3D Channel Tracking in Space-Air-Ground Integrated Networks.

PhD ThesesThe space-air-ground integrated network (SAGIN) aims to provide seamless wide-area connections, high throughput and strong resilience for beyond the fth generation (B5G) and future communications. As a multidimensional network, SAGIN adopts di erent communication links across three segments: the space segment with satellite networks, the air segment with aerial networks, and the ground segment with territorial networks. Apart from Ka-band millimetre wave (mmWave) frequencies being utilized for low earth orbit (LEO) satellites and medium earth orbit (MEO) satellites communications, with emerging smart devices brought online and crowded under-6GHz spectrum, mmWave frequencies have also been widely considered to support both aerial networks and territorial networks. To ensure stable wireless communications and tackle the severer propagation loss of mmWave transmission, massive multiple input and multiple output (MIMO) and intelligent re ecting surfaces (IRSs), which can con gure directional beams and bring huge improvements of radiated energy e ciency, are two technologies to be employed in SAGIN. Conventionally, perfect channel state information (CSI) is the fundamental knowledge to enable building reliable communication connections. With massive antenna arrays installed on orbiting satellites, navigation unmanned aerial vehicles (UAVs), and base stations, it's very challenging to acquire real-time mmWave CSI in SAGIN due to the heavy overheads and the dynamic environment. Most existing mmWave channel estimation work proposed compressive sensing (CS) based algorithms to reduce the heavy overheads with the assumption that the environment is in two-dimensional (2D) space and static without any movement. However, in SAGIN, 2D and static assumptions are not practical. Hence, tracking the dynamic three-dimensional (3D) CSI using small training overheads becomes a crucial and demanding task. i In this thesis, 3D channel tracking algorithms are proposed based on unique characteristics of air-ground and space-air links. For IRS-assisted air-ground links, we propose a 3D geometry dynamic channel model with both UAV navigation and mobile user movement. We further develop a deep learning (DL)-based channel tracking algorithms with two modules: deep neural network (DNN) channel pre-estimation for denoising and stacked bi-directional long short term memory (Stacked Bi-LSTM) for channel tracking. For space-air links, we exploit the on-grid and o -grid single user (SU) and multi-user (MU) UAV-satellite communications. Two statistical spatial and temporal correlation sparsity of the dynamic channel models called 3D two-dimensional Markov model (3D- 2D-MM) and multi-dimensional Markov model (MD-MM) are developed by introducing the more realistic 3D movement in the system. Based on the message passing rule and the proposed Markov structures, 3D dynamic turbo approximate message passing algorithm (3D-DTAMP) and multi-dimensional dynamic turbo approximate message passing (MD-DTAMP) are derived for channel tracking. Our proposed algorithms can achieve better channel estimation accuracy with comparable complexity and smaller training overheads

IRS-assisted UAV Communications: A Comprehensive Review

Intelligent reflecting surface (IRS) can smartly adjust the wavefronts in terms of phase, frequency, amplitude and polarization via passive reflections and without any need of radio frequency (RF) chains. It is envisaged as an emerging technology which can change wireless communication to improve both energy and spectrum efficiencies with low energy consumption and low cost. It can intelligently configure the wireless channels through a massive number of cost effective passive reflecting elements to improve the system performance. Similarly, unmanned aerial vehicle (UAV) communication has gained a viable attention due to flexible deployment, high mobility and ease of integration with several technologies. However, UAV communication is prone to security issues and obstructions in real-time applications. Recently, it is foreseen that UAV and IRS both can integrate together to attain unparalleled capabilities in difficult scenarios. Both technologies can ensure improved performance through proactively altering the wireless propagation using smart signal reflections and maneuver control in three dimensional (3D) space. IRS can be integrated in both aerial and terrene environments to reap the benefits of smart reflections. This study briefly discusses UAV communication, IRS and focuses on IRS-assisted UAC communications. It surveys the existing literature on this emerging research topic and highlights several promising technologies which can be implemented in IRS-assisted UAV communication. This study also presents several application scenarios and open research challenges. This study goes one step further to elaborate research opportunities to design and optimize wireless systems with low energy footprint and at low cost. Finally, we shed some light on future research aspects for IRS-assisted UAV communication

Near-Space Communications: the Last Piece of 6G Space-Air-Ground-Sea Integrated Network Puzzle

This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space-air-ground-sea integrated network (SAGSIN). Specifically, we firstly explore the recent technical developments of NS-COM, followed by the discussions about motivations behind integrating NS-COM into SAGSIN. To further demonstrate the necessity of NS-COM, a comparative analysis between the NS-COM network and other counterparts in SAGSIN is conducted, covering aspects of deployment, coverage, channel characteristics and unique problems of NS-COM network. Afterwards, the technical aspects of NS-COM, including channel modeling, random access, channel estimation, array-based beam management and joint network optimization, are examined in detail. Furthermore, we explore the potential applications of NS-COM, such as structural expansion in SAGSIN communication, civil aviation communication, remote and urgent communication, weather monitoring and carbon neutrality. Finally, some promising research avenues are identified, including stratospheric satellite (StratoSat) -to-ground direct links for mobile terminals, reconfigurable multiple-input multiple-output (MIMO) and holographic MIMO, federated learning in NS-COM networks, maritime communication, electromagnetic spectrum sensing and adversarial game, integrated sensing and communications, StratoSat-based radar detection and imaging, NS-COM assisted enhanced global navigation system, NS-COM assisted intelligent unmanned system and free space optical (FSO) communication. Overall, this paper highlights that the NS-COM plays an indispensable role in the SAGSIN puzzle, providing substantial performance and coverage enhancement to the traditional SAGSIN architecture.Comment: 28 pages, 8 figures, 2 table

Terahertz Communications and Sensing for 6G and Beyond: A Comprehensive View

The next-generation wireless technologies, commonly referred to as the sixth generation (6G), are envisioned to support extreme communications capacity and in particular disruption in the network sensing capabilities. The terahertz (THz) band is one potential enabler for those due to the enormous unused frequency bands and the high spatial resolution enabled by both short wavelengths and bandwidths. Different from earlier surveys, this paper presents a comprehensive treatment and technology survey on THz communications and sensing in terms of the advantages, applications, propagation characterization, channel modeling, measurement campaigns, antennas, transceiver devices, beamforming, networking, the integration of communications and sensing, and experimental testbeds. Starting from the motivation and use cases, we survey the development and historical perspective of THz communications and sensing with the anticipated 6G requirements. We explore the radio propagation, channel modeling, and measurements for THz band. The transceiver requirements, architectures, technological challenges, and approaches together with means to compensate for the high propagation losses by appropriate antenna and beamforming solutions. We survey also several system technologies required by or beneficial for THz systems. The synergistic design of sensing and communications is explored with depth. Practical trials, demonstrations, and experiments are also summarized. The paper gives a holistic view of the current state of the art and highlights the issues and challenges that are open for further research towards 6G.Comment: 55 pages, 10 figures, 8 tables, submitted to IEEE Communications Surveys & Tutorial

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components