Dynamic traffic patterns and shifts in traffic distribution in Open Radio Access Networks (O-RAN) pose a significant challenge for real-time network optimization in 5G and beyond. Traditional traffic analytics methods struggle to remain accurate under such non-stationary conditions, where models trained on historical data quickly degrade as traffic evolves. This paper introduces AIDITA, an AI-driven Digital Twin for Traffic Analytics framework designed to solve this problem through autonomous model adaptation. AIDITA creates a digital replica of the live analytics models running in the RAN Intelligent Controller (RIC) and continuously updates them within the digital twin using incremental learning. These updates use real-time Key Performance Metrics (KPMs) from the live network, augmented with synthetic data from a Generative AI (GenAI) component to simulate diverse network scenarios. Combining GenAI-driven augmentation with incremental learning enables traffic analytics models, such as prediction or anomaly detection, to adapt continuously without the need for full retraining, preserving accuracy and efficiency in dynamic environments. Implemented and validated on a real-world 5G testbed, our AIDITA framework demonstrates significant improvements in traffic prediction and anomaly detection use cases under distribution shifts, showcasing its practical effectiveness and adaptability for real-time network optimization in O-RAN deployments.

Autonomous Network enablers for a 5G Network-on-Wheels are investigated, with a field-trial for a Communication Service Provider. The objective was to devise solutions to reduce time spent on network life cycle tasks, such as network function validation, system commission and service deployment. The field trial revealed significant data collection and analysis challenges even with a single cell campaign, this suggests severe costs with public-network scales. The work contributes a new architecture for experiments and optimisation of observability strategies with algorithms in 5G networks. This work helps operators more effectively denlov 5G networks and services.

Multi-Access Point Collaboration (MAPC) envisioned in future Wi-Fi standards has the potential to provide reliable connectivity for time-critical IoT applications. The joint transmission (JT) concept strengthens the signals at the station transmitted from distributed APs, increasing its resilience against interference and multi-path fading to improve reliability and latency performance. There is no commercially available WiFi device capable of doing this since individual APs must be synchronized for time, RF carrier and packet data, and are required to share the medium access with each other. We present an experimental study of distributed dual-AP Wi-Fi network prototype with SDR platforms with openwifi. By synchronizing the clock source, packet transmission control and data, we demonstrate a successful constructive overlap of transmitted WiFi signals at the receiver from distributed APs. Specifically, we observe a 6 dB received signal power gain and a 4.4 dB SNR improvement from the decoded packets with two APs compared to a standalone transmission in the experiment.

Time-Sensitive Networking (TSN) ensures reliable traffic delivery in industrial automation, multimedia, and automotive systems. While effective in wired networks, wireless TSN (WTSN) faces challenges like delays and interference, complicating traffic scheduling. This paper presents a data-driven approach to improve WTSN management by addressing the residual service time (RST) problem, which increases link latency. Tested in a Wi-Fi TSN-based environment, the proposed WTSN digital twin framework preserves TSN traffic guarantees while significantly reducing RST and hence link latency.

This paper investigates a dual-polarized intelligent reflecting surface (DP-IRS)-assisted multiuser multiple-input multiple-output (MIMO) wireless network with the possibility of multi-stream transmission per user. We aim to determine the number of data streams per user while simultaneously ensuring that each user achieves its specified target spectral efficiency performance with the minimum transmit power. To achieve this, we optimize the number of data streams, power allocations, transmit/receive digital filters, DP-IRS operations, and transmit/receive DP antennas phase shifters. Based on this generalized network setup, we formulate an optimization framework involving multiple coupled optimization variables. To tackle this complex optimization problem, we first derive low-complexity convex formulations for each variable. Subsequently, we propose a novel multi-step alternating optimization algorithm that effectively solves multiple subproblems sequentially and converges to a feasible solution. Motivated by further complexity reduction, we present a low-complexity suboptimal version of the main algorithm. Extensive numerical simulations demonstrate that, compared to a simple IRS, the DP-IRS achieves a 42.4% reduction in transmit power for a configuration with 50 reflecting elements and eight users. Additionally, the proposed low-complexity Algorithm 2 incurs a 62% decrease in computational complexity compared to Algorithm 1 while maintaining satisfactory performance.

Time-Sensitive Networking (TSN) plays a crucial role in ensuring determinism and low latency, vital for the demands of industrial applications. Integrating the benefits of wire-less networks, including mobility, presents a significant challenge in such environments. In this study, we propose a novel solution to address this challenge by introducing handover capabilities into wireless Time-Sensitive Networking (W-TSN). Through real-world development and testing, we present an optimized approach for minimizing handover delay and leveraging machine learning to select the optimal handover time and space moment in a two-dimensional environment, with low effect on time-sensitive traffic. Our findings demonstrate that our mechanism reduces handover delay below 10 milliseconds and optimizes the handover moment selection, leading to improvements in critical network parameters such as bandwidth and jitter.

Recent technologies of Wi-Fi are being widely in-corporated in smart factories with an expectation of real-time, flexible, reliable, and quality services. The current Wi-Fi offers a range of physical data rates based on channel quality but is limited to certain applications. With the traditional application and transport layer protocols being designed for wired networks, using them in bottleneck situations of industrial wireless networks poses certain drawbacks and one such drawback is the through-put degradation due to airtime unfairness. Using innovations like in-band network telemetry, application-network interaction, and the programmability of the kernel and intermediate devices, a reactive airtime feedback-based congestion control algorithm, RACC, for wireless networks is introduced in this paper. The designed algorithm reactively adapts the application data transfer rate based on the feedback from the access point and was implemented on commercial off-the-shelf devices. Using this algorithm, the throughput was improved 72% and the airtime unfairness was reduced to as low as 15% as compared to the CUBIC. The designed congestion control algorithm addresses the issue of airtime unfairness and throughput degradation in industrial wireless networks based on real-time network state.

Addressing long-range dependencies in blind co-channel interference waveforms typically requires convolutional networks with large kernels or significant depth, which are resource-intensive. This paper presents a streamlined UNet architecture integrated with fast Fourier convolution blocks and a long short-term memory in the bottleneck, designed to efficiently capture these dependencies. By leveraging the Fourier domain for global feature processing, our architecture reduces the model's complexity without compromising performance. Compared to the leading benchmark model (a deep UNet), our approach yields a 26.5% improvement in mean square error, while reducing multiply-accumulate operations and the number of model parameters by 76.8% and 76.3% respectively, demonstrating a significant enhancement in both accuracy and efficiency for interference cancellation in constrained computational environments.

With ever-increasing throughput-hungry applications running over WiFi, such as Virtual and eXtended Reality (VR/XR), on the one hand and the need for deterministic communication on the other, network densification is not an option. With dense network deployment interference between overlapping basic service set (OBSS) become the main source of system throughput drop and packet delays, decreasing the benefits of dense network. With the latest WiFi 7 standard being standardized, access point (AP) coordination is one of the key features foreseen to be added. With increased interactions between APs from different OBSS, spatial reuse feature can benefit in determining accurately the levels of interference and modulation and coding scheme (MCS) index to be used for concurrent transmissions. In this paper we show a centralized Coordinated Spatial Reuse (C-SR) algorithm implemented in the network controller that determines the transmit powers of the concurrent AP transmitters based on calculated interference levels in the main receiver. In addition, the algorithm determines the MCS index for each concurrent transmission. In a test-bed measurement setup, we show that the overall system goodput is increased by 20% and 33%, respectively, for the network topology where receivers are positioned in the inner zone between APs. In addition, the communication latency is maintained below certain threshold, compared to cases where C-SR is not activated.

As network management operations increasingly rely on automation and finer control actions, there is a need for precise telemetry systems. In-band Network Telemetry (INT) methods use data packets to carry telemetry and give real-time insights about network performance. Existing solutions often require specialized hardware or offer limited runtime configuration options. This work presents an INT Framework for heterogeneous private networks, targeting industrial and multimedia applications. The framework is designed to be flexible and runtime-reconfigurable, addressing challenges in real-world applications. We provide implementation details of our elements supporting the configurability and the consolidation of raw telemetry into high-level Quality of Service (QoS) metrics. We evaluated the framework in a testbed with wired and wireless devices. The results show the accuracy in monitoring QoS, as well as an analysis of synchronization requirements, showcasing the feasibility of our framework for solutions requiring precise and flexible QoS monitoring.

As industries increasingly rely on advanced networking solutions, Time-Sensitive Networking (TSN) has emerged as an essential tool, ensuring smooth and reliable communication in mission-critical applications. However, while TSN does a lot for industrial systems, there is still a whole world of not-utilized potential in wireless communication. To extend wired TSN with wireless capabilities, imec’s openwifi platform has been extended with TSN features. To speed up the implementation of new Wi-Fi features in the openwifi platform, as well as to test their feasibility in larger-scale network scenarios we implemented the key TSN features of openwifi in the ns-3 simulator. In this paper, we evaluate how the selection of transmission opportunity (TXOP) duration affects network performance in shared time slots, as well as the impact of different shifts between shared time slots. The ns-3 implementation is validated against openwifi as well.

Time-sensitive networking (TSN) is proposed to support deterministic communication for industrial automation use cases. To harvest the wireless communication flexibility, TSN features have been extended to the wireless domain as well. One of the key TSN features is the ability to assign transmission schedules to different traffic flows in the network with the aim of reducing time slot access delay on each network node. In the wireless domain, this becomes even more challenging due to the shared medium, lower reliability, and slower transmission rates compared to wired systems, reducing the available time resources. In this paper we look at utilizing genetic algorithms to support scheduling of traffic flows from different wireless end devices in a shared schedule. Two optimization functions are defined. The first optimization is based on minimizing the overall shared air time between different end nodes, while the second optimization is based on maximizing time slots that can be used without any interference. Both optimizations aim to reduce the collision probability. With these initial results, we identify the best parameters for genetic algorithms and examine the initial population's impact on overall performance. We show that a fully randomized initial population does not achieve the highest fitness value, even after several generations.

Real-time applications are employed in today's pri-vate professional networks to support process handling and improve the efficiency of production. For supporting such applications, communication networks need to support deterministic communication with bounded low latency and high reliability. Time-sensitive networking (TSN) is used for such purposes, recently extended to wireless networks as well. To further improve the network catering to such real-time applications, it is crucial for end devices to expose their requirements to the network. On top of that, new wireless features like OFDMA, implemented in IEEE 802.11ax (Wi-Fi 6), can improve wireless time-sensitive networks (W-TSNs) by improving communication efficiency. This paper looks at reducing the overhead of OFDMA and integrating UL-OFDMA with wireless TSN to support time-sensitive flows. We show that when both features are integrated, it reduces the latency by ~ 16 times compared to Wi-Fi with UL-OFDMA scenario while giving 50 % better air time utilization compared to the wireless TSN scenario.

