Energy-Efficient Design of Satellite-Terrestrial Computing in 6G Wireless Networks

In this paper, we investigate the issue of satellite-terrestrial computing in the sixth generation (6G) wireless networks, where multiple terrestrial base stations (BSs) and low earth orbit (LEO) satellites collaboratively provide edge computing services to ground user equipments (GUEs) and space user equipments (SUEs) over the world. In particular, we design a complete process of satellite-terrestrial computing in terms of communication and computing according to the characteristics of 6G wireless networks. In order to minimize the weighted total energy consumption while ensuring delay requirements of computing tasks, an energy-efficient satellite-terrestrial computing algorithm is put forward by jointly optimizing offloading selection, beamforming design and resource allocation. Finally, both theoretical analysis and simulation results confirm fast convergence and superior performance of the proposed algorithm for satellite-terrestrial computing in 6G wireless networks

Improving SINR Performance Deploying IRS in 6G Wireless Networks

Interactive reflecting surfaces (IRSs) are a remarkable technology that will be integrated into 6G wireless networks to enhance the electromagnetic propagation environment in a programmable or adaptable way in order to improve communication between both transmission and reception devices. The work intends to broaden coverage by including IRS into micro radio transmission. As a consequence, the study evaluated and contrasted the performance of regular miniature cellular connection with IRS-enhanced miniature cellular connection in the 6G radio context in respect to signal to interference plus noise ratio (SINR)

6G White Paper on Machine Learning in Wireless Communication Networks

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented

6G Radio Testbeds: Requirements, Trends, and Approaches

The proof of the pudding is in the eating - that is why 6G testbeds are essential in the progress towards the next generation of wireless networks. Theoretical research towards 6G wireless networks is proposing advanced technologies to serve new applications and drastically improve the energy performance of the network. Testbeds are indispensable to validate these new technologies under more realistic conditions. This paper clarifies the requirements for 6G radio testbeds, reveals trends, and introduces approaches towards their development

Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality

Reconfigurable Intelligent Surfaces based system design for future 6G wireless networks

Future sixth generation (6G) wireless networks perceive the THz band as essential to support the high volume of wireless traffic data being generated in the network, thus enabling ultra high transmission rates. However, the behaviour of the THz frequency spectrum affects the propagation occurring in the wireless communication system due to high attenuation, leading to severe propagation losses. Reconfigurable intelligent surfaces (RIS) are a promising technology to overcome the limitations present in the THz waveband by reshaping the wave direction, thus enabling the signal to propagate towards its intended target. RIS have many applications in wireless systems, specifically in the optimization of the communication network performance when combined with ultra-massive multiple-input multiple-output antennas (UM-MIMO). UMMIMO systems are critical for implementing THz frequencies as the large number of antennas provides high directivity pencil like beams, thereby enabling easy data spread from the transmitter towards the receiver. To achieve low complexity whilst deploying UM-MIMO systems, hybrid precoders must be implemented. This dissertation aims to design and evaluate a RIS-assisted communication model for ultra-massive MIMO systems to extend coverage range and to improve the energy and spectral efficiency of 6G communications. To maximize the achievable rate of the structure, an algorithm will be developed to calculate the phase shifts of the individual RIS elements, and the implementation of various hybrid precoding structures. Several numerical results will be obtained through various simulations and analysed to give insight into which design is best suited for RIS-assisted THz communication system through the achievable rates obtained.As futuras redes sem fios da sexta geração (6G) consideram a frequência Terahertz fundamental para suportar o elevado número de tráfego gerado na rede, permitindo assim elevadas taxas de transmissão de dados. Todavia, o comportamento do espectro de frequências THz condiciona a propagação que ocorre no sistema de comunicação pela sua elevada atenuação, originando graves perdas de propagação. Superfícies inteligentes reconfiguráveis (RIS) são uma tecnologia promissora para ultrapassar as limitações existentes na faixa dos THz ao moldarem a direção da onda, permitindo que o sinal se propague para o destinatário. Os RIS dispõem de inúmeras aplicações nos sistemas sem fios, especificamente na otimização do desempenho da rede de comunicações ao utilizarem antenas ultra massivas de múltipla entradas e saídas. Os sistemas UM-MIMO são fundamentais para implementar frequências THz pelo elevado número de antenas, facilitando a propagação de dados desde o emissor e recetor. A fim de alcançar uma complexidade reduzida nos sistemas UM-MIMO, é necessário implementar pré-codificadores híbridos. Esta dissertação pretende conceber um sistema de comunicação para redes sem fios ultra massivo MIMO assistido por RIS para melhorar a eficiência energética das comunicações 6G e do espectro e o alcance da cobertura. De modo a maximizar a taxa alcançável do modelo, será desenvolvido um algoritmo para calcular a quantização das mudanças de fase dos elementos RIS sendo implementado várias estruturas híbridas de pré-codificação. Os resultados numéricos serão analisados a fim de revelar qual a configuração ideal para o sistema de comunicação THz assistido por RIS mediante as taxas alcançáveis obtidas

