A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence

Due to the advancements in cellular technologies and the dense deployment of cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond cellular networks is a promising solution to achieve safe UAV operation as well as enabling diversified applications with mission-specific payload data delivery. In particular, 5G networks need to support three typical usage scenarios, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). On the one hand, UAVs can be leveraged as cost-effective aerial platforms to provide ground users with enhanced communication services by exploiting their high cruising altitude and controllable maneuverability in three-dimensional (3D) space. On the other hand, providing such communication services simultaneously for both UAV and ground users poses new challenges due to the need for ubiquitous 3D signal coverage as well as the strong air-ground network interference. Besides the requirement of high-performance wireless communications, the ability to support effective and efficient sensing as well as network intelligence is also essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting aerial and ground users. In this paper, we provide a comprehensive overview of the latest research efforts on integrating UAVs into cellular networks, with an emphasis on how to exploit advanced techniques (e.g., intelligent reflecting surface, short packet transmission, energy harvesting, joint communication and radar sensing, and edge intelligence) to meet the diversified service requirements of next-generation wireless systems. Moreover, we highlight important directions for further investigation in future work.Comment: Accepted by IEEE JSA

Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance

The pervasive nature of wireless telecommunication has made it the foundation for mainstream technologies like automation, smart vehicles, virtual reality, and unmanned aerial vehicles. As these technologies experience widespread adoption in our daily lives, ensuring the reliable performance of cellular networks in mobile scenarios has become a paramount challenge. Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages and implications. Notably, the study presents an impressive 53% improvement in signal-to-noise ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and Zero forcing (ZF) techniques, alongside deep neural networks (DNN) employing Bayesian Optimization (BO), represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino, in enabling location-aware beamforming

LiDAR aided simulation pipeline for wireless communication in vehicular traffic scenarios

Abstract. Integrated Sensing and Communication (ISAC) is a modern technology under development for Sixth Generation (6G) systems. This thesis focuses on creating a simulation pipeline for dynamic vehicular traffic scenarios and a novel approach to reducing wireless communication overhead with a Light Detection and Ranging (LiDAR) based system. The simulation pipeline can be used to generate data sets for numerous problems. Additionally, the developed error model for vehicle detection algorithms can be used to identify LiDAR performance with respect to different parameters like LiDAR height, range, and laser point density. LiDAR behavior on traffic environment is provided as part of the results in this study. A periodic beam index map is developed by capturing antenna azimuth and elevation angles, which denote maximum Reference Signal Receive Power (RSRP) for a simulated receiver grid on the road and classifying areas using Support Vector Machine (SVM) algorithm to reduce the number of Synchronization Signal Blocks (SSBs) that are needed to be sent in Vehicle to Infrastructure (V2I) communication. This approach effectively reduces the wireless communication overhead in V2I communication

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

A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G

Sixth-generation (6G) mobile communication networks are expected to have dense infrastructures, large-dimensional channels, cost-effective hardware, diversified positioning methods, and enhanced intelligence. Such trends bring both new challenges and opportunities for the practical design of 6G. On one hand, acquiring channel state information (CSI) in real time for all wireless links becomes quite challenging in 6G. On the other hand, there would be numerous data sources in 6G containing high-quality location-tagged channel data, making it possible to better learn the local wireless environment. By exploiting such new opportunities and for tackling the CSI acquisition challenge, there is a promising paradigm shift from the conventional environment-unaware communications to the new environment-aware communications based on the novel approach of channel knowledge map (CKM). This article aims to provide a comprehensive tutorial overview on environment-aware communications enabled by CKM to fully harness its benefits for 6G. First, the basic concept of CKM is presented, and a comparison of CKM with various existing channel inference techniques is discussed. Next, the main techniques for CKM construction are discussed, including both the model-free and model-assisted approaches. Furthermore, a general framework is presented for the utilization of CKM to achieve environment-aware communications, followed by some typical CKM-aided communication scenarios. Finally, important open problems in CKM research are highlighted and potential solutions are discussed to inspire future work

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

An introduction of intelligent interconnectivity for people and things has posed higher demands and more challenges for sixth-generation (6G) networks, such as high spectral efficiency and energy efficiency, ultra-low latency, and ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent reflecting surface (IRS), are two promising technologies for coping with these unprecedented demands. Given their distinct capabilities, integrating the two technologies to further enhance wireless network performances has received great research and development attention. In this paper, we provide a comprehensive survey of research on RIS-aided CF mMIMO wireless communication systems. We first introduce system models focusing on system architecture and application scenarios, channel models, and communication protocols. Subsequently, we summarize the relevant studies on system operation and resource allocation, providing in-depth analyses and discussions. Following this, we present practical challenges faced by RIS-aided CF mMIMO systems, particularly those introduced by RIS, such as hardware impairments and electromagnetic interference. We summarize corresponding analyses and solutions to further facilitate the implementation of RIS-aided CF mMIMO systems. Furthermore, we explore an interplay between RIS-aided CF mMIMO and other emerging 6G technologies, such as next-generation multiple-access (NGMA), simultaneous wireless information and power transfer (SWIPT), and millimeter wave (mmWave). Finally, we outline several research directions for future RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure