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Due to the fast growth of diverse wireless network deployments, the radio spectrum is becoming scarce. Hence, it is beneficial that different radio access technologies share the spectrum in a harmonious way. In this paper, we propose a co-existence scheme between Long Term Evolution (LTE) and Wi-Fi networks that utilizes a Multimedia Broadcast Multicast Service (MBMS) over a Single Frequency Network (MBSFN) feature of an LTE network. MBSFN is an LTE feature that provides support for multicast/broadcast traffic. We propose an adaptive scheme that configures muted subframes, initially intended for MBSFN operation, to allow Wi-Fi transmissions. For the adaptive configuration of muted MBSFN subframes, the LTE eNB uses its traffic queue and the Wi-Fi spectrum occupancy information, which is determined by a convolutional neural network-based technology recognition and traffic characterization system. The standard LTE System Information Blocks are used to convey the updated configuration to the LTE UE. Hence, the proposed coexistence scheme doesn’t require any modifications to a standard MBSFN-compliant LTE UE. Performance analysis is done for various traffic situations, and the results show that muted MBSFN subframe-based coexistence gives a 15% improvement in average aggregated throughput as compared to using Almost Blank Subframe-based coexistence.

ispartof: pages:287-292 ispartof: Proceedings of the 16th ACM Conference on Security and Privacy in Wireless and Mobile Networks pages:287-292 ispartof: ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) location:Guildford, Surrey, United Kingdom date:29 May - 1 Jun 2023 status: Published online

With the advent of deep learning (DL), various automatic modulation classification (AMC) methods using deep learning architectures achieved significant performance improvements compared to conventional algorithms. Aiming to achieve high classification accuracy, DL-based AMC algorithms require numerous annotated training samples for each modulation class to extract salient features, but it is hardly applicable in real-world AMC applications. To tackle the annotated data scarce issue, this paper proposes a novel few-shot learning (FSL) framework, which introduces a relation network with a denoising autoencoder to extract feature representations effectively from a limited dataset. The experimental result demonstrate that the proposed method can achieve higher classification accuracy compared to the conventional FSL algorithm for signal modulation recognition, especially in low signal to noise ratio conditions.

Industrial communication systems provide deterministic and reliable communication between various industrial components. In the past several decades, different communication technologies (Fieldbus, Real-Time Ethernet (RTE)) were used to achieve such determinism. Recently, Time-Sensitive Networking (TSN) is being utilized in industrial environments to support end-to-end low latency deterministic communication by providing mechanisms for accurate time synchronization, traffic scheduling/shaping, and reliability. With many use cases requiring portability and seamless mobility, such features are being developed for wireless networks as well, expanding the time-sensitive communication to the wireless domain. Wireless TSN’s aim is to provide wired TSN-like features, achieving wired-wireless interoperability and flattening the automation system pyramid. In this paper, we present an integration between the wireless TSN and PROFINET. We show that the safety-related applications can be supported seamlessly, providing deterministic communication and reliability under best-effort traffic load in the wireless network. The solution is evaluated in terms of the achieved end-to-end latency and the probability of failure per hour of the fail-safe communication. It is shown that by using wireless time-sensitive networking with dedicated time slots per traffic flow a safety integrity level up to grade 4 can be achieved.

Time-sensitive networking (TSN) is utilized in industrial environments to support reliable low-latency communications. Bringing TSN features to wireless networks is getting traction recently by achieving time synchronization and traffic scheduling over wireless links. Besides these basic features, impact-less and network transparent association of prospective clients is paramount for wireless TSN. This demo presents an impactless TSN association procedure, where beacons are used to provide time synchronization and scheduling to prospective clients, where association procedure is done in reserved time slots. The presented demo is designed, implemented, and tested on top of a wireless Software Defined Radio platform using the IEEE802.11 standard. By utilizing a dashboard, this demo will demonstrate real-time control over association as well as high accuracy synchronization on client frame transmissions even with challenging scheduling configuration of 128 μ S timeslots.

