LTE Spectrum Sharing Research Testbed: Integrated Hardware, Software, Network and Data

This paper presents Virginia Tech's wireless testbed supporting research on long-term evolution (LTE) signaling and radio frequency (RF) spectrum coexistence. LTE is continuously refined and new features released. As the communications contexts for LTE expand, new research problems arise and include operation in harsh RF signaling environments and coexistence with other radios. Our testbed provides an integrated research tool for investigating these and other research problems; it allows analyzing the severity of the problem, designing and rapidly prototyping solutions, and assessing them with standard-compliant equipment and test procedures. The modular testbed integrates general-purpose software-defined radio hardware, LTE-specific test equipment, RF components, free open-source and commercial LTE software, a configurable RF network and recorded radar waveform samples. It supports RF channel emulated and over-the-air radiated modes. The testbed can be remotely accessed and configured. An RF switching network allows for designing many different experiments that can involve a variety of real and virtual radios with support for multiple-input multiple-output (MIMO) antenna operation. We present the testbed, the research it has enabled and some valuable lessons that we learned and that may help designing, developing, and operating future wireless testbeds.Comment: In Proceeding of the 10th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization (WiNTECH), Snowbird, Utah, October 201

Real-Time Waveform Prototyping

Mobile Netzwerke der fünften Generation zeichen sich aus durch vielfältigen Anforderungen und Einsatzszenarien. Drei unterschiedliche Anwendungsfälle sind hierbei besonders relevant: 1) Industrie-Applikationen fordern Echtzeitfunkübertragungen mit besonders niedrigen Ausfallraten. 2) Internet-of-things-Anwendungen erfordern die Anbindung einer Vielzahl von verteilten Sensoren. 3) Die Datenraten für Anwendung wie z.B. der Übermittlung von Videoinhalten sind massiv gestiegen. Diese zum Teil gegensätzlichen Erwartungen veranlassen Forscher und Ingenieure dazu, neue Konzepte und Technologien für zukünftige drahtlose Kommunikationssysteme in Betracht zu ziehen. Ziel ist es, aus einer Vielzahl neuer Ideen vielversprechende Kandidatentechnologien zu identifizieren und zu entscheiden, welche für die Umsetzung in zukünftige Produkte geeignet sind. Die Herausforderungen, diese Anforderungen zu erreichen, liegen jedoch jenseits der Möglichkeiten, die eine einzelne Verarbeitungsschicht in einem drahtlosen Netzwerk bieten kann. Daher müssen mehrere Forschungsbereiche Forschungsideen gemeinsam nutzen. Diese Arbeit beschreibt daher eine Plattform als Basis für zukünftige experimentelle Erforschung von drahtlosen Netzwerken unter reellen Bedingungen. Es werden folgende drei Aspekte näher vorgestellt: Zunächst erfolgt ein Überblick über moderne Prototypen und Testbed-Lösungen, die auf großes Interesse, Nachfrage, aber auch Förderungsmöglichkeiten stoßen. Allerdings ist der Entwicklungsaufwand nicht unerheblich und richtet sich stark nach den gewählten Eigenschaften der Plattform. Der Auswahlprozess ist jedoch aufgrund der Menge der verfügbaren Optionen und ihrer jeweiligen (versteckten) Implikationen komplex. Daher wird ein Leitfaden anhand verschiedener Beispiele vorgestellt, mit dem Ziel Erwartungen im Vergleich zu den für den Prototyp erforderlichen Aufwänden zu bewerten. Zweitens wird ein flexibler, aber echtzeitfähiger Signalprozessor eingeführt, der auf einer software-programmierbaren Funkplattform läuft. Der Prozessor ermöglicht die Rekonfiguration wichtiger Parameter der physikalischen Schicht während der Laufzeit, um eine Vielzahl moderner Wellenformen zu erzeugen. Es werden vier Parametereinstellungen 'LLC', 'WiFi', 'eMBB' und 'IoT' vorgestellt, um die Anforderungen der verschiedenen drahtlosen Anwendungen widerzuspiegeln. Diese werden dann zur Evaluierung der die in dieser Arbeit vorgestellte Implementierung herangezogen. Drittens wird durch die Einführung einer generischen Testinfrastruktur die Einbeziehung externer Partner aus der Ferne ermöglicht. Das Testfeld kann hier für verschiedenste Experimente flexibel auf die Anforderungen drahtloser Technologien zugeschnitten werden. Mit Hilfe der Testinfrastruktur wird die Leistung des vorgestellten Transceivers hinsichtlich Latenz, erreichbarem Durchsatz und Paketfehlerraten bewertet. Die öffentliche Demonstration eines taktilen Internet-Prototypen, unter Verwendung von Roboterarmen in einer Mehrbenutzerumgebung, konnte erfolgreich durchgeführt und bei mehreren Gelegenheiten präsentiert werden.:List of figures List of tables Abbreviations Notations 1 Introduction 1.1 Wireless applications 1.2 Motivation 1.3 Software-Defined Radio 1.4 State of the art 1.5 Testbed 1.6 Summary 2 Background 2.1 System Model 2.2 PHY Layer Structure 2.3 Generalized Frequency Division Multiplexing 2.4 Wireless Standards 2.4.1 IEEE 802.15.4 2.4.2 802.11 WLAN 2.4.3 LTE 2.4.4 Low Latency Industrial Wireless Communications 2.4.5 Summary 3 Wireless Prototyping 3.1 Testbed Examples 3.1.1 PHY - focused Testbeds 3.1.2 MAC - focused Testbeds 3.1.3 Network - focused testbeds 3.1.4 Generic