This paper proposes a fully unsupervised technology recognition method using deep clustering for identifying wireless technologies to learn from raw data without requiring manual label annotations. Identifying and recognizing wireless technologies is important to realize effective spectrum management. Recent scientific publications utilized supervised deep learning with great success to train AI models to recognize different wireless technologies based on labeled RF signal datasets. However, assigning labels to wireless technology signal datasets for supervised deep learning is time consuming and may not always be practical. To remedy this issue, the proposed method combines an autoencoder and clustering layers, extended with a Gaussian Mixture Model, to learn low-dimensional salient features from raw IQ data and cluster them into distinct wireless technologies. The optimal input dimensions and performance of the method in different signal-to-noise ratio conditions are analyzed for a set of several different low-power wide area network (LPWAN) technologies: Sigfox, LoRa, IEEE 802.11ah, and IEEE 802.15.4g. Extensive simulations show that the proposed method for wireless technology recognition exhibits a recognition accuracy exceeding 90%, surpassing the performance of the state-of-the-art deep clustering algorithms by 4 to 5% in terms of accuracy.

Dynamic Spectrum Sharing (DSS) is an enabler for a seamless transition from 4G Long Term Evolution (LTE) to 5G New Radio (NR) by utilizing existing LTE bands without static spectrum re-farming. In this paper, we propose a cross-band DSS scheme that utilizes the Multimedia Broadcast Multicast Service over a Single Frequency Network (MBSFN) feature of an LTE network and the Multicast Broadcast Service (MBS) feature of an NR network. The proposed DSS scheme utilizes LTE and NR resource controllers to assign muted MBSFN subframes on the LTE band and muted MBS subframes on the NR band based on traffic needs. In contrast to the state-of-the-art, the proposed DSS scheme does not require a coordination signaling channel between the LTE and NR networks. Instead, a machine learning-based Technology Recognition and Traffic Characterization (TRTC) system is used to identify and characterize traffic patterns. The LTE and NR resource controllers use the TRTC to sense the muted subframes and offload traffic accordingly. On average, the proposed DSS, as compared to static band configuration, improves the LTE throughput, NR throughput, LTE band spectrum utilization efficiency, and NR band spectrum utilization efficiency by 13.5%, 8.3%, 11.8%, and 20.7%, respectively.

The need for supporting multimedia streaming services in cellular networks as standardized by 3GPP is expanding rapidly. Evolved Multimedia Broadcast Multicast Service (eM-BMS) was initially introduced in Release 9 and following releases have introduced several enhancements. Multimedia Broadcast Multicast Single Frequency Network (MBSFN) is one of the eMBMS enhancements targeting to reduce interference, however, its static parameter configuration yields inefficient resource allocation. Therefore, in this paper, an adaptive demand-driven MBSFN resource allocation algorithm is proposed aiming to efficiently utilize the radio resources. The algorithm flexibly assigns resources to multicast transmissions by varying MBSFN configuration parameters (the number and period of multicast subframes) and provides freed resources to unicast traffic. The proposed algorithm is implemented and evaluated using a Software Defined Radio platform which we made open source. As compared to the fixed MBSFN parameter configuration, our solution showcases an improvement of at least 24% and maximally by 40% in terms of multicast resource efficiency. Also, the total system throughput (multicast and unicast) improves by at least 4% and maximally by 24%.

Field-Programmable Gate Array (FPGA)-based Software-Defined Radio (SDR) is well-suited for experimenting with advanced wireless communication systems, as it allows to alter the architecture promptly while obtaining high performance. However, programming the FPGA using a Hardware Description Language (HDL) is a time-consuming task for FPGA developers and difficult for software developers, which limits the potential of SDR. High-Level Synthesis (HLS) tools aid the designers by allowing them to program on a higher layer of abstraction. However, if not carefully designed, it may lead to a degradation in computing performance or significant increase in resource utilization. This work shows that it is feasible to design modern Orthogonal Frequency Division Multiplex (OFDM) baseband processing modules like channel estimation and equalization using HLS without sacrificing performance and to integrate them in an HDL design to form a fully-operational FPGA-based Wi-Fi (IEEE 802.11a/g/n) transceiver. Starting from no HLS experience, a design with limited overhead in terms of latency and resource utilization as compared to the HDL approach was created in less than one month. The FPGA design generated by HLS achieved the same performance as compared to its HDL counterpart when deployed on a System-on-Chip (SoC)-based SDR, as verified by a professional wireless connectivity tester.

End-to-end low-latency deterministic communication, next to high-reliability communication, is one of the key features that communication systems are expected to provide for industrial systems. To achieve time-sensitive networking (TSN), a set of standards have already been designed and deployed for wired industrial communication systems, coexisting or replacing other long-living technologies such as Fieldbus, Profibus, or Modbus. Wireless time-sensitive networking (W-TSN) is getting traction with the development of the newest WiFi generation (IEEE 802.11be) as well as advances in cellular networking. One of the challenges in W-TSN is scheduling and isolation of time-critical traffic in the shared wireless medium. In this paper we present a solution, called dynamic traffic classification, to give faster dedicated access to the wireless medium for packets of highly-time-sensitive flows, that can be generated randomly. Dynamic traffic classification utilizes so-called shadow queues implemented in FPGA-based WiFi baseband SDR platform, openwifi, to prioritize channel access of certain packets over others. We show that the channel access latency in the case of dynamic traffic classification does not depend on the scheduling cycle, but on the distribution of dedicated time slots inside the schedule cycle. As such we achieve to decrease the end-to-end latency by 75% in case of longer communication cycles with wider space between communication time slots.

The emergence of Time-Sensitive Networking (TSN) has enabled network determinism to a new level, offering high reliability and bounded latency for critical communications. However, the unpredictable nature of traffic generation also poses new challenges to TSN. While TSN is designed to maintain backward compatibility with the 802.1 standards, many end nodes may not be equipped to understand TSN. This can result in a less deterministic TSN, and suboptimal resource utilization, mainly driven by Residual Service Time (RST). To address these challenges, this study proposes three scheduling mechanisms to reduce RST: q-learning, active time slot update, and polynomial forecasting. Real-world data captured from our wireless-TSN (W-TSN) evaluation kit is used to compare the proposed approaches in terms of one-way latency. The results show that the machine learning approach outperforms the other methods in terms of overall latency. However, it is less effective in identifying the optimal time slot position compared to the other methods.

Investigating the security of Wi-Fi devices often requires writing scripts that send unexpected or malformed frames, to subsequently monitor how the devices respond. Such tests generally use Linux and off-the-self Wi-Fi dongles. Typically, the dongle is put into monitor mode to get access to the raw content of received Wi-Fi frames and to inject, i.e., transmit, customized frames. In this paper, we demonstrate that monitor mode on Linux may, unbeknownst to the user, mistakenly inject Wi-Fi frames or even drop selected frames instead of sending them. We discuss cases where this causes security testing tools to misbehave, making users to believe that a device under test is secure while in reality it is vulnerable to an attack. To remedy this problem, we create a script to test raw frame injection, and we extend the Radiotap standard to gain more control over frame injection. Our extension is now part of the Radiotap standard and has been implemented in Linux. We tested it using commercial Wi-Fi dongles and using openwifi, which is an open implementation of Wi-Fi on top of software-defined radios. With our improved setup, we reproduced tests for the KRACK and FragAttack vulnerabilities, and discovered previously unknown vulnerabilities in three smartphones.

Deterministic performance and reliable operation are vital for many applications with industrial-grade requirements. Such applications rely on Time-Sensitive Networking (TSN) to enable time-critical deterministic communication. While standardization efforts were focused mainly on TSN features for wired domains, recent advances in wireless technologies (e.g., Wi-Fi 6/7) are extending time-sensitive communication towards wireless networks as well. However, achieving multi-domain LAN/ Wireless LAN (WLAN) end-to-end TSN communication requires addressing challenges on end-to-end time synchronization, multi-domain control plane interoperability, run-time end-to-end scheduling, and fine-grained monitoring. Because state-of-the-art TSN controllers’ scope lays far below these new required capabilities, in this work we present a novel, fully-programmable controller for end-to-end TSN-enabled networks. Our controller is based on a modular architecture to be adaptable to challenges arising when shifting the standard TSN scope towards WLAN domain. We deploy a proof-of-concept in a cloud-wired environment to evaluate its key performance indicators when handling increasing numbers of nodes and simultaneous requests. Further, we run experiments on real TSN-enabled networks comprising Ethernet and Wi-Fi technologies, demonstrating the effectiveness of the controller in performing seamless fine-grained traffic control in both domains.

One of the aims of the H2020 5G Blueprint project is to enable seamless cross border teleoperation use cases with 5G technology. The explored use cases are automated barge control, automated drive-in-loop docking, cooperative adaptive cruise control based platooning, and remote take-over operations. In this paper, we present an analysis of the network requirements of such use cases, and we present an end-to-end 5G architecture (with a focus on network slicing and seamless cross-border roaming) for the trial network based on lasted standardization work and implementation tools, from user equipment, radio, transport, core network to exposed network APIs. This work will be used as guideline for further network deployment and feature implementation in test labs and project pilot area within the project.

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 widely used in industrial environments to support low-latency deterministic communications. Innovation to bring time-sensitive networking to wireless networks is getting traction. Besides enabling real-time and deterministic communications, Wireless Time-Sensitive Networks (W- TSN) should provide flexibility and easy deploy-ment, key characteristic requirements for industrial networks. Nevertheless, current research in this field focuses on adapting wired TSN features to the wireless world, namely accurate time synchronization and traffic scheduling, essential processes for wireless end devices such as automated and impact-less association procedure are not considered until now. This work proposes a W - TSN impactless association procedure that provides time synchronization and traffic scheduling for prospect W - TSN clients during the association phase by utilization of beacons. As such, prospect clients can perform association procedure in a controlled fashion avoiding collisions with other, already-associated, W - TSN clients. The presented procedure is designed, implemented, and tested in a real-world scenario on top of a wireless Software Defined Radio (SDR) platform with the IEEE802.11 standard. The results show high accuracy synchro-nization on client frame transmissions even with challenging scheduling timeslots of 128 μs.

