Physical Layer Security Issues In Massive Mimo And Gnss

Wireless communication technology has evolved rapidly during the last 20 years. Nowadays, there are huge networks providing communication infrastructures to not only people but also to machines, such as unmanned air and ground vehicles, cars, household appliances and so on. There is no doubt that new wireless communication technologies must be developed, that support the data traffic in these emerging, large networks. While developing these technologies, it is also important to investigate the vulnerability of these technologies to different malicious attacks. In particular, spoofing and jamming attacks should be investigated and new countermeasure techniques should be developed. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal-to-interference-and-noise ratio (SINR) on the receiver side. In this thesis, we analyze the effects of spoofing and jamming both on global navigation satellite system (GNSS) and on massive multiple-input multiple-output (MIMO) communications. GNSS is everywhere and used to provide location information. Massive MIMO is one of the cornerstone technologies in 5G. We also propose countermeasure techniques to the studied spoofing and jamming attacks. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation’s cellular networks? Which jamming attack strategies are the best from the jammer’s perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number of spoofers in the environment.

Securely transferring confidential information over a wireless network is a challenging task. This book addresses security issues, not only for 5G but also beyond, using physical layer security technology and techniques.

This book investigates key security issues in connection with the physical layer for random wireless cellular networks. It first introduces readers to the fundamentals of information theoretic security in the physical layer. By examining recently introduced security techniques for wireless point-to-point communications, the book proposes new solutions to physical layer security based on stochastic geometric frameworks for random cellular networks. It subsequently elaborates on physical-layer security in multi-tier heterogeneous networks. With the new modeled settings, the authors also verify the security performance with the impact of the full-duplex transceivers. The specific model design presented here offers a valuable point of reference for readers in related areas. In addition, the book highlights promising topics and proposes potential future research directions.

Physical layer security has recently become an emerging technique to complement and significantly improve the communication security of wireless networks. Compared to cryptographic approaches, physical layer security is a fundamentally different paradigm where secrecy is achieved by exploiting the physical layer properties of the communication syst

This two volume set constitutes the refereed proceedings of the 14th EAI International Conference on Communications and Networking, ChinaCom 2019, held in November/December 2019 in Shanghai, China. The 81 papers presented were carefully selected from 162 submissions. The papers are organized in topical sections on Internet of Things (IoT), antenna, microwave and cellular communication, wireless communications and networking, network and information security, communication QoS, reliability and modeling, pattern recognition and image signal processing, and information processing.

5G Physical Layer: Principles, Models and Technology Components explains fundamental physical layer design principles, models and components for the 5G new radio access technology – 5G New Radio (NR). The physical layer models include radio wave propagation and hardware impairments for the full range of frequencies considered for the 5G NR (up to 100 GHz). The physical layer technologies include flexible multi-carrier waveforms, advanced multi-antenna solutions, and channel coding schemes for a wide range of services, deployments, and frequencies envisioned for 5G and beyond. A MATLAB-based link level simulator is included to explore various design options. 5G Physical Layer is very suitable for wireless system designers and researchers: basic understanding of communication theory and signal processing is assumed, but familiarity with 4G and 5G standards is not required. With this book the reader will learn: The fundamentals of the 5G NR physical layer (waveform, modulation, numerology, channel codes, and multi-antenna schemes). Why certain PHY technologies have been adopted for the 5G NR. The fundamental physical limitations imposed by radio wave propagation and hardware impairments. How the fundamental 5G NR physical layer functionalities (e.g., parameters/methods/schemes) should be realized. The content includes: A global view of 5G development – concept, standardization, spectrum allocation, use cases and requirements, trials, and future commercial deployments. The fundamentals behind the 5G NR physical layer specification in 3GPP. Radio wave propagation and channel modeling for 5G and beyond. Modeling of hardware impairments for future base stations and devices. Flexible multi-carrier waveforms, multi-antenna solutions, and channel coding schemes for 5G and beyond. A simulator including hardware impairments, radio propagation, and various waveforms. Ali Zaidi is a strategic product manager at Ericsson, Sweden. Fredrik Athley is a senior researcher at Ericsson, Sweden. Jonas Medbo and Ulf Gustavsson are senior specialists at Ericsson, Sweden. Xiaoming Chen is a professor at Xi’an Jiaotong University, China. Giuseppe Durisi is a professor at Chalmers University of Technology, Sweden, and a guest researcher at Ericsson, Sweden.

