Survey of Inter-satellite Communication for Small Satellite Systems: Physical Layer to Network Layer View

Small satellite systems enable whole new class of missions for navigation, communications, remote sensing and scientific research for both civilian and military purposes. As individual spacecraft are limited by the size, mass and power constraints, mass-produced small satellites in large constellations or clusters could be useful in many science missions such as gravity mapping, tracking of forest fires, finding water resources, etc. Constellation of satellites provide improved spatial and temporal resolution of the target. Small satellite constellations contribute innovative applications by replacing a single asset with several very capable spacecraft which opens the door to new applications. With increasing levels of autonomy, there will be a need for remote communication networks to enable communication between spacecraft. These space based networks will need to configure and maintain dynamic routes, manage intermediate nodes, and reconfigure themselves to achieve mission objectives. Hence, inter-satellite communication is a key aspect when satellites fly in formation. In this paper, we present the various researches being conducted in the small satellite community for implementing inter-satellite communications based on the Open System Interconnection (OSI) model. This paper also reviews the various design parameters applicable to the first three layers of the OSI model, i.e., physical, data link and network layer. Based on the survey, we also present a comprehensive list of design parameters useful for achieving inter-satellite communications for multiple small satellite missions. Specific topics include proposed solutions for some of the challenges faced by small satellite systems, enabling operations using a network of small satellites, and some examples of small satellite missions involving formation flying aspects.Comment: 51 pages, 21 Figures, 11 Tables, accepted in IEEE Communications Surveys and Tutorial

The Coverage, Capacity and Coexistence of Mixed High Altitude Platform and Terrestrial Segments

This thesis explores the coverage, capacity and coexistence of High Altitude Platform (HAP) and terrestrial segments in the same service area. Given the limited spectrum available, mechanisms to manage the co-channel interference to enable effective coexistence between the two infrastructures are examined. Interference arising from the HAP, caused by the relatively high transmit power and the antenna beam profile, has the potential to significantly affect the existing terrestrial system on the ground if the HAP beams are deployed without a proper strategy. Beam-pointing strategies exploiting phased array antennas on the HAPs are shown to be an effective way to place the beams, with each of them forming service cells onto the ground in the service area, especially dense user areas. Using a newly developed RF clustering technique to better point the cells over an area of a dense group of users, it is shown that near maximum coverage of 96% of the population over the service area can be provided while maintaining the coexistence with the existing terrestrial system. To improve the user experience at the cell edge, while at the same time improving the overall capacity of the system, Joint Transmission – Coordinated Multipoint (JT-CoMP) is adapted for a HAP architecture. It is shown how the HAP can potentially enable the tight scheduling needed to perform JT-CoMP due to the centralisation of all virtual E-UTRAN Node Bs (eNodeBs) on the HAP. A trade-off between CINR gain and loss of capacity when adapting JT-CoMP into the HAP system is identified, and strategies to minimise the trade-off are considered. It is shown that 57% of the users benefit from the JT-CoMP. In order to enable coordination between the HAP and terrestrial segments, a joint architecture based on a Cloud – Radio Access Network (C-RAN) system is introduced. Apart from adapting a C-RAN based system to centrally connect the two segments together, the network functional split which varies the degree of the centralised processing is also considered to deal with the limitations of HAP fronthaul link requirements. Based on the fronthaul link requirements acquired from the different splitting options, the ground relay station diversity to connect the HAP to centralised and distributed units (CUs and DUs) is also considered

Towards Context Information-based High-Performing Connectivity in Internet of Vehicle Communications

Internet-of-vehicles (IoV) is one of the most important use cases in the fifth generation (5G) of wireless networks and beyond. Here, IoV communications refer to two types of scenarios: serving the in-vehicle users with moving relays (MRs); and supporting vehicle-to-everything (V2X) communications for, e.g., connected vehicle functionalities. Both of them can be achieved by transceivers on top of vehicles with growing demand for quality of service (QoS), such as spectrum efficiency, peak data rate, and coverage probability. However, the performance of MRs and V2X is limited by challenges such as the inaccurate prediction/estimation of the channel state information (CSI), beamforming mismatch, and blockages. Knowing the environment and utilizing such context information to assist communication could alleviate these issues. This thesis investigates various context information-based performance enhancement schemes for IoV networks, with main contributions listed as follows.In order to mitigate the channel aging issue, i.e., the CSI becomes inaccurate soon at high speeds, the first part of the thesis focuses on one way to increase the prediction horizon of CSI in MRs: predictor antennas (PAs). A PA system is designed as a system with two sets of antennas on the roof of a vehicle, where the PAs positioned at the front of the vehicle are used to predict the CSI observed by the receive antennas (RAs) that are aligned behind the PAs. In PA systems, however, the benefit is affected by a variety of factors. For example, 1) spatial mismatch between the point where the PA estimates the channel and the point where the RA reaches several time slots later, 2) antenna utilization efficiency of the PA, 3) temporal evolution, and 4) estimation error of the PA-base station (BS) channel. First, in Paper A, we study the PA system in the presence of the spatial mismatch problem, and propose an analytical channel model which is used for rate adaptation. In paper B, we propose different approximation schemes for the analytical investigation of PA systems, and study the effect of different parameters on the network performance. Then, involving PAs into data transmission, Paper C and Paper D analyze the outage- and the delay-limited performance of PA systems using hybrid automatic repeat request (HARQ), respectively. As we show in the analytical and the simulation results in Papers C-D, the combination of PA and HARQ protocols makes it possible to improve spectral efficiency and adapt the transmission parameters to mitigate the effect of spatial mismatch. Finally, a review of PA studies in the literature, the challenges and potentials of PA as well as some to-be-solved issues are presented in Paper E.The second part of the thesis focuses on using advanced technologies to further improve the MR/IoV performance. In Paper F, a cooperative PA scheme in IoV networks is proposed to mitigate both the channel aging effect and blockage sensitivity in millimeter-wave channels by collaborative vehicles and BS handover. Then, in Paper G, we study the potentials and challenges of dynamic blockage pre-avoidance in IoV networks

Revolutionizing Future Connectivity: A Contemporary Survey on AI-empowered Satellite-based Non-Terrestrial Networks in 6G

Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as the primary enabler for NTN, leveraging their extensive coverage, stable orbits, scalability, and adherence to international regulations. However, satellite-based NTN presents unique challenges, including long propagation delay, high Doppler shift, frequent handovers, spectrum sharing complexities, and intricate beam and resource allocation, among others. The integration of NTNs into existing terrestrial networks in 6G introduces a range of novel challenges, including task offloading, network routing, network slicing, and many more. To tackle all these obstacles, this paper proposes Artificial Intelligence (AI) as a promising solution, harnessing its ability to capture intricate correlations among diverse network parameters. We begin by providing a comprehensive background on NTN and AI, highlighting the potential of AI techniques in addressing various NTN challenges. Next, we present an overview of existing works, emphasizing AI as an enabling tool for satellite-based NTN, and explore potential research directions. Furthermore, we discuss ongoing research efforts that aim to enable AI in satellite-based NTN through software-defined implementations, while also discussing the associated challenges. Finally, we conclude by providing insights and recommendations for enabling AI-driven satellite-based NTN in future 6G networks.Comment: 40 pages, 19 Figure, 10 Tables, Surve