Software Defined Radio (SDR) platforms are valuable for research and development activities or high-end systems that demand real-time adaptable wireless protocols. While low latency can be achieved using the dedicated digital processing unit of a state-of-the-art SDR platform, its Radio Frequency (RF) front-end often poses a limitation in terms of turnaround time (TT), the time needed for switching from the receiving to the transmitting mode (or vice versa). Zero Intermediate Frequency (ZIF) transceivers are favorable for SDR, but suffer from self-interference even if the device is not currently transmitting. The strict MAC-layer requirements of Time Division Duplex (TDD) protocols like Wi-Fi cannot be achieved using configurable ZIF transceivers without having to compromise receiver sensitivity. Using a novel approach, we show that the TT using the AD9361 RF front-end can be as low as 640 ns, while the self-interference is at the same level as achieved by the conventional TDD mode, which has a TT of at least 55 μs. As compared to Frequency Division Duplex (FDD) mode, a decrease of receiver noise floor by about 13 dB in the 2.4 GHz band and by about 4.5 dB in the 5 GHz band is achieved.

Precision time protocol (PTP), a state-of-the-art clock synchronization protocol primarily designed for wired networks, has recently gained attention in the wireless community, due to the increased use of the IEEE 802.11 wireless local area networks (WLAN) in real-time distributed systems. However, all the existing WLAN-based PTP designs either incorporate software timestamping (TS) delivering poor clock synchronization accuracy, or hardware (HW) TS providing better synchronization accuracy at the cost of a significant amount of HW overhead. Moreover, the performance of the existing PTP solutions is mostly evaluated in single-hop wireless networks, while the performance across wired and wireless networks is taken for granted. In this article, a new software-defined-radio-based approach to implement PTP is introduced and validated for the IEEE 802.11 WLAN. Instead of using a dedicated HW clock, the solution utilizes the timing synchronization function clock, an existing clock in the IEEE802.11 standard for synchronization between access point and WLAN stations. The performance of the proposed solution is first investigated within a single-hop WLAN and then across wired–wireless networks. Experimental results unveil that 90% of the absolute clock synchronization error falls within 1.4$\mu \mathrm{s}$.

In the coming years, connectivity between vehicles with autonomous driving features and roadside infrastructure will become more and more a reality on our roads, pursuing to improve road safety and traffic efficiency. In this regard, two main communication standards are considered as key enablers, that is ITS-G5 (based on IEEE 802.11p) and C-V2X (3GPP). To assess the real performance of these technologies, there is still need for an objective and independent one-to-one comparison of these technologies using off-the-shelf hardware under identical and real-life traffic conditions. Until today, performance evaluations are limited to simulations, emulations or individual technology assessments in real-life circumstances. In this paper, an exhaustive and fair evaluation of the technologies has been conducted in a real-life highway environment under identical conditions. Tailored evaluation tools in combination with our in-house CAMINO vehicular framework has been utilized to perform the tests and analyze the results for different well-specified test cases. The performance evaluation shows that for the short-range technologies, C-V2X PC5 has, in general, a higher range than ITS-G5, while ITS-G5 offers lower latency than C-V2X PC5 in low-density scenarios. Long-range 4G C-V2X can be considered as an alternative for certain use cases. The outcome of this experimentation study can be used as valuable information for the further development of future (5G) connected and autonomous driving.

5G systems promise to enable autonomous vehicles by empowering road-, water-, and air-vehicles with ultra low latency communications and computing at edge in order to share and process data from multiple sensors. However, in order to realize such fully Connected and Automated Mobility (CAM) for cars, drones and vessels, a crucial intermediary step must be fully achieved: 5G-based tele-operated transport. In order to do so, the European project H2020 5G-Blueprint aims to design, test, and validate in real deployments a 5G-enabled tele-operated transport and its enabling functions in both a relevant and operational environment realised through cross-border trials on the road and on the water along 5G corridors in the Dutch and Belgian border area, resulting in a blueprint for future cooperation on 5G-enabled CAM between public, private and semi-private parties (e.g, ports), gaining new and innovative insights on the stringent particular requirements for safe CAM, on the architecture, on governance and relevant business models.

Many applications use Transmission Control Protocol (TCP) to achieve end-to-end reliable, ordered, and error-free data transfer in the network. The decisions are entirely based on the partial end-to-end information obtained from the acknowledgment packets. With several applications moving towards the wireless domain or wired-wireless domain, there has been advancements in the field of application-network interaction and innovations to obtain real-time network monitoring information on a per-hop basis. This paves a way for extensibility and customization of transport protocols. In this paper, we use detailed real-time in-band network telemetry information to adjust the data transfer at the sender side by modifying the congestion control algorithms in real time. This new technique is tested for different network scenarios and the obtained results indicate that a more network-aware TCP design can greatly increase performance under lossy conditions. The implemented technique illustrates how tighter interactions between higherlayer protocols and the network, in combination with real-time telemetry, can facilitate the way for novel, more adaptive protocol designs.

In-band network telemetry (INT) monitoring is getting traction in the recent years for its ability to offer high-granularity network information on per-hop, per-flow and end-to-end basis. Such detailed network monitoring helps in better network management and accurate network (re)configuration, supporting automated network management and control. However, until now the collected INT information is used as is, without any classification based on its provided information value. In this paper we derive the Age of Information (AoI) mathematical model to calculate the INT hop-time average AoI and the impact of reporting on the INT AoI. Such metric can be used to reduce the network overhead in term of INT reporting by not sending old AoI INT and determining the information accuracy. We also show that the INT hop-time average AoI for a layer three INT implementation for a wireless network depends heavily on the communication latency between each hop and end hop, and that it is bounded by the end-to-end communication latency averaged over the number of hops.

CSI (Channel State Information) of WiFi systems contains the environment channel response between the transmitter and the receiver, so the people/objects and their movement in between can be sensed. To get CSI, the receiver performs channel estimation based on the pre-known training field of the transmitted WiFi signal. CSI related technology is useful in many cases, but it also brings concerns on privacy and security. In this paper, we open sourced a CSI fuzzer to enhance the privacy and security of WiFi CSI applications. It is built and embedded into the transmitter of openwifi, which is an open source full-stack WiFi chip design, to prevent unauthorized sensing without sacrificing the WiFi link performance. The CSI fuzzer imposes an artificial channel response to the signal before it is transmitted, so the CSI seen by the receiver will indicate the actual channel response combined with the artificial response. Only the authorized receiver, that knows the artificial response, can calculate the actual channel response and perform the CSI sensing. Another potential application of the CSI fuzzer is covert channels based on a set of pre-defined artificial response patterns. Our work resolves the pain point of implementing the anti-sensing idea based on the commercial off-the-shelf WiFi devices.

In this study, an energy-efficient self-organized framework for sub-channel allocation and power allocation is presented for ultra-dense small cell networks, which can operate in both licensed and unlicensed bands. In order to protect legacy WiFi devices (operating in unlicensed bands), we consider the Long-Term Evolution (LTE) operation in unlicensed bands based on Carrier Sense Adaptive Transmission (CSAT), in which 'ON' and 'OFF' duty cycle approach is utilized. On the other hand, there are severe interference management problems among small cells (operating in licensed and unlicensed bands) and between macro cells and small cells (operating in licensed bands) due to co-channel and ultra-dense deployment of small cells. This article proposes a self-organized optimization framework for the allocation of sub-channels and power levels by exploiting a non-cooperative game with the objective to maximize the energy efficiency of dual-access small cells without creating harmful impact on coexisting network entities including macro cell users, small cell users, and legacy WiFi devices. Simulation results show that the proposed scheme outperforms (6 and 11 percent) and (8 and 18 percent) the round-robin and the spectrum-efficient schemes, respectively, for two different small cell scenarios. In addition, it is shown that for less channel state information (CSI) estimation errors ς = 0.02, the maximum performance degradation of the proposed scheme is reasonably small (5.5 percent) as compared to the perfect CSI.

Most industrial applications demand determinism in terms of latency, reliability, and throughput. This goes hand in hand with the increased complexity of real-time network programability possibilities. To ensure network performance low-overhead, high-granularity, and timely network verification techniques need to be deployed. The first cornerstone of network verification ability is to enable end-to-end network monitoring, including end devices too. To achieve this, this article shows a novel and low overhead in-band network telemetry and monitoring technique for wireless networks focusing on IEEE 802.11 networks. A design of in-band network telemetry enabled node architecture is proposed and its proof of concept implementation is realized. The PoC realization is used to monitor a real-life SDN-based wireless network, enabling on-the-fly (re)configuration capabilities based on monitoring data. In addition, the proposed monitoring technique is validated in terms of monitoring accuracy, monitoring overhead, and network (re)configuration accuracy. It is shown that the proposed in-band monitoring technique has 6 times lower overhead than other active monitoring techniques on a single-hop link. Besides this, it is demonstrated that (re)configuration decisions taken based on monitored data fulfill targeted application requirements, validating the suitability of the proposed monitoring technique.

Recently, the operation of LTE in unlicensed bands has been proposed to cope with the ever-increasing mobile traffic demand. However, the deployment of LTE in such bands implies sharing spectrum with mature technologies such as Wi-Fi. Several studies have discussed this coexistence problem by suggesting that LTE implements different adaptation mechanisms that allow transmission possibilities to Wi-Fi. While such adaptation mechanisms exist, they still negatively impact Wi-Fi performance, mainly due to the lack of collaboration/coordination mechanisms that inform about the co-located networks' activities. In this paper, we propose a distributed spectrum management framework that enhances the performance of Wi-Fi, as a particular case, by detecting harmful co-located wireless networks and changes the Wi-Fi's operating central frequency to avoid them. The framework is based on a Convolutional Neural Network (CNN) that can identify different wireless technologies and provides spectrum usage statistics. Experiments were carried out in a real-life testbed, and the results show that Wi-Fi maintains its performance when using our framework. This translates in an increase of at least 40% on the overall throughput compared to a non-managed operation of Wi-Fi.

