As industries become more digitized, they are entering a new era of connectivity based on 5G and beyond technology features. This transformation brings new challenges such as interference between public and non-public networks. In this study, we investigate the automatic configuration of non-public networks using a Machine Learning-based What-if Analysis technique to mitigate interference and enhance 5G NR networks coexistence. This proactive decision-making solution is designed for various coexistence scenarios, namely adjacent and co-channel. It provides a systematic approach for selecting the most suitable network parameters and configurations. We validate our approach through experimental analysis, with a particular focus on selecting and analyzing the TDD pattern and link robustness for 5G NR non-public network deployments. Our analysis is based on real-world experiments carried out at the 5G Industry Campus Europe in Aachen, Germany.

Digitalization of industries is essential for achieving the ever-increasing demands for flexible and customized production. Wireless communication plays a key role in enabling digitalization of industries. Cellular communication systems are expected to efficiently support data traffic with varying sets of requirements on latency, reliability and throughput as well as mobility and scalability in industrial applications. In this paper, we describe a framework that enables closed-loop runtime adaptation of a cellular network configuration using artificial intelligence and machine learning ($\mathrm{AI} / \mathrm{ML}$) methods based on the observed network performance characteristics and dynamic changes in application service level requirements. While most of the existing works on the use of $\mathrm{AI} / \mathrm{ML}$ methods for 5 G performance enhancement are based on computer simulations, our framework has been experimentally evaluated on an industrial 5G non-public network in an industrial environment. We present over-the-air empirical performance results of a 5 G non-public network deployment in the local industrial spectrum in Germany. Our empirical results give insights into 5G deployments in industrial environments and highlight that the desired communication robustness for a mobile robotics use case can be achieved with efficient use of radio resources using deep reinforcement learning.

5G New Radio (NR) non-public network deployments for industrial and enterprise applications are becoming highly popular in locally licensed and/or operator spectrum. The interference from coexisting networks on adjacent channels (in same or adjacent spectrum bands) could potentially deteriorate the performance characteristics in certain deployment scenarios. Appropriate interference mitigation is thus required to achieve the desired performance levels. In this paper, we present our detailed empirical results on the performance impact of coexisting 5G NR networks operating on adjacent channels. Our experimental study conducted on an industrial shopfloor reports the impact on the downlink and uplink latency and throughput when using the same and different Time Division Duplexing patterns for coexisting networks. Our empirical evaluation includes realistic user equipment deployment locations and traffic load conditions. We also present our results on different mitigation techniques to counter the adjacent channel interference effects.

Converged networks require new service protection functionalities to ensure reliable and robust communications. This paper provides insights into the evolution of deterministic communication and the importance of service protection in converged networks. We examine the per-packet-based replication/elimination service protection mechanism, ongoing standardization efforts, and potential areas for further development. We also explore the practical implementation of the service protection technique in real network scenarios, including its impact on operation and maintenance. The main contributions of the paper are: (1) new cloud-specific extensions to the service protection functionality, (2) introduction of redundancy domains to avoid replication/elimination-related failure propagation, (3) new service protection specific extensions to the network operation toolset, and (4) new diagnostic capabilities to monitor the healthiness of the service protection functionalities. Additionally, we evaluate the effectiveness and operation of newly proposed service protection extensions based on experimental results from a real 5G testbed.

The 3rd Generation Partnership Project (3GPP) has introduced technical features for Non-Public Networks (NPN), allowing highly flexible and dedicated 5G deployments for Industry 4.0 applications. This paper presents insights into the early adoption of a 5G Public Network Integration Non-Public Network (PNI-NPN) for industrial automation applications with observed network performance. Our contributions are threefold: (i) we present network design concepts to overcome the challenges of industrial use-cases and mobile network limitations, (ii) we propose network architecture over 5G Non-Standalone architecture (NSA), and (iii) we perform validation measurements with PROFINET and PROFIsafe communication. Our results – at a real industrial 5G setting – indicate that the proposed architecture is very promising for future 5G industrial deployments.

Autonomous Mobile Robots (AMRs) and mobile manipulators are becoming increasingly popular in industrial use cases, especially for flexible lineless assembly systems. These use cases require wireless communication with high reliability and jitter-minimized bounded latency. This paper describes an industrial use case, where edge-controlled AMRs collaboratively perform various screw installation tasks on a truck chassis. We integrate Time Sensitive Networking (TSN) features such as time synchronization and IEEE 802.1CB based Frame Replication and Elimination for Reliability (FRER) scheme with 5G wireless communication to realize this use case. Moreover, we apply hold and forward buffer (HFB) mechanism to minimize communication jitters. This paper highlights the performance benefits of the aforementioned TSN features for 5G communication in the edge-controlled AMR use case. Our empirical evaluation with over-the-air performance results obtained on an industrial shopfloor brings significant insights on using 5G for edge-controlled robotic use cases.