The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource, can meet the above requirements, and hence, it is a promising candidate technology for next generations of wireless systems. With massive antenna arrays at the BS, for most propagation environments, the channels become favorable, i.e., the channel vectors between the users and the BS are (nearly) pairwisely orthogonal, and hence, linear processing is nearly optimal. A huge throughput and energy efficiency can be achieved due to the multiplexing gain and the array gain. In particular, with a simple power control scheme, Massive MIMO can offer uniformly good service for all users. In this dissertation, we focus on the performance of Massive MIMO. The dissertation consists of two main parts: fundamentals and system designs of Massive MIMO. In the first part, we focus on fundamental limits of the system performance under practical constraints such as low complexity processing, limited length of each coherence interval, intercell interference, and finite-dimensional channels. We first study the potential for power savings of the Massive MIMO uplink with maximum-ratio combining (MRC), zero-forcing, and minimum mean-square error receivers, under perfect and imperfect channels. The energy and spectral efficiency tradeoff is investigated. Secondly, we consider a physical channel model where the angular domain is divided into a finite number of distinct directions. A lower bound on the capacity is derived, and the effect of pilot contamination in this finite-dimensional channel model is analyzed. Finally, some aspects of favorable propagation in Massive MIMO under Rayleigh fading and line-of-sight (LoS) channels are investigated. We show that both Rayleigh fading and LoS environments offer favorable propagation. In the second part, based on the fundamental analysis in the first part, we propose some system designs for Massive MIMO. The acquisition of channel state information (CSI) is very importantin Massive MIMO. Typically, the channels are estimated at the BS through uplink training. Owing to the limited length of the coherence interval, the system performance is limited by pilot contamination. To reduce the pilot contamination effect, we propose an eigenvalue-decomposition-based scheme to estimate the channel directly from the received data. The proposed scheme results in better performance compared with the conventional training schemes due to the reduced pilot contamination. Another important issue of CSI acquisition in Massive MIMO is how to acquire CSI at the users. To address this issue, we propose two channel estimation schemes at the users: i) a downlink "beamforming training" scheme, and ii) a method for blind estimation of the effective downlink channel gains. In both schemes, the channel estimation overhead is independent of the number of BS antennas. We also derive the optimal pilot and data powers as well as the training duration allocation to maximize the sum spectral efficiency of the Massive MIMO uplink with MRC receivers, for a given total energy budget spent in a coherence interval. Finally, applications of Massive MIMO in relay channels are proposed and analyzed. Specifically, we consider multipair relaying systems where many sources simultaneously communicate with many destinations in the same time-frequency resource with the help of a massive MIMO relay. A massive MIMO relay is equipped with many collocated or distributed antennas. We consider different duplexing modes (full-duplex and half-duplex) and different relaying protocols (amplify-and-forward, decode-and-forward, two-way relaying, and one-way relaying) at the relay. The potential benefits of massive MIMO technology in these relaying systems are explored in terms of spectral efficiency and power efficiency.

Build scalable, cost-effective, high-performance, and secure architectures using AWS Outposts, AWS Local Zones, AWS Wavelength, and AWS Snow services guided by best practices and practical examples Key Features Take advantage of the opportunities and challenges arising from the exponential growth of connected devices Use AWS edge compute services to extend your applications to wherever they are needed Follow guided tutorials for building an IIoT gateway and a distributed edge application with AWS services Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe surge in connected edge devices has driven organizations to capitalize on the opportunities presented by the massive amounts of data generated by these devices. However, adapting to this landscape demands significant changes in application architectures. This book serves as your guide to edge computing fundamentals, shedding light on the constraints and risks inherent in selecting solutions within this domain. You’ll explore an extensive suite of edge computing services from AWS, gaining insights into when and how to use AWS Outposts, AWS Wavelength, AWS Local Zones, AWS Snow Family, and AWS IoT Greengrass. With detailed use cases, technical requirements, and architectural patterns, you’ll master the practical implementation of these services and see how they work in real life through step-by-step examples, using the AWS CLI and AWS Management Console. To conclude, you’ll delve into essential security and operational considerations to maximize the value delivered by AWS services. By the end of this book, you'll be ready to design powerful edge computing architectures and handle complex edge computing use cases across multiple AWS services.What you will learn Overcome network challenges faced at the near and far edge Leverage services in over 450 points of presence at the edge of the AWS global backbone Deploy edge solutions in disconnected scenarios using AWS Snow Family Build multi-access edge (MEC) solutions with 5G and AWS Wavelength Reduce latency for your users with AWS Local Zones Configure AWS Snowcone as an IIoT gateway with AWS IoT Greengrass Extend your AWS VPC into your on-premise data center with AWS Outposts Deploy distributed applications for core, near, and far edge cloud services Who this book is for This book is designed for cloud architects, cloud engineers, solutions architects, and IoT architects tasked with building edge compute solutions using AWS. If you want to master the full range of edge computing services offered by AWS, this book is for you. A basic understanding of AWS services and networking is assumed.