The fifth generation of mobile networks (5G) and the Software- Defined Radio Access Networks (SD- RAN) architecture envision to support lower latency, enhanced reliability, massive connectivity, and improved energy efficiency. In this context, low latency is considered crucial and Ultra-Reliable Low Latency Communication (URLLC) as one of the key enablers. Currently, IEEE 802.11 networks cannot be programmed fine-grained enough nor manage multiple networks at runtime. Besides, in such scenarios, the coarse-grained level of monitoring information has been hindering troubleshooting and management. In this paper, we present an SDN-based framework where fine-grained End-to-End (E2E) network statistics can be gathered using Inband Network Telemetry (INT) and used for network control and management. With such fine-grained network information, we show how our system can enhance the Quality of Service (QoS) delivery through slice orchestration in IEEE 802.11 Radio Access Networks (RANs).

Low power wide area networks support the success of long range Internet of things applications such as agriculture, security, smart cities and homes. This enormous popularity, however, breeds new challenging problems as the wireless spectrum gets saturated which increases the probability of collisions and performance degradation. To this end, smart spectrum decisions are needed and will be supported by wireless technology recognition to allow the networks to dynamically adapt to the ever changing environment where fair co-existence with other wireless technologies becomes essential. In contrast to existing research that assesses technology recognition using machine learning on powerful graphics processing units, this work aims to propose a deep learning solution using convolutional neural networks, cheap software defined radios and efficient embedded platforms such as NVIDIA's Jetson Nano. More specifically, this paper presents low complexity near-real time multi-band sub-GHz technology recognition and supports a wide variety of technologies using multiple settings. Results show accuracies around 99%, which are comparable with state of the art solutions, while the classification time on a NVIDIA Jetson Nano remains small and offers real-time execution. These results will enable smart spectrum management without the need of expensive and high power consuming hardware.

Collision detection (CD) is a key capability of carrier sense multiple access (CSMA) based medium access control (MAC) protocol. Applying CD, the transmitter can abort transmission immediately so that the power can be saved. This technique does not need the peer receiver to give feedback on whether there is a packet collision, and hence, the overall overhead is significantly low. The challenge, however, is to operate in transmit time and instantly detect the week colliding signal in the presence of strong self-interference (SI). This paper investigates two CD methods. The first technique trains a convolutional neural network (CNN) model which operates on raw baseband samples, without the need for pre-decoding. The second method treats the SI as a normal signal and estimates the signal to noise ratio (SNR): low SNR implies there is a collision because the pure SI is expected to have high SNR. Both models are evaluated by IEEE 802.15.4-like measured and simulated signals. The results show that collisions up to 30 dB below the SI signal can be detected precisely within 20 μs, while the proposed models can deliver acceptably low false alarm rate <; 1.5 %.

This paper introduces a Non-Orthogonal Multiple Access (NOMA) scheme to support concurrent transmission of multiple IEEE 802.15.4 packets. Unlike collision avoidance Multiple Access Control (MAC), concurrent transmission supports Concurrent-MAC (C-MAC) where packet collision is allowed. The communication latency can be reduced by C-MAC because a user can transmit immediately without waiting for the completion of other users' transmission. The big challenge of concurrent transmission is that error free demodulation of multiple collided packets hardly can be achieved due to severe Multiple Access Interference (MAI). To improve the demodulation performance with MAI presented, we introduce an architecture with multiple switching antennas sharing a single analog transceiver to capture spatial character of different users. Successive Interference Cancellation (SIC) algorithm is designed to separate collided packets by utilizing the spatial character. Simulation shows that at least five users can transmit concurrently to the SIC receiver equipped with eight antennas without sacrificing Packet Error Rate.

Open source Software Defined Radio (SDR) project, such as srsLTE and Open Air Interface (OAI), has been widely used for 4G/5G research. However the SDR implementation of the IEEE802.11 (Wi-Fi) is still difficult. The Wi-Fi Short InterFrame Space (SIFS) requires acknowledgement (ACK) packet being sent out in 10μs/16μs (2.4GHz/5GHz) after receiving a packet successfully, thus the Personal Computer (PC) based SDR architecture hardly can be used due to the latency (≥ 100μs) between PC and Radio Frequency (RF) front-end. Researchers have to do simulation, hack a commercial chip or buy an expensive reference design to test their ideas. To change this situation, we have developed an open-source full-stack IEEE802.11a/g/n SDR implementation - openwifi. It is based on Xilinx Zynq Systemon-Chip (SoC) that includes Field Programmable Gate Array (FPGA) and ARM processor. With the low latency connection between FPGA and RF front-end, the most critical SIFS timing is achieved by implementing Physical layer (PHY) and low level Media Access Control (low MAC) in FPGA. The corresponding driver is implemented in the embedded Linux running on the ARM processor. The driver instantiates Application Programming Interfaces (APIs) defined by Linux mac80211 subsystem, which is widely used for most SoftMAC Wi-Fi chips. Researchers could study and modify openwifi easily thanks to the modular design. Compared to PC based SDR, the SoC is also a better choice for portable and embedded scenarios.

Wireless network technologies are becoming more and more popular. Because of this, important parts of the wireless spectrum become overloaded. Static spectrum allocation, which has been the norm for decades, is not suitable anymore. To maintain the high demand for spectrum and the continuous development of new wireless technologies, there is a need for an intelligent, dynamic spectrum allocation mechanism, where different network technologies collaboratively optimize the spectrum usage. New wireless network paradigms, such as Neutral Host Networks (NHNs) and private 5G, require a smart, spectrum-footprint-aware flow control algorithm to overcome the spectrum scarcity in collaborative way. This article presents a strategy, vision and flow control mechanism to implement collaboration in a Quality of Service (QoS)-driven way. The solution in this article is based on policies which may activate depending on its current and neighbor's network states. Through a flow ordering and selection strategy, these policies optimize the spectrum footprint, based on the performance and QoS-requirements of the own and surrounding networks. The proposed algorithm is tested extensively and validated on a large scale during the DARPA Spectrum Collaboration Challenge (SC2) competition. The results of the SC2 final event and intermediate scrimmages showed that the proposed approach increased the score, indicating increased inter-network collaboration was achieved.

Wireless netWorks are becoming more complex while applications on top are becoming more demanding. To maintain network performance in terms of latency, throughput and reliability, continuous verification of the performance, possibly followed by on-the-fly network (re)configuration is needed. To achieve this, the way wireless network monitoring is being done needs to be reconsidered and should evolve towards more timely, low overhead and fine-grained monitoring. This paper shows hoiv in-band network telemetry (INT) monitoring can achieve these objectives. An INT-enabled node architecture is designed as well as novel INT options. By means of an implementation on WiFi Linux devices, the concept is validated by tracking the behavior of a real network.

This paper presents a Convolutional Neural Network (CNN) approach for classification of low power wide area network (LPWAN) technologies such as Sigfox, LoRA and IEEE 802.15.4g. Since the technologies operate in unlicensed sub-GHz bands, their transmissions can interfere with each other and significantly degrade their performance. This situation further intensifies when the network density increases which will be the case of future LPWANs. In this regard, it becomes essential to classify coexisting technologies so that the impact of interference can be minimized by making optimal spectrum decisions. State-of-the-art technology classification approaches use signal processing approaches for solving the task. However, such techniques are not scalable and require domain-expertise knowledge for developing new rules for each new technology. On the contrary, we present a CNN approach for classification which requires limited domain-expertise knowledge, and it can be scalable to any number of wireless technologies. We present and compare two CNN based classifiers named CNN based on in-phase and quadrature (IQ) and CNN based on Fast Fourier Transform (FFT). The results illustrate that CNN based on IQ achieves classification accuracy close to 97% similar to CNN based on FFT and thus, avoiding the need for performing FFT.

Mobile traffic demand is expected to grow as much as eight-fold in the coming next five years, putting strain in current wireless infrastructures . Meanwhile the diversity of traffic and standards may explode as well. One of the most common means for matching these mounting requirements is through network densification , essentially increasing the density of deployment of operators’ base stations in many small cells and handling timing critical traffic at the edge. In this paper we take a step in that direction by implementing a virtualized small cell base station consisting of multiple, isolated LTE PHY stacks running concurrently on top of a hypervisor deployed on a cheap, off-the-shelf x86 server and a shared radio head. In particular, we show that it is possible to run multiple virtualized base stations while achieving throughput equal or close to the theoretical maximum. In contrast to C-RAN (Cloud/Centralized Radio Access Network), our virtualized small cell base station has full stack at the edge so that a low latency high throughput front-haul, which is necessary in C-RAN architecture, is not needed. This approach brings all the flexibility and configurability (from network management point of view) that a software based implementation provides while the transparent architecture enables the possibility of multiple standards sharing the same radio infrastructure.

Recently, LoRaWAN has attracted much attention for the realization of many Internet of Things applications because it offers low-power, long-distance, and low-cost wireless communication. Recent works have shown that the LoRaWAN specification for class A devices comes with scalability limitations due to the ALOHA-like nature of the MAC layer. In this paper, we propose a synchronization and scheduling mechanism for LoRaWAN networks consisting of class A devices. The mechanism runs on top of the LoRaWAN MAC layer. A central network synchronization and scheduling entity will schedule uplink and downlink transmissions. In order to reduce the synchronization packet length, all time slots that are being assigned to an end node are encoded in a probabilistic space-efficient data structure. An end node will check if a time slot is part of the received data structure in order to determine when to transmit. Time slots are assigned based on the traffic needs of the end nodes. We show that in case of a nonsaturated multichannel LoRaWAN network with synchronization being done in a separate channel, the packet delivery ratio (PDR) is easily 7% (for SF7) to 30% (for SF12) higher than in an unsynchronized LoRaWAN network. For saturated networks, the differences in PDR become more profound as nodes are only scheduled as long as they can be accommodated given the remaining capacity of the network. The synchronization process will use less than 3-mAh extra battery capacity per end node during a one year period, for synchronization periods longer than three days. This is less than the battery capacity used to transmit packets that are going to be lost in an unsynchronized network due to collisions.

A number of industrial wireless technologies have emerged over the last decade, promising to replace the need for wires in a variety of use cases. Except for customized time division multiple access (TDMA)-based wireless technologies that can achieve ultralow latency over a very limited area, wireless communication generally has reliability and latency issues when it comes to industrial applications. Closed loop communication requires high reliability (over 99%), limited jitter and latency, which poses a challenge especially over a wide area measuring in hundreds of meters. Extended coverage is promised with the advent of sub-GHz technologies, one of them being IEEE 802.11ah which is the only one that offers sufficient data rate for frequent bidirectional communication. Thus, we evaluated IEEE 802.11ah for low-latency time-critical control loops. We propose the network setup for adjusting the network dynamics to that of control loops, enabling limited jitter and high reliability. We explore the scalability of IEEE 802.11ah network hosting both control loops and monitoring sensors that periodically transmit measurements. Assigning the control loop end-nodes to dedicated restricted access window (RAW) slot results in over 99.99% successful deliveries. Furthermore, interpacket delay is concentrated around the cycle-time in the following or preceding beacon interval in case the beacon interval is at least half the value of the shortest cycle-time. Adjusting the beacon interval to the fastest control loop in the network ensures latency requirements at the cost of maximum achievable throughput and energy consumption.