testbeds 3.2 Considerations 3.3 Use cases and Scenarios 3.4 Requirements 3.5 Methodology 3.6 Hardware Platform 3.6.1 Host 3.6.2 FPGA 3.6.3 Hybrid 3.6.4 ASIC 3.7 Software Platform 3.7.1 Testbed Management Frameworks 3.7.2 Development Frameworks 3.7.3 Software Implementations 3.8 Deployment 3.9 Discussion 3.10 Conclusion 4 Flexible Transceiver 4.1 Signal Processing Modules 4.1.1 MAC interface 4.1.2 Encoding and Mapping 4.1.3 Modem 4.1.4 Post modem processing 4.1.5 Synchronization 4.1.6 Channel Estimation and Equalization 4.1.7 Demapping 4.1.8 Flexible Configuration 4.2 Analysis 4.2.1 Numerical Precision 4.2.2 Spectral analysis 4.2.3 Latency 4.2.4 Resource Consumption 4.3 Discussion 4.3.1 Extension to MIMO 4.4 Summary 5 Testbed 5.1 Infrastructure 5.2 Automation 5.3 Software Defined Radio Platform 5.4 Radio Frequency Front-end 5.4.1 Sub 6 GHz front-end 5.4.2 26 GHz mmWave front-end 5.5 Performance evaluation 5.6 Summary 6 Experiments 6.1 Single Link 6.1.1 Infrastructure 6.1.2 Single Link Experiments 6.1.3 End-to-End 6.2 Multi-User 6.3 26 GHz mmWave experimentation 6.4 Summary 7 Key lessons 7.1 Limitations Experienced During Development 7.2 Prototyping Future 7.3 Open points 7.4 Workflow 7.5 Summary 8 Conclusions 8.1 Future Work 8.1.1 Prototyping Workflow 8.1.2 Flexible Transceiver Core 8.1.3 Experimental Data-sets 8.1.4 Evolved Access Point Prototype For Industrial Networks 8.1.5 Testbed Standardization A Additional Resources A.1 Fourier Transform Blocks A.2 Resource Consumption A.3 Channel Sounding using Chirp sequences A.3.1 SNR Estimation A.3.2 Channel Estimation A.4 Hardware part listThe demand to achieve higher data rates for the Enhanced Mobile Broadband scenario and novel fifth generation use cases like Ultra-Reliable Low-Latency and Massive Machine-type Communications drive researchers and engineers to consider new concepts and technologies for future wireless communication systems. The goal is to identify promising candidate technologies among a vast number of new ideas and to decide, which are suitable for implementation in future products. However, the challenges to achieve those demands are beyond the capabilities a single processing layer in a wireless network can offer. Therefore, several research domains have to collaboratively exploit research ideas. This thesis presents a platform to provide a base for future applied research on wireless networks. Firstly, by giving an overview of state-of-the-art prototypes and testbed solutions. Secondly by introducing a flexible, yet real-time physical layer signal processor running on a software defined radio platform. The processor enables reconfiguring important parameters of the physical layer during run-time in order to create a multitude of modern waveforms. Thirdly, by introducing a generic test infrastructure, which can be tailored to prototype diverse wireless technology and which is remotely accessible in order to invite new ideas by third parties. Using the test infrastructure, the performance of the flexible transceiver is evaluated regarding latency, achievable throughput and packet error rates.:List of figures List of tables Abbreviations Notations 1 Introduction 1.1 Wireless applications 1.2 Motivation 1.3 Software-Defined Radio 1.4 State of the art 1.5 Testbed 1.6 Summary 2 Background 2.1 System Model 2.2 PHY Layer Structure 2.3 Generalized Frequency Division Multiplexing 2.4 Wireless Standards 2.4.1 IEEE 802.15.4 2.4.2 802.11 WLAN 2.4.3 LTE 2.4.4 Low Latency Industrial Wireless Communications 2.4.5 Summary 3 Wireless Prototyping 3.1 Testbed Examples 3.1.1 PHY - focused Testbeds 3.1.2 MAC - focused Testbeds 3.1.3 Network - focused testbeds 3.1.4 Generic testbeds 3.2 Considerations 3.3 Use cases and Scenarios 3.4 Requirements 3.5 Methodology 3.6 Hardware Platform 3.6.1 Host 3.6.2 FPGA 3.6.3 Hybrid 3.6.4 ASIC 3.7 Software Platform 3.7.1 Testbed Management Frameworks 3.7.2 Development Frameworks 3.7.3 Software Implementations 3.8 Deployment 3.9 Discussion 3.10 Conclusion 4 Flexible Transceiver 4.1 Signal Processing Modules 4.1.1 MAC interface 4.1.2 Encoding and Mapping 4.1.3 Modem 4.1.4 Post modem processing 4.1.5 Synchronization 4.1.6 Channel Estimation and Equalization 4.1.7 Demapping 4.1.8 Flexible Configuration 4.2 Analysis 4.2.1 Numerical Precision 4.2.2 Spectral analysis 4.2.3 Latency 4.2.4 Resource Consumption 4.3 Discussion 4.3.1 Extension to MIMO 4.4 Summary 5 Testbed 5.1 Infrastructure 5.2 Automation 5.3 Software Defined Radio Platform 5.4 Radio Frequency Front-end 5.4.1 Sub 6 GHz front-end 5.4.2 26 GHz mmWave front-end 5.5 Performance evaluation 5.6 Summary 6 Experiments 6.1 Single Link 6.1.1 Infrastructure 6.1.2 Single Link Experiments 6.1.3 End-to-End 6.2 Multi-User 6.3 26 GHz mmWave experimentation 6.4 Summary 7 Key lessons 7.1 Limitations Experienced During Development 7.2 Prototyping Future 7.3 Open points 7.4 Workflow 7.5 Summary 8 Conclusions 8.1 Future Work 8.1.1 Prototyping Workflow 8.1.2 Flexible Transceiver Core 8.1.3 Experimental Data-sets 8.1.4 Evolved Access Point Prototype For Industrial Networks 8.1.5 Testbed Standardization A Additional Resources A.1 Fourier Transform Blocks A.2 Resource Consumption A.3 Channel Sounding using Chirp sequences A.3.1 SNR Estimation A.3.2 Channel Estimation A.4 Hardware part lis