Industrial automation applications generally have stringent communication requirements in terms of low latency and high reliability. Existing wireless technologies operating in the unlicensed spectrum are unable to fulfill these requirements owing to the regulatory constraints for coexistence and spectrum sharing. In this paper, we (i) comprehensively analyze and classify the typical industrial automation applications based on their latency and reliability requirements, (ii) investigate the performance of LTE and its latency reduction and reliability enhancements, and (iii) identify which classes of industrial automation applications can be satisfied by using LTE and its enhancements. Our detailed system level simulation results indicate that LTE (release 14 and beyond) is able to satisfy the requirements for some of the identified industrial automation use-cases such as machine tools, production lines, and logistics.

The standardization of 5G New Radio (NR) has started and addresses a wide range of use-cases. The 5G application demands include among others, very high data rates, support for huge number of low-power devices and mission critical communication. NR design supports operation in both traditional licensed frequency spectrum bands as well as unlicensed frequencies. In this paper, we present some of the design aspects and architectural details of NR to support spectrum sharing in the unlicensed spectrum. Moreover, we present system level simulation results showing the NR spectrum sharing capabilities while complying with the regulatory requirements.

We consider a multichannel Cognitive Radio Network (CRN), where secondary users sequentially sense channels for opportunistic spectrum access. In this scenario, the Channel Selection Algorithm (CSA) allows secondary users to find a vacant channel with the minimal number of channel switches. Most of the existing CSA literature assumes exponential ON-OFF time distribution for primary user's (PU) channel occupancy pattern. This exponential assumption might be helpful to get performance bounds; but not useful to evaluate the performance of CSA under realistic conditions. An in-depth analysis of independent spectrum measurement traces reveals that wireless channels have typically heavy-tailed PU OFF times. In this paper, we propose an extension to the Predictive CSA framework and its generalization for heavy tailed PU OFF time distribution, which represents realistic scenarios. In particular, we calculate the probability of channel being idle for hyper-exponential OFF times to use in CSA. We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns. The proposed CSA shows significant reduction in channel switches and energy consumption as compared to Predictive CSA which always assumes exponential PU ON-OFF times. Through our work, we show the impact of the PU channel occupancy pattern on the performance of CSA in multichannel CRN.

Wireless factory automation has been receiving much interest in recent years due to its advantages of low cost and high flexibility over the traditional wired networks. Factory automation is also considered as one of the important use-cases of the 5th generation (5G) cellular system. In this paper, we present comprehensive system level simulation results to evaluate the performance of LTE and new 5G radio-interface design concepts in a realistic factory deployment scenario. We believe that our detailed evaluation studies bring valuable insights to show the potential of 3GPP technologies for different factory use-cases.

This over-the-air demo presents the coexistence features of LTE-U namely, (i) dynamic channel selection and (ii) adaptive radio duty cycle operation to allow symbiotic coexistence with collocated networks such as Wi-Fi. The LTE-U coexistence features are implemented on the WARP software defined radio platform with configurable parameter settings. A graphical user interface based application is developed for the demo to allow user interaction, on-the-fly configuration of the LTE-U coexistence parameters and display the live over-the-air performance characteristics.

In order to cope with the increasing complexity of wireless networks, dynamic spectrum access, and varying application needs, fast and flexible reconfiguration of protocol stack is desired. Since Medium Access Control (MAC) layer plays a pivotal role in providing efficient spectrum sharing and utilization, rapid on-the-fly reconfigurability of MAC protocols is highly important. We have designed and implemented TRUMP: a Toolchain for RUntiMe Protocol realization. Based on the component-oriented design approach, TRUMP allows runtime realization, reconfiguration, and optimization of MAC layer according to the varying application requirements, spectral environmental, and network conditions. TRUMP, with a platform-independent MAC meta-language, also enables rapid MAC prototyping. In this article, we carry out a detailed performance evaluation of MAC schemes realized through TRUMP on WARP SDR platform. Our results indicate that TRUMP allows reconfiguration of MAC schemes in the order of a few microseconds, thus meeting the strict timeliness requirements of MAC processing. We also present application examples to highlight capabilities of TRUMP.