In this paper, we describe the design and implementation of WiSH-WalT, a framework for controllable and reproducible LoRa testbeds. The implementation of the WiSHFUL unified interface provides the means for controlling and adapting the LoRa parameters to given conditions and low energy consumption by configuring transmission power, spreading factor, bandwidth, and error coding rate. WalT provides support for running reproducible experiments based on the deployment of docker images on a distributed set of nodes. Put together, the functionalities of WiSHFUL and WalT open new possibilities for deploying reproducible LoRa testbeds. We have used WiSH-WalT to experiment with adaptive configuration of the LoRa parameters and evaluated the communication performance of LoRa motes in a setup with several gateways.

Indoor positioning systems (IPS) aim to track objects, people or assets with the highest possible accuracy. In literature, it has been shown that among radio-frequency based technologies, ultra-wideband (UWB) is capable of providing em-level accuracy. However, this technology is not yet mature when it comes to large-area coverage and multi-user support. To remedy this, this paper proposes a TDMA protocol for a large scale localization network with numerous simultaneously active users. To this end, a full system was designed that handles the scheduling of the transmissions, the synchronization of the fixed nodes and the roaming of the mobile nodes. Moreover, the performance of the system has been analyzed by simulations using OMNeT++ and INET framework. The simulation was improved with real life experiments and has been used to evaluate full TDMA/TDoA approach. Our solution improves the scalability to 88.3 % effective spectrum usage, compared to only 18.6% when using ALOHA, while mobile nodes are able to roam successfully in 90% of the handovers.

LoRa is a long range, low power, low bit rate, single hop wireless communication technology. It is intended to be used for Internet of Things (IoT) networks, where devices are battery powered and limited bandwidth is needed. In combination with its scalability and the low end device price, LoRa is a candidate technology for low bandwidth industrial applications with a high number of communication devices spread across large areas. The use case for this paper is taken from the flower industry, where a large number of trolleys need to communicate with a server during their movement across the auction floor area. Once trolleys are outside of the auction floor they can use the public LoRaWAN network to communicate with the server, without switching communication technology. The LoRaWAN network consists of multiple end nodes and a single gateway per cell, acting as a transparent bridge between the end nodes and the network server. The measurements show that with a single LoRa gateway we can cover an indoor area of around 34000m2 only with spreading factor 7, while for spreading factor 12 the total covered area will be even higher. Also, the area outside the factory is covered when switching to spreading factor 12. We also show that the number of nodes (trolleys) that can be served by a gateway in such a case can be as high as 6000.

Due to the fast emergence of location-based services and the absence of a widely adopted localization technology for indoor environments, Indoor Localization Systems have become a central topic of research in the last decade. Although there is a significant amount of research targeting indoor localization technologies and their performance, most of these efforts only focus on theory, system design or evaluation in non-industrial environments, usually offices or healthcare spaces. In this work, a detailed performance evaluation of two commercially available accurate localization technologies, based on Bluetooth Low Energy (LE) and Ultra-wideband (UWB), in an industrial environment is presented to create an experimental understanding of their behaviour in similar conditions and to investigate their potential to be used in industrial applications with concrete localization requirements. For this purpose, these localization technologies are examined with respect to various performance criteria in several scenarios in a real industrial site.

Spectrum scarcity has been driving cellular operators to utilize unlicensed spectrum in conjunction with licensed bands to deliver mobile data to its Long-Term Evolution (LTE) users, offloading the fully allocated LTE bands. However, the use of LTE in unlicensed spectrum creates numerous challenges as the fair coexistence with other technologies. A myriad of experimental works tackles the problems involved in the coexistence of different radio access technologies (RAT) in unlicensed spectrum, however, they do not cover all aspects of the problem and fail to provide the framework adopted in the experiments for reproducible research. Therefore, in this demo we present a highly configurable packetized-LTE PHY open-source framework for coexistence experiments. The framework allows the evaluation and comparison of different coexistence techniques.

Experimental wireless network research is often very time consuming and requires knowledge of multiple experimentation platforms (JFED, OMF, etc.), thereby hindering innovation specially from non-testbed experts. To foster innovation, this paper presents an intuitive wireless experimentation using the Node-RED framework. Within the framework, drag and drop components are combined to set-up wireless experiments in simulation and testbed environments, configure network stack and execute series of experiments. Furthermore, the intuitiveness of the Node-RED framework is demonstrated by using drag and drop components to optimize multiple conflicting objectives in simulation and in a real-testbed, without requiring advanced testbed knowledge.

As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this low power wide area network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This paper uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multichannel, multispreading factor, multi-gateway, bi-directional LoRaWAN networks with thousands of end devices. Using the LoRaWAN ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact downstream traffic has on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities.

Since Global Positioning System technologies cannot be used indoors, a significant amount of research focuses on developing radio-frequency-based alternatives for indoor localization. Unfortunately, most of the suggested solutions for indoor localization consist of theoretical work or have been evaluated in non-industrial environments, typically office spaces. To evaluate the influence of industrial environments on localization accuracy, in this paper, a time-of-arrival (ToA) approach was used to determine the stationary locations of a robot inside the w-iLab.t II testbed, an open industrial-like environment containing several metal obstacles. The ToA method utilizes the measured propagation time of a radio wave between a sender and receiver to estimate their corresponding distance. This paper evaluates several industrial-related deployment aspects that influence location accuracy and describes how their negative impact can be reduced, resulting in an almost 50% accuracy improvement in industrial environments.

Wireless network deployments in industry often grow organically with new technologies added over time, among which many use the non-licensed spectrum to avoid licensing costs. As a result, technologies competing for the same spectrum end up deployed in the same area, causing coexistence problems to manifest themselves at a later stage. To avoid unexpected performance degradation, there is a need to evaluate the impact of additional wireless technologies on an existing network before the actual deployment. This paper proposes to simplify the impact assessment by emulating the signals of the potential wireless network with a single software-defined radio. To evaluate the emulator's performance, the impact of Bluetooth on Wi-Fi technology is considered as the reference scenario. A series of real-life experiments with configurable traffic load and network scale are conducted to estimate the impact of Bluetooth network on a Wi-Fi link, and the corresponding measurements are repeated with the emulated Bluetooth signals. To the best of the authors' knowledge, we are the first to propose such a solution, and it is shown that the use of our emulator gives a reliable indication of the expected impact at the location of the Wi-Fi link. As such, this paper provides an important step toward a simple, cost efficient, and reliable solution, to assess the impact of a wireless network prior to its deployment.

Wireless communication is an enabling technology for industrial automation. For mobile industrial devices operating in large areas, the performance of the wireless handover process is crucial. For the welfare of industrial processes short time communication outage must be ensured, especially for time-critical traffic. This paper assesses the handover performance for three industrial real-life use cases with different requirements. It covers handover performance under heavy interference, its impact on time-critical traffic and on broadcast traffic latency, followed by lessons learned and opportunities for further research.

The proliferation of mobile devices and the exponential growth of data transmitted over the air pushed the wireless community to find solutions in order to increase network capacity and fully exploit the available spectrum. Recently, 3GPP announced the operation of LTE in the unlicensed spectrum in order to offload the limited and expensive licensed spectrum. Concurrently, leading parties of the wireless community examine standalone operation of LTE in unlicensed spectrum. LTE was initially designed to operate in licensed spectrum and does not use any channel estimation mechanism to determine ongoing transmissions by other co-located networks. This introduces important coexistence challenges in unlicensed spectrum between LTE deployments and the current, well-established technologies, such as IEEE 802.11 (a.k.a. Wi-Fi). In this paper, we discuss the core differences between LTE and Wi-Fi, which lead to significant coexistence issues. We verify and showcase the problem by analyzing the performance degradation of Wi-Fi, when a traditional LTE network is co-located and operates in the same unlicensed frequency without any coexistence mechanism. The experiments are performed using open- source LTE and Wi-Fi implementations on real equipment in a fully controlled wireless environment. We conclude with showing the need for coexistence mechanisms, following the work that is being done within the standardization activities.

This demonstration presents a user-friendly web-based platform that supports intuitive remote benchmarking of different indoor localization solutions. It reduces the barriers for experimental evaluation and fair comparison of their performance across a set of testing environments. The platform is aimed at addressing the limitations in the current praxis of publishing indoor localization research evaluated only in local, potentially biased environments. To this end, it provides a holistic support for the benchmarking process offering: (i) multiple pre-collected raw data-traces from different RF technologies, (ii) high-level interface to control remote wireless testbed facilities, and (iii) a set of tools for creating, storing, comparing and visualizing the performance results of multiple indoor localization solutions.

In this demo we demonstrate the functionalities of a novel experimentation framework, called WiSHFUL, that facilitates the prototyping and experimental validation of innovative solutions for heterogeneous wireless networks, including cross-technology coordination mechanisms. The framework supports a clean separation between the definition of the logic for optimizing the behaviors of wireless devices and the underlying device capabilities, by means of a unifying platform-independent control interface and programming model. The use of the framework is demonstrated through two representative use cases, where medium access is coordinated between IEEE-802.11 and IEEE-802.15.4 networks.

Wireless systems often need to optimize multiple conflicting objectives (low delay, high reliability, and low cost), which are difficult to fulfill simultaneously. In such cases, the wireless system exhibits multiple optimal operation points, referred to as the optimal Pareto front (OPF). However, due to the large number of parameter settings to be evaluated and the time-consuming nature of performing wireless experiments, it is typically not possible to identify the OPF by exhaustively evaluating all possible settings. Instead, for many use cases, an approximation is good enough. To this end, this paper applies a multi-objective surrogate-based optimization (MOSBO) toolbox to efficiently optimize wireless systems and approximate the OPF using a limited number of iterations. Moreover, a real Wi-Fi conferencing scenario is optimized that has two conflicting objectives (exposure and audio quality) and four configurable parameters (Tx-Power, Tx-Rate, Codec Bit-Rate, and Codec Frame-Length). The benefits of using the MOSBO approach for such a network problem is demonstrated by approximating the OPF using 94 iterations instead of requiring the exploration of 6528 different parameter combinations, while still dominating 96.58% of the complete design space.