Design of a Drone-Flight-Enabled Wireless Isolation Chamber

The next wave of drone applications is moving from repeatable, single-drone activities such as evaluating propagation environments to team-based, multi-drone objectives such as drone-based emergency services. In parallel, testbeds have sought to evaluate emerging concepts such as highly-directional and distributed wireless communications. However, there is a lack of intersection between the two works to characterize the impact of the drone body, antenna placement, swarm topologies, and multi-dimensional connectivity needs that require in-flight experimentation with a surrounding testbed infrastructure. In this work, we design a drone-flight-enabled isolation chamber to capture complex spatial wireless channel relationships that drone links experience as applications scale from single-drone to swarm-level networks within a shared three-dimensional space. Driven by the challenges of outdoor experimentation, we identify the need for a highly-controlled indoor environment where external factors can be mitigated. To do so, we first build an open-source drone platform to provide programmable control with visibility into the internal flight control system and sensors enabling specialized coordination and accurate repeatable positioning within the isolated environment. We then design a wireless data acquisition system and integrate distributed software defined radios (SDRs) in order to inspect multi-dimensional wireless behavior from the surrounding area. Finally, we achieve and demonstrate the value of measurement perspectives from diverse altitudes and spatial locations with the same notion of time

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

Towards addressing training data scarcity challenge in emerging radio access networks: a survey and framework

The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch automation, a myriad of AI-based solutions are being proposed in literature to leverage AI for modeling and optimizing network behavior to achieve the zero-touch automation goal. However, to work reliably, AI based automation, requires a deluge of training data. Consequently, the success of the proposed AI solutions is limited by a fundamental challenge faced by cellular network research community: scarcity of the training data. In this paper, we present an extensive review of classic and emerging techniques to address this challenge. We first identify the common data types in RAN and their known use-cases. We then present a taxonomized survey of techniques used in literature to address training data scarcity for various data types. This is followed by a framework to address the training data scarcity. The proposed framework builds on available information and combination of techniques including interpolation, domain-knowledge based, generative adversarial neural networks, transfer learning, autoencoders, fewshot learning, simulators and testbeds. Potential new techniques to enrich scarce data in cellular networks are also proposed, such as by matrix completion theory, and domain knowledge-based techniques leveraging different types of network geometries and network parameters. In addition, an overview of state-of-the art simulators and testbeds is also presented to make readers aware of current and emerging platforms to access real data in order to overcome the data scarcity challenge. The extensive survey of training data scarcity addressing techniques combined with proposed framework to select a suitable technique for given type of data, can assist researchers and network operators in choosing the appropriate methods to overcome the data scarcity challenge in leveraging AI to radio access network automation

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

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure