a distributed approach and can process scenarios with a higher number of aircraft. Additionally, an option for weighted-fair throughput allocation is included. Hence, large aircraft obtain a larger share of the throughput than smaller ones. This leads to fair throughput allocation with respect to the size of the aircraft. To analyze the performance of throughput allocation in the air-to-ground network, this work introduces an air-to-ground network model. It models the network realistically, but independent from specific network implementations, such as 5G or WiFi. It is also adaptable to different scenarios. The aircraft network is studied based on captured flight traces. Extensive and representative parameter studies are conducted, including, among others, different link setups, geographic scenarios, aircraft capabilities, link distances and link capacities. The results show that the throughput can be distributed optimally during high-aircraft-density times using the optimal solution and close to optimal using the heuristic solution. The mean throughput during these times in the optimal reference scenario with low Earth orbit satellites is 20 Mbps via direct air-to-ground links and 4 Mbps via satellite links, which corresponds to 10.7% and 1.9% of the maximum link throughput, respectively. Nevertheless, during low-aircraft-density times, which are less challenging, the throughput can reach more than 200 Mbps. Therefore, the challenge is on providing a high throughput during high-aircraft-density times. In the larger central European scenario, using the heuristic scheme, a minimum of 22.9 Mbps, i.e. 3.2% of the maximum capacity, can be provided to all aircraft during high-aircraft-density times. Moreover, the critical parameters to obtain a high throughput are presented. For instance, this work shows that multi-hop air-to-air links are dispensable for aircraft within direct air-to-ground coverage. While the computation time of the optimal solution limits the number of aircraft in the scenario, larger scenarios can be studied using the heuristic scheme. The results using the weighted-fair throughput allocation show that the introduction of weights enables a user-fair throughput allocation instead of an aircraft-fair throughput allocation. As a conclusion, using the air-to-ground model and the two introduced throughput allocation schemes, the achievable weighted-fair throughput per aircraft and the respective link choices can be quantified