Spectrum sensing is one of the core functionalities of a true cognitive radio (CR) that supports operation over a broad range of frequencies and can autonomously adapt transmission parameters to the operating environment. There are several types of hardware ranging from sophisticated (i.e. Nutaq Radio420X FPGA mezzanine card) to low cost (i.e. WiSpy) that can be used to experiment with spectrum sensing. This hardware is available for use in several testbeds across the world (i.e. ORBIT, w-iLab.t, TWIST and LOG-a-TEC). Each testbed provides a specific mechanism to define, deploy and execute experiments making it difficult for an individual researcher to use more than one testbed. In this work we propose an information model for describing spectrum sensing functionality with the ultimate goal of developing and promoting a Common CR language that can describe the resources in existing GENI and FIRE testbeds.

LTE, commonly known as 4G, stands for Long-Term Evolution and is a wireless communication technology standardized by 3GPP. LTE adoption has increased drastically over the last years, and today is integrated widely in a vast number of wireless devices. However, significant restrictions, such as the increased equipment cost and the acquisition of licensed spectrum, renders experimentation with real LTE equipment very difficult. Recently, iMinds w-iLab.t testbed has been extended with commercial LTE equipment and an EPC (Evolved Packet Core) software platform, offering the opportunity to orchestrate and execute real LTE experiments, hereby providing full access to the most relevant configurable LTE parameters of the network. In this paper, we describe an LTE demonstration scenario that showcases various use cases and the respective experimental settings that can be conducted on the LTE testbed.

A large amount of research focuses on experimentally optimizing the performance of wireless solutions. Finding the optimal performance settings typically requires investigating all possible combinations of design parameters, while the number of required experiments increases exponentially for each considered design parameter. The aim of this paper is to analyze the applicability of global optimization techniques to reduce the optimization time of wireless experimentation. In particular, the paper applies the Efficient Global Optimization (EGO) algorithm implemented in the SUrrogate MOdeling (SUMO) toolbox inside a wireless testbed. Moreover, to cope with the unpredictable nature of wireless testbeds, the paper applies an experiment outlier detection which monitors outside interference and verifies the validity of conducted experiments. The proposed techniques are implemented and evaluated in a wireless testbed using a realistic wireless conferencing scenario. The performance gain and experimentation time of a SUMO optimized experiment is compared against an exhaustively searched experiment. In our proof of concept, it is shown that the proposed SUMO optimizer reaches 99.79% of the global optimum performance while requiring 8.67 times less experiments compared to the exhaustive search experiment.

More and more wireless networks are deployed with overlapping coverage. Especially in the unlicensed bands, we see an increasing density of heterogeneous solutions, with very diverse technologies and application requirements. As a consequence, interference from heterogeneous sources-also called cross-technology interference-is a major problem causing an increase of packet error rate (PER) and decrease of quality of service (QoS), possibly leading to application failure. This issue is apparent, for example, when an IEEE 802.15.4 wireless sensor network coexists with an IEEE 802.11 wireless LAN, which is the focus of this work. One way to alleviate cross-technology interference is to avoid it in the frequency domain by selecting different channels. Different multichannel protocols suitable for frequency-domain interference avoidance have already been proposed in the literature. However, most of these protocols have only been investigated from the perspective of intratechnology interference. Within this work, we create an objective comparison of different candidate channel selection mechanisms based on a new multichannel protocol taxonomy using measurements in a real-life testbed. We assess different metrics for the most suitable mechanism using the same set of measurements as in the comparison study. Finally, we verify the operation of the best channel selection metric in a proof-of-concept implementation running on the testbed.

Abstract Receiver Strength Signal Indication based Wireless Sensor Networks offer a cheap solution for location‐aware applications. For a final breakthrough these systems need fast deployment and easy auto‐configuration. In this study, we use the real‐life iMinds test bed to expand a two‐dimensional localization algorithm to the pseudo third dimension with very low additional computational time. Our experiments show that this fast three‐dimensional algorithm has no outliers and avoids manual calibration. Our algorithm has lower position errors than a maximum likelihood algorithm with a mean square error cost function. Furthermore, with non‐parametric statistical tests, we show that our previously designed two‐dimensional preprocessing performs equally well in pseudo‐three dimensions: the preprocessing reduces the position error in a statistically significant way.Copyright © 2013 John Wiley & Sons, Ltd.

Indoor localization and navigation using wireless sensor networks is still a big challenge if expensive sensor nodes are not involved.Previous research has shown that in a sparse distributed sensor network the error distance is way too high.Even room accuracy can not be guaranteed.In this paper, an easy-to-use generic positioning framework is proposed, which allows users to plug in a single or multiple positioning algorithms.We illustrate the usability of the framework by discussing a new hybrid positioning solution.The combination of a weighted (range-based) and proximity (range-free) algorithm is made.Both solutions separately have an average error distance of 13.5m and 2.5m respectively.The latter result is quite accurate due to the fact that our testbeds are not sparse distributed.Our hybrid algorithm has an average error distance of 2.66m only using a selected set of nodes, simulating a sparse distributed sensor network.All our experiments have been executed in the iMinds testbed: namely at "de Zuiderpoort".These algorithms are also deployed in two real-life environments: "De Vooruit" and "De Vijvers".

We envisage a wireless sensor network (WSN) where each node is tasked with estimating a set of node-specific desired signals that has been corrupted by additive noise. The nodes accomplish this estimation by means of the distributed adaptive node-specific estimation (DANSE) algorithm in a tree topology (T-DANSE). In this paper, we consider a network where there is at least one node with a large (virtually infinite) energy budget, which we select as the root node. We propose a modification to the signal flow of the T-DANSE algorithm where instead of each node having two-way signal communication, there is a single signal flow toward the root node of the tree topology which then broadcasts a single signal to all other nodes. We demonstrate that the modified algorithm is equivalent to the original T-DANSE algorithm in terms of the signal estimation performance, shifts a large part of the communication burden toward the highpower root node to reduce the energy consumption in the low-power nodes and reduces the input-output delay.

In a modern conference room, various of video and audio devices are provided to ensure efficient communications. This is commonly referred to as a conferencing system. Compared to wired conferencing systems, wireless systems require less deployment effort, but may become unreliable when the selected radio spectrum is highly occupied. This demo focuses on improving the quality of service of a commercial wireless conferencing system using dynamic channel selection based on real-time spectrum sensing. The proposed solution is verified in a large-scale wireless testbed, and the result shows that the link of the conferencing system is indeed more robust against interference when cognitive solution is applied.

A large amount of research focuses on experimentally optimizing performance of wireless solutions. Finding the optimal performance settings typically requires investigating all possible combinations of design parameters, and as a result the number of required experiments increases exponentially for each considered design parameter. However, Efficient Global Optimization (EGO) algorithms overcome this limitation and arrive at the global optimum performance in a very short time compared to the exhaustive search technique. In this demo, we apply the SUrrogate MOdeling (SUMO) toolbox, an efficient implementation of EGO algorithms, in order to improve the experimentation time of a realistic wireless conference solution. By tuning a speaker's transmit power and channel parameters, the SUMO toolbox searches for an improved listeners' audio quality having minimum transmission exposure. Moreover, the SUMO experiment is compared to an exhaustive search experiment and it is found that SUMO reached 99.51\% of the global optimum performance while requiring 10 times less experiments.

As open standards for the Internet of Things gain traction, the current Intranet of Things will evolve to a truly open Internet of Things, where constrained devices are first class citizens of the public Internet. However, the large amount of control over constrained networks offered by today's vertically integrated platforms, becomes even more important in an open IoT considering its promise of direct end-to-end interactions with constrained devices. In this paper a set of challenges is identified for controlling interactions with constrained networks that arise due to their constrained nature and their integration with the public Internet. Furthermore, a number of solutions are presented for overcoming these challenges by means of an intercepting intermediary at the edge of the constrained network.

The Constrained Application Protocol (CoAP) is a new Internet protocol that is currently being standardized. CoAP allows access to the drastically increasing number of smart objects and their sensing resources from virtually anywhere. It is a light-weight protocol designed to cope with the restrictions imposed by the limited resources (CPU, memory, power,...) of many smart objects. Depending on the application, information from individual objects might not be sufficient, reliable, or useful. An application may need to aggregate and/or compare data from a group of objects in order to obtain accurate results. Although multicast may be used to transmit the same request to several objects, multicast communication with smart objects has some disadvantages. Programming individual requests is another solution but lacks flexibility and opportunities for reusability. In this paper we propose a novel CoAP-based approach for communication with a group of resources across multiple smart objects. This approach organizes the group of resources that should be accessed into a new CoAP resource, called an entity, and nicely integrates several important aspects of entity management: creation, validation, usage and manipulation. In order to demonstrate the feasibility of this approach we present an implementation and experimental validation.

Cognitive radio systems have gathered a lot of research interest during the last decade. Accuracy of spectrum sensing and efficiency of free spectrum utilization are considered as the primary objectives in this emerging technology, which promises a boost in wireless network performance, through exploitation of underutilized licensed frequency bands. As the focus of researchers is usually on these two major challenges, other aspects have been in part underestimated. In this work, we consider two factors that are rather important for evaluation of cognitive platforms, namely sensing delay and energy efficiency. The first is related to the latency induced by the spectrum sensing process and its impact on sensing efficiency, which is tightly connected to both the QoS performance of secondary users and the protection of primary users. On the other hand, energy consumption is considered as a crucial issue in all types of wireless communications, due to restricted battery autonomy of mobile devices, as well as for moving towards "greener" solutions in telecommunications. Therefore, it is important to extend existing testbed experimentation tools and develop new ones, in order to equip cognitive testbeds with such advanced monitoring capabilities. In this work, we present a monitoring procedure that has been directly integrated in the experimentation tools of the CREW testbed federation and demonstrate how it aids in the online evaluation of four different cognitive platforms in terms of the aforementioned metrics.

As embedded networks are evolving to open systems, it's becoming possible to create new applications on top of these existing embedded systems. However, developing new applications can be difficult due to the large diversity of protocols that exist today. In this paper, the authors demonstrate how employing the CoAP protocol can enable rapid application development by re-using well-known principles from the Web development world. Furthermore, we also demonstrate how a number of extensions to CoAP help to lower the barrier for developing applications even further.