The large contiguous bandwidths available in the mm-wave frequency bands have recently started to gain significant attention due to the growing belief that it can alleviate the spectrum shortage at lower frequencies and meet the increasing high data rate demands. While some commercially available mm-wave transceivers in the 60 GHz and 70 GHz bands have been developed, only a few studies exist on the achievable data rates in realistic deployment scenarios. Moreover, practical issues such as interference and coexistence of heterogeneous applications have not been investigated. In this paper, we present our empirical study on the bit error ratio and throughput for realistic indoor application scenarios in 60 GHz and 70GHz using orthogonal frequency division multiplexing based physical layer on various commercially available transceivers. Furthermore, we analyze the effects of interference on the performance characteristics of the mm-wave frequency links in different deployment setups.

Estimating the coverage of a wireless network is one of the key problems in network planning and management. In outdoor environments this is usually done using modern network planning tools combined with intensive drive tests. However, in indoor environments the problem is much more difficult. Solutions based on propagation modeling require precise building information for accuracy, and even then their performance is highly varying. Refining such predictions using measurements from mobile terminals is a promising possibility, but is not straightforward due to the noisy and unreliable measurement quality. In this paper we study the performance of spatial statistics techniques for coverage prediction in indoor environments. Using data collected in an indoor testbed with 60 low cost radio receivers, we show that such techniques can yield accurate coverage predictions provided suitable preprocessing and filtering of the data is performed. Further, a simple optimization approach enables high prediction accuracy to be achieved using only a small subset of the available measurement devices. These results are also highly relevant to the minimization of drive tests (MDT) approach currently being developed in 3GPP to enable mobile terminals carry out coverage measurements for wireless networks.

Recent years have witnessed a number of new and fairly complex MAC schemes for cognitive radios and other reconfigurable networks. These emerging MAC protocols impose increasing demands for flexibility, real-time response and a closer interaction between the MAC- and the physical layers. Different designs for Software Defined Radio (SDR) platforms have been investigated to realize these protocols. In this context, hardware acceleration and flexibility through hardware-software partitioning emerge as the major design considerations for prototyping and over-the-air evaluation. Following the hardware-software partitioning philosophy, this demonstration will show how MAC schemes can be decomposed into constituent functional components and how different MAC functionalities, when possible, are scheduled in a parallel fashion to enhance the execution efficiency and flexibility. In particular, we have enabled a dual-processor interrupt driven hardware architecture and supported a customized real-time Operating System (OS) kernel on the commercially available and widely used WARP SDR platform [1]. Moreover, we have adapted our framework for composing MAC protocols based on their elementary functionalities [2] to the dual-processor, OS-supported architecture on WARP boards. Our demonstration will highlight the benefits of parallelization and efficient scheduling of MAC processes in embedded realizations on SDR platforms in order to achieve a high degree of flexibility while satisfying the hard real-time constraints.

Various emerging applications enabled by wireless sensor networks demand new and versatile MAC algorithms. These MAC protocols should be able to adapt to varying application requirements and deployment conditions. In this paper, we present a component based scheme for enabling fast prototyping of MAC protocols using a lightweight tool chain. Our tool chain allows run-time MAC protocol reconfiguration by controlling the data path and the execution flow of the constituent components. Our approach of composing protocols based on common MAC components aims at reducing the protocol prototyping efforts. Moreover, our toolchain implemented for various sensor nodes provides a platform independent MAC meta-language which simplifies the protocol designing, testing and debugging processes. Empirical tests conducted on commercially available sensor nodes show that our approach enables run-time reconfiguration for MAC protocols with affordable memory consumption and execution overhead.

No abstract available.

A rapid reconfiguration of medium access scheme is required in order to achieve runtime performance optimization for dynamic spectrum access and fulfilling varying Quality of Service (QoS) demands. We have developed TRUMP, a toolchain which allows composing MAC solutions at runtime. In this demonstration, we will show how MAC reconfiguration can be achieved efficiently using TRUMP. Inspired by the optimum route calculation method used in car navigation systems, the compiler toolchain in TRUMP realizes an appropriate MAC solution at runtime. TRUMP allows expressing various types of constraints and options such as speed, energy consumption and packet delivery rate which leads to different MAC compositions. The live demonstration of MAC reconfiguration will be carried out on WARP SDR platform.

We empirically study problems of online estimation and modeling of radio activity (ON/OFF) patterns and their duty cycles. We consider performance of two algorithms that analyze power spectrum samples in time domain as sensed by WARP SDR boards placed at different indoor locations. The first algorithm utilizes density function of the marginal distribution of the received readings to perform clustering of the power samples into the classes that correspond to ON/OFF activity states. The second algorithm uses hidden Semi-Markov processes and the Viterbi algorithm to model and estimate the radio activity patterns of signal sources. Unlike the first algorithm it can also be used for both signal classification and estimation of the state duration that corresponds to the certain power level. We study signals obtained from one or two transmitters. Our results indicate the first technique can often provide accurate estimations. However, if sensor nodes receive low RSSI values or modeling of the temporal structure of the activity patterns is required then the second technique is preferable. This method also has a potential to benefit from cooperation between nodes.