The recently introduced 5G New Radio is the first wireless standard natively designed to support critical and massive machine type communications (MTC). However, it is already becoming evident that some of the more demanding requirements for MTC cannot be fully supported by 5G networks. Alongside, emerging use cases and applications towards 2030 will give rise to new and more stringent requirements on wireless connectivity in general and MTC in particular. Next generation wireless networks, namely 6G, should therefore be an agile and efficient convergent network designed to meet the diverse and challenging requirements anticipated by 2030. This paper explores the main drivers and requirements of MTC towards 6G, and discusses a wide variety of enabling technologies. More specifically, we first explore the emerging key performance indicators for MTC in 6G. Thereafter, we present a vision for an MTC-optimized holistic end-to-end network architecture. Finally, key enablers towards (1) ultra-low power MTC, (2) massively scalable global connectivity, (3) critical and dependable MTC, and (4) security and privacy preserving schemes for MTC are detailed. Our main objective is to present a set of research directions considering different aspects for an MTC-optimized 6G network in the 2030-era.

The future 5G wireless infrastructure will support any-to-any connectivity between densely deployed smart objects that form the emerging paradigm known as the Internet of Everything (IoE). Compared to traditional wireless networks that enable communication between devices using a single technology, 5G networks will need to support seamless connectivity between heterogeneous wireless objects and IoE networks. To tackle the complexity and versatility of future IoE networks, 5G will need to guarantee optimal usage of both spectrum and energy resources and further support technology-agnostic connectivity between objects. One way to realize this is to combine intelligent network control with adaptive software defined air interfaces. In this paper, a flexible and compact platform is proposed for on-the-fly composition of low-power adaptive air interfaces, based on hardware/software co-processing. Compared to traditional Software Defined Radio (SDR) systems that perform computationally-intensive signal processing algorithms in software, consume significantly power and have a large form factor, the proposed platform uses modern hybrid FPGA technology combined with novel ideas such as RF Network-on-Chip (RFNoC) and partial reconfiguration. The resulting system enables composition of reconfigurable air interfaces based on hardware/software co-processing on a single chip, allowing high processing throughput, at a smaller form factor and reduced power consumption., Comment: 9 pages, 3 figures

To enhance system performance of future heterogeneous wireless networks the co-design of PHY, MAC, and higher layer protocols is inevitable. In this work, we present WiSCoP - a novel embedded platform for experimentation, prototyping and implementation of integrated cross-layer network design approaches. WiSCoP is built on top of a Zynq hardware platform integrated with FMCOMMS1/2/4 RF front ends. We demonstrate the flexibility of WiSCoP by using it to prototype a fully standard compliant IEEE 802.15.4 stack with real-time performance and cross-layer integration., Comment: 2 pages, 2 figures, to be published in the EWSN'17 Proceedings of the 2017 International Conference on Embedded Wireless Systems and Networks, Uppsala, Sweden - February 20-22, 2017

In the last years, we have assisted to an impressive evolution of wireless technologies for short distance communication (like IEEE 802.11, IEEE 802.15.4. Bluetooth Low Energy, etc.) due to the need of coping with the heterogeneous requirements of emerging applications, such as Internet of things, the Industry 4.0, the Tactile Internet, the ambient assistant living, and so on. Indeed, for optimizing the technology performance in these scenarios, it is often required to support some forms of protocol adaptation, by allowing the dynamic reconfiguration of protocol parameters and the dynamic activation of optional mechanisms, or some targeted protocol extensions.In both cases, prototyping, testing and experimentally validating potential solutions is a complex task, which generally requires significant time and resource investment. On one side, off-the-shelf wireless interfaces are based on radio chips which implement only the obligatory parts of the standards and arbitrarily selected optional parts, with only partially documented interfaces and with drivers being either closed or limited in functionality. On the other side, many powerful Software Defined Radio (SDR) platforms, while offering excellent flexibility at the physical layer, typically have limited performance and lack high-level specifications and programming tools as well as standard APIs for developing protocols. Consequently, testing of new solutions often proves problematic, as experimenters can only rely on the limited optimization space enabled by the drivers, or on open software architectures where many functionalities have to be written from scratch and are tightly dependent on the specific hardware platform. In many cases, different experimentation platforms have ss, because experimenters have to be familiar with platform-specific architectures and programming tools before prototyping their solutions. To overcome the aforementioned shortcomings and reduce the threshold for experimentation, we propose a novel approach within the European project WiSHFUL [1]. The project main goal is the design and development of a software architecture enabling a flexible radio and network control of heterogeneous experimentation platforms, based on standardized wireless technologies and SDRs, through unified programming interfaces. More specifically, the architecture is devised to allow: Maximal exploitation of radio functionalities available in current radio chips, as opposed to today’s radio drivers that restrict radio functionality. For example today’s radio drivers for IEEE 802.11 do not supportTDMA (Time Division Multiple Access) operation, while the hardware perfectly supports it. Clean separation between radio control and protocol logic, as opposed to today’s monolithic implementations, which do not allow to work separately on the logic for enabling specific protocol features and the definition of these features. To frame this effort, several driving scenarios were identified to capture the challenges associated with the increasing density and heterogeneity of wireless devices in a concrete and tangible manner. These scenarios directly present a set of relevant and significant requirements for developing the functionalities required by the WiSHFUL control framework in order to investigate the challenges of future wireless systems experimentation. Each showcase focuses on a different source for inter-device and inter-technology interference and displays a scenario, which requires novel experimentation functionalities. Following the definition of this set of motivating scenarios, an architecture is presented to support future wireless experimentation. This architecture is constructed to address the requirements of the tangible scenarios, capturing key challenges of future systems while allowing for extensions to support investigation of as yet unforeseen challenges.