Wireless Sensor Networks (WSNs) are subject to high levels of dynamism arising from changing environmental conditions and application requirements. Reconfiguration allows software functionality to be optimized for current environmental conditions and supports software evolution to meet variable application requirements. Contemporary software modularization approaches for WSNs allow for software evolution at various granularities; from monolithic re-flashing of OS and application functionality, through replacement of complete applications, to the reconfiguration of individual software components. As the nodes that compose a WSN must typically operate for long periods on a single battery charge, estimating the energy cost of software evolution is critical. This paper contributes a generic model for calculating the energy cost of the reconfiguration in WSN. We have embedded this model in the LooCI middleware, resulting in the first energy aware reconfigurable component model for sensor networks. We evaluate our approach using two real-world WSN applications and find that (i.) our model accurately predicts the energy cost of reconfiguration and (ii.) component-based reconfiguration has a high initial cost, but provides energy savings during software evolution.

We developed a network platform that is responsible for an uninterrupted and seamless connectivity from the train to the wayside through heterogeneous wireless access technologies. However, limiting the offered services to only an onboard Internet is not a feasible business case. A viable one should extend to a broad spectrum of railway communication services like: train control, diagnostics, real time passenger information, entertainment, security CCTV surveillance etc. In a highly dynamic environment (from the communication link point of view) such a fast moving train, it is necessary to introduce prioritization among different traffic classes. This will implicitly determine under what conditions a certain flow should get suspended or dropped in order to preserve the flows of a higher priority as long as possible and to ensure that they meet their QoS demands. The first step towards this goal is data traffic differentiation.

In a future 'internet of things', an increasing number of every-day objects are connected with each other. Nowadays, connectivity between these devices is supported by assigning each device to an existing (wireless) network. However, these networks do not take into account the individual needs of these devices, even though all these devices are very different in terms of application requirements and hardware capabilities. Moreover, multiple existing networks are often configured independent from each other without any interaction. As an alternative, this paper proposes and discusses a methodology that more efficiently supports network cooperation between heterogeneous devices. The paper argues for autonomously created communities of similar devices, that are able to negotiate with different co-located communities to further optimize their network performance. Different communities engage in cooperation by activating network service, but only when the end result is beneficial for all involved communities. In this paper, the concepts and advantages of this approach are discussed. In addition, a methodology is explored that is able to realize these concepts. Finally, based on this methodology, possible network solutions are presented, remaining challenges are listed and future research opportunities are identified.

Handover parameter optimization is a self-optimizing network (SON) use case that promises significant performance improvement of the radio network. The basic idea is to adapt the handover control parameters, hysteresis and time-to-trigger, to the individual cell situation, in terms of e.g. the building density, cell environment and degree of user mobility. The aim is to reduce the number of handover failures, ping-pong handovers and radio link failures. We propose an handover parameter optimization algorithm that tunes the hysteresis and time-to-trigger in iterative steps and show the system performance improvement with it in both a realistic and a hexagonal simulation scenario.

This paper presents a self-optimizing algorithm that tunes the handover (HO) parameters of a LTE (Long-Term Evolution) base station in order to improve the overall network performance and diminish negative effects (call dropping , HO failures). The proposed algorithm picks the best hysteresis and time-to-trigger combination for the current network status. We examined the effects of this self-optimizing algorithm in a realistic scenario setting and the results show an improvement from the static value settings.

The goal of this paper is to investigate the performance of a mobile WiMAX system for various settings of its physical-layer parameters and for realistic propagation channels. For this, a physical layer model of IEEE 802.16e is developed in software. Different propagation channels are implemented, such as the Rayleigh channel and the SUI channel models. Moreover, a tapped delay line channel model is developed for a specific area in Ghent (Belgium) using raytracing software. For this area, the maximum achievable range of a realistic mobile WiMAX system is found to be 2.7 km. Additionally, the performance gain of MIMO systems with diversity is investigated. The diversity gain of a 2x2 MIMO Alamouti diversity scheme is found to vary between 3 and 5.5 dB.

For Mobile WiMAX, data rate and throughput figures are often presented in literature. However, the used calculation methods and the influence of the packet size on the data rate are often unclear. Therefore, we develop a new method in order to obtain more precise data rate figures at the MAC (Medium Access Control) layer. In this paper the common physical data rate and MAC data rate calculation method are first examined. Next, the new MAC data rate calculation method is presented. They are applied to the official set of Mobile WiMAX parameters. Our method is able to differentiate for different packet sizes and provides a prediction of the MAC layer throughput.

In this paper we discuss the impact of proactive routing in comparison with a reactive routing approach in an environment where multiple communication technologies are used simultaneously. Therefore the Virtual Private Ad Hoc Networking platform will be introduced and used. A simulation environment is created and used to illustrate the outcomes with a simple scenario. Although many papers have been published comparing proactive and reactive routing protocols, this paper focusses on the impact on the VPAN platform with its two-level hierarchical architecture and nodes joining and leaving clusters.

Wireless sensor networks consist of several hundredths of simple sensing devices, equipped with a radio. They are typically used for monitoring and automation purposes of large areas. Due to their simplicity, these networks quickly run out of energy, and often have problems regarding scalability and available bandwidth. To solve these issues, current research is mostly limited to the addition of extra sinks to the network, or the use of gateways to request sensor data over the Internet. In this paper, we explore how wireless sensor networks can be combined with wireless mesh networks to obtain a more optimized solution. The mesh network can be used to connect separate sensor networks, to connect sensor nodes with a monitoring platform, or as a scalable backbone for sensor to sensor communication. Additionally, we give an overview of the advantages and disadvantages of existing interconnection techniques between wireless and mesh networks, and propose several new interconnection strategies. Finally, we identify remaining challenges, upon which future research can be based.

In this paper we introduce the Virtual Private Ad Hoc Networking platform as an integrated solution for emergency communication and applications. This platform creates a virtual logical self-organizing network on top of existing network technologies reducing complexity and facilitating immediate availability. The architecture and its features will be explained in detail and matched against the specific communication needs of emergency applications.

Wireless body area networks (WBANs) offer many promising new applications in the area of remote health monitoring. An important element in the development of a WBAN is the characterization of the physical layer of the network, including an estimation of the delay spread and the path loss between two nodes on the body. This paper discusses the propagation channel between two half-wavelength dipoles at 2.45 GHz, placed near a human body and presents an application for cross-layer design in order to optimize the energy consumption of different topologies. Propagation measurements are performed on real humans in a multipath environment, considering different parts of the body separately. In addition, path loss has been numerically investigated with an anatomically correct model of the human body in free space using a 3-D electromagnetic solver. Path loss parameters and time-domain channel characteristics are extracted from the measurement and simulation data. A semi-empirical path loss model is presented for an antenna height above the body of 5 mm and antenna separations from 5 cm up to 40 cm. A time-domain analysis is performed and models are presented for the mean excess delay and the delay spread. As a cross-layer application, the proposed path loss models are used to evaluate the energy efficiency of single-hop and multihop network topologies.

Nowadays, wireless sensor and actuator networks are a hot issue because they can enable the Internet of things at little expense. Research activities mainly focus on one aspect of these networks (e.g. energy consumption) neglecting others (e.g. latency, scalability). Aspects like energy reduction, scalability, quality-of-service, and reliability are key requirements in our envisaged heterogeneous applications for sensor and actuator networks in commercial/residential buildings consisting of 1000+ nodes. In this paper, a stack which meets these requirements is proposed. We found that simulations only are not sufficient when developing WSAN solutions. We showed that it is possible to combine low-power with low-latency on large-scale QoS-aware networks.

In this paper we present a cross layer topology preserving channel selection protocol for a two interface wireless mesh network. The presented protocol is a cluster driven channel selection protocol, preserving a single interface to maintain connectivity and using the other interface to participate in small clusters. The clusters are organized by an independent set clustering algorithm, in which the cluster head dictates the operating channel for the local cluster. We show that the channel selection algorithm doubles the capacity for both a regular grid and a random topology.

Advances in low-power and low-cost sensor networks have led to solutions mature enough for use in a broad range of applications varying from health monitoring to building surveillance. The development of those applications has been stimulated by the finalization of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer for sensor networks. One of the MAC schemes proposed is slotted carrier sense multiple access with collision avoidance (CSMA/CA), and this paper analyzes whether this scheme meets the design constraints of those low-power and low-cost sensor networks. The paper provides a detailed analytical evaluation of its performance in a star topology network, for uplink and acknowledged uplink traffic. Both saturated and unsaturated periodic traffic scenarios are considered. The form of the analysis is similar to that of Bianchi for IEEE 802.11 DCF only in the use of a per user Markov model to capture the state of each user at each moment in time. The key assumptions to enable this important simplification and the coupling of the per user Markov models are however different, as a result of the very different designs of the 802.15.4 and 802.11 carrier sensing mechanisms. The performance predicted by the analytical model is very close to that obtained by simulation. Throughput and energy consumption analysis is then performed by using the model for a range of scenarios. Some design guidelines are derived to set the 802.15.4 parameters as function of the network requirements.

In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targeted at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the quality of service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 medium access controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques.

In this paper we present a protocol performing on demand distributed channel selection in multi channel, multi interface wireless mesh networks, based on the exchange of control messages. The link based channel reservation happens almost instantly when data traffic is sent through the network, and does not require long-term traffic profiles or measurements. The protocol is both simulated and implemented using the IEEE 802.11 b/g protocol. We show that in a raster topology, the protocol successfully optimizes the local spectrum usage at 87% of the nodes, and that globally, an equal amount of links is allocated to each of the channels used for the transport of data packets.

Wireless body area networks (WBANs) form a new and interesting area in the world of remote health monitoring. An important concern in such networks is the communication between the sensors. This communication needs to be energy efficient and highly reliable while keeping delays low. Mobility also has to be supported as the nodes are positioned on different parts of the body that move with regard to each other. In this paper, we present a new cross-layer communication protocol for WBANs: CICADA or Cascading Information retrieval by Controlling Access with Distributed slot Assignment. The protocol sets up a network tree in a distributed manner. This tree structure is subsequently used to guarantee collision free access to the medium and to route data towards the sink. The paper analyzes CICADA and shows simulation results. The protocol offers low delay and good resilience to mobility. The energy usage is low as the nodes can sleep in slots where they are not transmitting or receiving.