Cognitive radios are becoming the technological foundation for efficiently managing the scarcity of wireless spectrum, fulfilling various QoS demands and allowing different networks to coexist. Cognition and spectrum agility in MAC protocols require adaptability and close PHY-MAC interaction. Classically, MAC protocols have been implemented in hardware, which gives a limited possibility for reconfiguration and customization. Recently, software based MAC implementations have emerged although a close hardware-software co-design is typically required to keep the time critical operations in ASICs or FPGAs. We introduce a MAC development framework for enabling fast composition of MAC protocols, which are best fitted to the application requirements, communication capabilities of the radio, and current spectrum regulations and policies. We decompose MAC protocols into their basic functionalities which are perceived as building blocks and are partitioned across hardware/software. Our framework allows on-the-fly realization of the envisioned MAC protocol through wiring of these fundamental components. By exposing extended metadata and hardware functionalities for the MAC implementation through our granular components, together with the support for run-time re-configuration, spectrum agile and cognitive MAC solutions can be easily realized. In this paper, we describe the design rationale and implementation details of our framework on WARP boards. We show through experimental evaluation that the framework provides flexible means for prototyping different reconfigurable cognitive and spectrum agile MAC protocols.

A wide-spread integration of Wireless Sensor Networks (WSNs) into daily life applications demands modular and flexible service oriented architectures. Discovering nodes and their services is imperative to any large-scale sensor network deployment. In this paper, we describe nanoSD, a lightweight service discovery protocol, designed for highly dynamic, mobile and heterogeneous sensor networks. We demonstrate through a fully functional implementation and its performance evaluation that nanoSD supports heterogeneous architectures and is scalable. It is able to efficiently cope network dynamics present in real WSN deployments. It uses features like delta service advertisements, message compression and piggy-backing techniques, which results in low network overhead. Furthermore, nanoSD protocol is easily integratable to web-service based backend systems using very limited resources.

In this paper we describe the design, implementation and performance evaluation of a low-power spectrum agile medium access control protocol for wireless sensor networks. With the ever increasing popularity of wireless embedded devices and networks, spectrum is getting congested, which in turn leads to performance degradation. Since protocols are designed in isolation of each other without appropriate consideration for potential interferences and mechanisms for symbiotic coexistence, they fail to achieve the desired performance characteristics in realistic interfering environments. The performance degradation is more significant for low-power embedded networks as they remain handicapped when competing with less resource constrained networks. We design a protocol that allows sensor nodes to dynamically select an interference minimal channel for data communication. It does not pose any synchronization restrictions on the nodes and effectively handles the dynamics of the network such as new nodes joining and old nodes leaving the network. We describe the various energy efficient spectrum sensing features of the protocol on which the dynamic channel selection is based. Our experiments suggest that even in highly crowded spectrum and environments with random interferences, sensor nodes are able to communicate in a reliable and energy efficient manner.

In this poster, we focus on the cross-layer design of a low-power traffic aware MAC protocol and a content and context based routing protocol. We describe the cross-layering aspects of the MAC-Routing framework and present the performance results on real sensor node testbed.

Wireless Sensor Networks (WSNs) have been deployed in a wide range of applications with different sensing and communication requirements. As a consequence, various MAC solutions have been proposed suiting to different application characteristics [1]. However, MAC protocols are typically implemented in a monolithic fashion -- specific to a particular hardware platform. This hinders the possibility of code re-use across different platforms, which makes both implementation and porting cumbersome. It also imposes difficulties in protocol redesign when the application requirements change since the entire radio stack needs to be modified.

Sensor network applications are generally characterized by long idle durations and intermittent communication patterns. The traffic loads are typically so low that overall the idle duration energy consumption dominates. Low duty cycle MAC protocols are used to reduce the idle duration energy consumption. However, lowering down the duty cycle in favour of energy consumption results in increased latency, which makes it undesirable for many applications. In this paper, we propose radio triggered wake-up with addressing capabilities (RTWAC) that allows suppressing the idle duration current consumption. Our solution consists of an external low-cost hardware wakeup circuit attached to the microcontroller of a sensor node. The sensor node stays in the sleep mode with its normal communication radio turned off. In order to communicate with a sensor node, a special kind of out-of-band modulated wakeup signal is transmitted. The modulated signal contains data that enables to distinguish between differently addressed nodes in order to avoid undesired node wake-ups. Furthermore, we augment this solution to a MAC protocol running on the normal radio on the sensor node in an advantageous way to achieve high energy gains and low latency for data communication.