LiFi Transceiver Designs for 6G Wireless Networks

Due to the dramatic increase in high data rate services, and in order to meet the demands of the sixth-generation (6G) wireless networks, researchers from both academia and industry have been exploring advanced transmission techniques, new network archi- tectures and new frequency bands, such as the millimeter wave (mmWave), the infrared, and the visible light bands. Light-fdelity (LiFi) particularly is an emerging, novel, bidirectional, high-speed and fully networked optical wireless communication (OWC) technology that has been introduced as a promising solution for 6G networks, especially for indoor connectivity, owing to the large unexploited spectrum that translates to signifcantly high data rates. Although there has been a big leap in the maturity of the LiFi technology, there is still a considerable gap between the available LiFi technology and the required demands of 6G networks. Motivated by this, this dissertation aims to bridge between the current research literature of LiFi and the expected demands of 6G networks. Specifcally, the key goal of this dissertation is to fll some shortcomings in the LiFi technology, such as channel modeling, transceiver designs, channel state information (CSI) acquisition, localization, quality-of-service (QoS), and performance optimization. Our work is devoted to address and solve some of these limitations. Towards achieving this goal, this dissertation makes signifcant contributions to several areas of LiFi. First, it develops novel and measurements-based channel models for LiFi systems that are required for performance analysis and handover management. Second, it proposes a novel design for LiFi devices that is capable of alleviating the real behaviour of users and the impurities of indoor propagation environments. Third, it proposes intelligent, accurate and fast joint position and orientation techniques for LiFi devices, which improve the CSI estimation process and boost the indoor location-based and navigation-based services. Then, it proposes novel proactive optimization technique that can provide near-optimal and real-time service for indoor mobile LiFi users that are running some services with high data rates, such as extended reality, video conferencing, and real-time video monitoring. Finally, it proposes advanced multiple access techniques that are capable of cancelling the efects of interference in indoor multi-user settings. The studied problems are tackled using various tools from probability and statistic theory, system design and integration theory, optimization theory, and deep learning. The Results demonstrate the efectiveness of the proposed designs, solutions, and techniques. Nevertheless, the fndings in this dissertation highlight key guidelines for the efective design of LiFi while considering their unique propagation features

Toward Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication, and Security

Integrated sensing and communication (ISAC) has recently emerged as a candidate 6G technology, aiming to unify the two key operations of the future network in a spectrum/energy/cost-efficient way. ISAC systems communicate and sense for targets using a common waveform, a common hardware platform, and ultimately the same network infrastructure. Nevertheless, the inclusion of information signaling in the probing waveform for target sensing raises challenges from the perspective of information security. At the same time, the sensing capability incorporated in ISAC transmission offers unique opportunities to design secure ISAC techniques. This overview article discusses these unique challenges and opportunities for the next generation of ISAC networks. We first briefly discuss the fundamentals of waveform design for sensing and communication. Then we detail the challenges and contradictory objectives involved in securing ISAC transmission, along with state-of-the-art approaches to ensure security. We then identify the new opportunity of using the sensing capability to obtain knowledge target information as an enabling approach against the known weak-nesses of PHY security. Finally, we illustrate some low-cost secure ISAC architectures, followed by a series of open research topics. This family of sensing-aided secure ISAC techniques brings new insight on providing information security, with an eye on robust and hardware-constrained designs tailored for low-cost ISAC devices

Toward Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication, and Security

Integrated sensing and communication (ISAC) has recently emerged as a candidate 6G technology, aiming to unify the two key operations of the future network in a spectrum/energy/cost-efficient way. ISAC systems communicate and sense for targets using a common waveform, a common hardware platform, and ultimately the same network infrastructure. Nevertheless, the inclusion of information signaling in the probing waveform for target sensing raises challenges from the perspective of information security. At the same time, the sensing capability incorporated in ISAC transmission offers unique opportunities to design secure ISAC techniques. This overview article discusses these unique challenges and opportunities for the next generation of ISAC networks. We first briefly discuss the fundamentals of waveform design for sensing and communication. Then we detail the challenges and contradictory objectives involved in securing ISAC transmission, along with state-of-the-art approaches to ensure security. We then identify the new opportunity of using the sensing capability to obtain knowledge target information as an enabling approach against the known weak-nesses of PHY security. Finally, we illustrate some low-cost secure ISAC architectures, followed by a series of open research topics. This family of sensing-aided secure ISAC techniques brings new insight on providing information security, with an eye on robust and hardware-constrained designs tailored for low-cost ISAC devices