International audience

The Forging Online Education through FIRE (FORGE) initiative provides educators and learners in higher education with access to world-class FIRE testbed infrastructure. FORGE supports experimentally driven research in an eLearning environment by complementing traditional classroom and online courses with interactive remote laboratory experiments. The project has achieved its objectives by defining and implementing a framework called FORGEBox. This framework offers the methodology, environment, tools and resources to support the creation of HTML-based online educational material capable accessing virtualized and physical FIRE testbed infrastruc- ture easily. FORGEBox also captures valuable quantitative and qualitative learning analytic information using questionnaires and Learning Analytics that can help optimise and support student learning. To date, FORGE has produced courses covering a wide range of networking and communication domains. These are freely available from FORGEBox.eu and have resulted in over 24,000 experiments undertaken by more than 1,800 students across\ud 10 countries worldwide. This work has shown that the use of remote high- performance testbed facilities for hands-on remote experimentation can have a valuable impact on the learning experience for both educators and learners. Additionally, certain challenges in developing FIRE-based courseware have been identified, which has led to a set of recommendations in order to support the use of FIRE facilities for teaching and learning purposes.

Experimental analysis of 5 GHz WiFi and UHF-TVWS hybrid Wireless Mesh Network back-haul links -- High-level and Compact Design of Cross-channel LTE DownLink Channel Encoder -- Detection of Different Wireless Protocols on an FPGA with the Same Analog/RF Front End -- Demonstration of Shared Spectrum Access of Different User Groups -- A Low-Latency Wireless Network for Cloud-Based Robot Control -- Comparison of incumbent user privacy preserving technologies in database driven dynamic spectrum access systems -- Spectrum Leasing for Micro-Operators Using Blockchain Networks -- SZ-SAS: A Framework for Preserving Incumbent User -- Privacy in SAS-based DSA Systems -- Secrecy Outage Probability of Cognitive Small-Cell Network with Unreliable Backhaul Connections -- Polarization-Space Based Interference Alignment for Cognitive Heterogeneous Cellular Network -- The vision of 5G and the need for change in mobile spectrum access -- Coexistence of LTE Networks Under LSA Paradigm in 2.6 GHz -- Pricing Private LTE and 5G Radio Licenses on 3.5 GHz -- LSA System Development with Sensing for Rapidly Deployable LTE Network -- Maxmin Strategy for a Dual Radar and Communication -- OFDM Waveforms System facing Uncertainty about the Background Noise -- Using Deep Learning and Radio Virtualisation for Efficient Spectrum Sharing among Coexisting Networks -- PHY and Sensing -- Evaluating Deep Neural Networks to classify Modulated and Coded Radio Signals -- Improving Spectrum Efficiency in Heterogeneous Networks using Granular Identification -- Interference Rejection Combining for Black-Space Cognitive Radio Communications -- An Image Processing Approach to Wideband Spectrum Sensing of Heterogeneous Signals. .