Nowadays on-board wireless broadband connectivity in mass transport vehicles, like trains and light rails, are being trialed around the world. These solutions depend on existing mobile network or satellite coverage to maintain a broadband Internet connection to these vehicles. However these technologies lack coverage in underground areas or tunnels, and an alternative "gap filler" technology is needed to keep the train connected. In this paper we discuss the architecture and design of a WLAN based gap filler network solution for rail vehicles, which is able to provide a reliable broadband connection, even at high speed.

In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targeted at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the quality of service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 medium access controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques

The IEEE 802.15.4 standard defines the medium access control (MAC) and physical layer for sensor networks. One of the MAC schemes proposed is slotted carrier sense multiple access with collision avoidance (CSMA/CA), and this paper analyzes whether this scheme meets the design constraints of low-power and low-cost sensor networks. The paper provides a detailed analytical evaluation of its performance in a star topology network for both saturated and unsaturated periodic traffic.The form of the analysis is similar to that of Bianchi for IEEE 802.11 DCF only in the use of a per user Markov model to capture the state of each user at each moment in time. The key assumptions to enable this important simplification and the coupling of the per user Markov models are however different, as a result of the very different designs of the 802.15.4 and 802.11 carrier sensing mechanisms. The performance predicted by the analytical model is very close to that obtained by simulation. Throughput and energy consumption analysis is then performed and design guidelines are derived.

Wireless body area networks (WBANs) have gained a lot of interest in the world of medical monitoring. Current implementations generally use a large single hop network to connect all sensors to a personal server. However recent research pointed out that multihop networks are more energy-efficient and even necessary when applied near the human body with inherent severe propagation loss. In this paper we present a slotted multihop approach to medium access control and routing in wireless body area networks, the wireless autonomous spanning tree protocol or WASP. It uses crosslayer techniques to achieve efficient distributed coordination of the separated wireless links. Traffic in the network is controlled by setting up a spanning tree and by broadcasting scheme messages over it that are used both by the parent and the children of each node in the tree. We analyze the performance of WASP and show the simulation results

The increasing use of wireless networks and the popularity of multimedia applications, leads to the need of Quality of Service support in a mobile IP-based environment. In [1], we investigated the reasons for path changes in the access network and we presented a framework to support these path changes regardless their cause and to avoid router inconsistencies. In this paper, the performance of this framework is thoroughly evaluated. To this end, we added the functionality of the framework to our Q-MEHROM handoff scheme [2]. However, the ideas and results presented in this paper are not restricted to this micromobility protocol. The performance with and without the defined functionalities is compared and tested under different network topologies, in terms of received service, packet loss and end-to-end delay.

Due to natural disasters or intentional attacks, large parts of our telecommunication network can be destroyed. The setup of a wireless shadow network can restore the damaged network connectivity. This paper investigates the need for a network layer solution to integrate such a wireless shadow network with the wired network. It presents the combination of the micromobility protocols MEHROM and mobile IP regional registration as an efficient solution to support terminal mobility. The proposed solution is evaluated in terms of control overhead, required storage and calculation capacity, and functional complexity

Handoffs between access points in a distributed IEEE 802.11 wireless LAN network for vehicular users can be a source of considerable packet loss. This severely degrades the visual quality of streaming video applications. In this paper we introduce the architecture of an Ethernet soft switch, which tries to preserve the quality of high bit rate streaming video upon each handoff, even if only limited resources are available access points. We have evaluated its performance in a test bed implementation for MPEG-2, MPEG-4 and H.264 video-on-demand and have compared it to the standard IEEE 802.11F-IAPP approach

In the domain of digital video coding, new technologies and solutions are emerging in a fast pace, targeting the needs of the evolving multimedia landscape. One of the questions that arises is how to assess these different video coding technologies in terms of compression efficiency. In this paper, several compression schemes are compared by means of peak signal-to-noise ratio (PSNR) and just noticeable difference (JND). The codecs examined are XviD 0.9.1 (conform to the MPEG-4 Visual Simple Profile), DivX 5.1 (implementing the MPEG-4 Visual Advanced Simple Profile), Windows Media Video 9, MC-EZBC and H.264/AVC AHM 2.0 (version JM 6.1 of the reference software, extended with rate control). The latter plays a key role in this comparison because the H.264/AVC standard can be considered as the de facto benchmark in the field of digital video coding. The obtained results show that H.264/AVC AHM 2.0 outperforms current proprietary and standards-based implementations in almost all cases. Another observation is that the choice of a particular quality metric can influence general statements about the relation between the different codecs.

Design of aggregation networks for delivering multimedia services to fast moving users is an interesting topic. Research has already been devoted to the dimensioning taking into account the movement of the users. However, the effects of packet loss and packet reordering when switching paths have not been taken into account before. This paper presents a design method that aims at minimizing packet loss and packet reordering in the dimensioning and routing process. Consequently, various routing techniques are presented and their performance is thoroughly compared. The results show that for some routing strategies only a slight extra installation cost is required for guaranteeing minimal packet loss and reordering. Deployment of routing schemes in Ethernet networks requires mapping of the calculated routes on different spanning tree instances. A path aggregation algorithm is presented that forms a minimal set of spanning tree instances out of a set of routing paths.

The increasing use of wireless networks and the popularity of multimedia applications, leads to the need of QoS (quality of service) support in a mobile IP-based environment. This paper considers the reservation of resources in the micromobility scenario. The reasons for path changes in the access network are investigated. Based upon this, we present the functionality that should be present in the different access network elements to support path changes regardless their cause and to avoid router inconsistencies. For the simulations we added this functionality to our previously developed Q-MEHROM handoff scheme (L. Peters et al., 2005). However, the ideas and results presented in this paper are not restricted to this micromobility protocol

In this paper, the focus is on the management aspects for delivery of multimedia services to fast moving users (e.g., users in trains, cars or airplanes). The considered network architecture consists of two parts: an aggregation network part and an access network part. We designed a management system for the aggregation network. The main functionalities of this management system are: (i) pre-configuration of the QoS (quality of service) tunnels, based on the results of the network capacity planning process, (ii) activation of the QoS tunnels when required and (iii) tunnel reconfiguration when the activated tunnels are insufficient to carry the instantaneous demand or in case of other failures. The main difference with existing management systems is that it is designed to deal with the rapidly moving nature of the traffic conditions and the generation of triggers for tunnel activations or reconfigurations. The management system focuses on multimedia service delivery to trains through high speed Ethernet aggregation networks. An extended GVRP (GARP (generic attribute registration protocol) VLAN registration protocol) and a new GARP protocol (G2RP) were designed and implemented as protocols for the automatic tunnel pre-configuration and activation, respectively. The management system makes use of optimization algorithms for network dimensioning and tunnel path determination. These algorithms are described in detail and their evaluation results are compared for a basic train scenario. Finally, measurement results on the performance of the designed protocols for tunnel pre-configuration and activation, are presented in detail.

In many devices, wireless network interfaces consume upwards of 30% of scarce portable system energy. Extending the system lifetime by minimizing communication power consumption has therefore become a priority. Conventional energy management techniques focus independently on minimizing the fixed energy consumption of the transceiver circuit or on scalable transmission control. Fixed energy consumption is reduced by maximizing the transceiver shutdown interval. In contrast, variable transmission rate, coding and power can be leveraged to minimize energy costs. These two energy management approaches present a tradeoff in minimizing the overall system energy. For example, variable energy costs are minimized by transmitting at a lower modulation rate and transmission power, but this also shortens the sleep duration thereby increasing fixed energy consumption. We present a methodology for energy-efficient resource allocation across the physical layer, communications layer and link layer. Our methodology is aimed at providing QoS for multiple users with bursty MPEG-4 video over a time-varying channel. We evaluate our scheme by exploiting control knobs of actual RF components over a modified IEEE 802.11 MAC. Our results indicate that the system lifetime is increased by a factor of 2 to 5 compared to the gains of conventional techniques.

With the currently emerging trials for Internet solutions on the train, it is a matter of time before best-effort Internet on the train becomes a reality. However, designing the aggregation network which transports data from fast moving users to service providers, requires extended research because an aggregation network responsible for the reliable transport of broadband multimedia traffic has not been studied before. We propose a flexible recovery strategy for Ethernet networks with dynamic VLANs. It is shown that fast recovery can be achieved in aggregation networks if standard Ethernet protocols are adjusted to co-operate with the fast and efficient link probe mechanism. Additionally a cost-effective design method is presented for networks of realistic size which aims at combining requirements of the commuters (such as end-to-end delay variations) with reliability constraints

An ad hoc network is an autonomous system of heterogeneous, mobile nodes that communicate with each other over wireless links. Routing protocols for these networks are inherently based on broadcasting control information and are therefore very bandwidth consuming. In order to limit the amount of routing information that has to be stored and maintained by the individual nodes, the technique of clustering is used. The network is partitioned into nonoverlapping sub networks, referred to as clusters, and one cluster node, the clusterhead, will take a leading role in the dissemination of control information. In this paper we approach the problem of finding an optimal partition that explicitly takes into account the heterogeneity of the network, as an integer linear programming (ILP) problem. In a second phase we have developed a new heuristic that approximates our ILP solution that is used in our clustering algorithm. It is shown that this heuristic tends to be more stable than existing clustering techniques that are solely based on ID number and/or connectivity and that do not take into account the heterogeneity of the network.

This paper describes the design of a novel tunnel set-up mechanism for Ethernet access networks. The establishment of VLAN-based tunnels is realised with a "scoped refresh" extension of the GVRP standard. For the distribution of QoS-related reservation parameters, a new GARP-based protocol (G2RP) is developed with a closed loop design for updating the reservation parameters and hop-by-hop admission control. Both protocols are implemented on a Linux test bed using the click modular router. Extensive performance evaluations were performed. The results are compared with Linux implementations of the other tunnel set-up mechanisms.

The combination of mobile IP with frequent handovers results in high handoff latencies and control overhead in the core network. Micromobility protocols like cellular IP. Hawaii and MIPv4 regional registration were developed to avoid these problems, supporting local mobility within one IP domain. Hereby, tree access topologies were considered to evaluate the protocol performance A. Campbell et al., (2000) (2002) although meshed topologies are desired for reasons of robustness against link failures and load balancing L. Peters et al., (2003). The mentioned micromobility protocols do not use the extra links or result in a bad performance in terms of end-to-end delay. This paper proposes a new micromobility protocol for random access topologies. During handoff a router in the access network detects if it has the function of cross-over node. Hereby, control traffic is concentrated near the involved access routers, while optimal paths in the access network are achieved. The basic concept of the protocol is presented and the handoff performance is compared to other micromobility protocols.