Currently there is no widely accepted formalized description or metadata that represents networks, their components and interrelations between them. There is also no de facto classification of network parameters, models and services. The network community lacks a metadata specification similar to WSDL that represents networks in clear and unified manner and includes software, hardware and networking parts of the system description. This limits the advance of the frameworks aiming to assist the development of complex non-established network systems, such as wireless sensor, cognitive and heterogeneous networks. Additionally a standard metadata would enhance the interoperability and acceptance of various middleware, service discovery schemes and cross-layer optimization solutions. In this paper we suggest a simple, but comprehensive extensible metadata specification and a corresponding metamodel that allows to describe a wide range of network components and network configurations. We describe metadata and metamodel on the example of wireless sensor networks. In this field the need for standard metadata is particularly pressing due to the high number of available protocol solutions and lack of standardization.

We present a system-level approach to localizing and tracking users on a basis of different sources of location information. We have applied a combination of the Cricket system and inertial navigation sensors to improve the coverage and accuracy of our framework when used indoors. The system can be applied outdoors as well using, for example, GPS as the source of location data. The overall system architecture is modular and extendible, allowing for creation of location and context aware services and inclusion of additional sources of localization data. Extensive performance evaluation presented shows that the system is both accurate as well as scalable.

This paper presents new approaches for dynamically integrating sensors into a surrounding computing infrastructure. Our work is based on small programs - called Senslets - that are stored on sensor nodes. Senslets are written using a programming model based on a high-level programming language such as C# or Java, but they do not assume a virtual execution environment on the sensors. Instead, they are downloaded to a mobile device or stationary computer, where they are hosted and executed. In this paper, we present (1) a programming framework for developing Senslets, (2) the tools necessary for deploying Senslets on resource-constrained sensor nodes, and (3) a hosting environment for executing Senslets on mobile phones. The paper also contains an evaluation and a description of example applications.

We describe the design, implementation and performance evaluation of a wireless sensor network based localization and tracking system, which can provide localization services in many of the pervasive computing applications. Our system uses non-linear Bayesian filtering to obtain accurate tracking results from noisy localization data. This allows high-accuracy tracking of non-linear motion even in the presence of non- Gaussian measurement noise, which is a significant improvement in generality compared to many state-of-the-art sensor network localization systems. Our prototype uses a combination of radio and ultrasound signals to obtain distance estimates necessary for the filtering process, although in principle any distance estimation technique can be used. We also describe improved outlier detection and post-calibration methods for enhancing the quality of the distance estimates obtained compared to earlier systems.

In this demonstration paper, we present a multi-radio MAC protocol and a prototype sensor node platform which supports dual frequency bands of operation. The multi-radio MAC protocol combines the advantages of both high and low frequency bands to give an energy efficient performance with high throughput and low latency in several applications. Our prototype supports spectrum agility, which is becoming important due to ever crowding spectrum. Besides demonstrating the improved performance metrics and spectrum agility support, we will also present the flexibility provided by our MAC protocol.

This paper describes the design, implementation and performance evaluation of a wireless sensor network based scalable outdoor vehicular tracking system. The system is highly flexible and configurable both from software and hardware architecture point of views and enables it to adapt to a wide range of vehicle tracking applications. We also present some intermediate results and the rationale behind our design approach. The system was tested for a network of 100 nodes and is scalable to a few thousand node setup. We believe that the vehicle localization and tracking results from our large scale deployment of sensor nodes and system design experience are useful to the community

This paper describes the implementation architecture and performance analysis of nanoMAC, a CSMA/CA based medium access control protocol, which is specifically designed for high density wireless sensor networks. We empirically show that nanoMAC performs with high reliability in a variety of network traffic conditions in single and multihop scenarios. For energy efficient operation and minimizing idle-overhearing, nanoMAC uses a specialized sleep algorithmWe also show results from a comparative study of nanoMAC with B-MAC in terms of performance measures.

In this demonstration paper we show and describe a flexible hardware and software platform for tracking applications. The architecture presented is extendible both on hardware and software sides, allowing for easy inclusion of sensors and signal processing algorithms of different types. During the demonstrations, examples of the software and hardware blocks developed within this generic architecture will be shown, and insight to the design choices and development issues will be given. Both outdoor and table-top versions of the possible demonstrations will be described.