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Jorge Torres Gómez, Pit Hofmann, Frank H. P. Fitzek and Falko Dressler, "Explainability of Neural Networks for Symbol Detection in Molecular Communication Channels," IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 9 (3), pp. 323–328, September 2023. [DOI, BibTeX, PDF and Details...]
Anatolij Zubow, Christos Laskos and Falko Dressler, "Towards the Simulation of WiFi Fine Time Measurements in NS3 Network Simulator," Elsevier Computer Communications, vol. 210, pp. 35–44, October 2023. [DOI, BibTeX, PDF and Details...]
Julian Heinovski, Jorge Torres Gómez and Falko Dressler, "Focusing on Information Context for ITS using a Spatial Age of Information Model," Elsevier Computer Communications, vol. 209, pp. 203–216, September 2023. [DOI, BibTeX, PDF and Details...]
Bo-Jun Qiu, Cheng-Ying Hsieh, Jyh-Cheng Chen and Falko Dressler, "TCOA: Triple-Check Offloading Algorithm for Roadside Units and Vehicular Microclouds in 5G Networks and Beyond," IEEE Access, vol. 11, pp. 84985–85001, August 2023. [DOI, BibTeX, PDF and Details...]
Jorge Torres Gómez, Jennifer Simonjan, Josep Miquel Jornet and Falko Dressler, "Optimizing Terahertz Communication Between Nanosensors in the Human Cardiovascular System and External Gateways," IEEE Communications Letters, vol. 27 (9), pp. 2318–2322, September 2023. [DOI, BibTeX, PDF and Details...]
Justin M. Kennedy, Julian Heinovski, Daniel E. Quevedo and Falko Dressler, "Centralized Model-Predictive Control with Human-Driver Interaction for Platooning," IEEE Transactions on Vehicular Technology, vol. 72 (10), pp. 12664–12680, October 2023. [DOI, BibTeX, PDF and Details...]
Jorge Torres Gómez, Joana Angjo and Falko Dressler, "Age of Information-based Performance of Ultrasonic Communication Channels for Nanosensor-to-Gateway Communication," IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 9 (2), pp. 112–123, June 2023. [DOI, BibTeX, PDF and Details...]
Gurjashan Singh Pannu, Seyhan Ucar, Takamasa Higuchi, Onur Altintas and Falko Dressler, "Data Sharing in Virtual Edge Computing using Coded Caching," Proceedings of 14th IEEE Vehicular Networking Conference (VNC 2023), Istanbul, Turkey, April 2023, pp. 104–111. [DOI, BibTeX, PDF and Details...]
Sunasheer Bhattacharjee, Martin Damrath, Lukas Stratmann, Peter Adam Hoeher and Falko Dressler, "Digital Communication Techniques in Macroscopic Air-Based Molecular Communication," IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 8 (4), pp. 276–291, December 2022. [DOI, BibTeX, PDF and Details...]
Vineet Gokhale, Kees Kroep, R. Venkatesha Prasad, Boris Bellalta and Falko Dressler, "ViTaLS - A Novel Link-Layer Scheduling Framework for Tactile Internet over Wi-Fi," IEEE Internet of Things Journal, vol. 10 (11), pp. 9917–9927, June 2023. [DOI, BibTeX, Details...]
Kai Li, Yingping Cui, Weicai Li, Tiejun Lv, Xin Yuan, Shenghong Li, Wei Ni, Meryem Simsek and Falko Dressler, "When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds," IEEE Internet of Things Journal, vol. 10 (5), pp. 4148–4173, March 2023. [DOI, BibTeX, PDF and Details...]
Katarzyna Kosek-Szott, Szymon Szott and Falko Dressler, "Improving IEEE 802.11ax UORA Performance: Comparison of Reinforcement Learning and Heuristic Approaches," IEEE Access, vol. 10, pp. 120285–120295, November 2022. [DOI, BibTeX, PDF and Details...]
Explainability of Neural Networks for Symbol Detection in Molecular Communication Channels
November, 2023
Recent research in molecular communication (MC) suggests machine learning (ML) models for symbol detection, avoiding the unfeasibility of end-to-end channel models. However, ML models are applied as black boxes, lacking proof of correctness of the underlying neural networks (NNs) to detect incoming symbols. This paper studies approaches to the explainability of NNs for symbol detection in MC channels. Based on MC channel models and real testbed measurements, we generate synthesized data and train a neural network (NN) model for the detection of binary transmissions in MC channels. Using the local interpretable model-agnostic explanation (LIME) method and the individual conditional expectation (ICE), the findings in this paper demonstrate the analogy between the trained NN and the standard peak and slope detectors.
Towards the Simulation of WiFi Fine Time Measurements in NS3 Network Simulator
October, 2023
We present FTM-ns3, a software module which implements the 802.11 FTM protocol so that it can be used within the widely used ns3 network simulator. Moreover, we conducted experiments using commodity WiFi-FTM hardware, Intel 8260 and ESP32, and derived empirical error models which can be used in simulations to study the performance of novel FTM-based localization schemes under real channel propagation conditions while taking into account the specifics of the used WiFi hardware and configuration of FTM. Finally, we present results from simulations of a simple localization scheme based on FTM and multilateration which show the great influence of ranging inaccuracy introduced due to multipath propagation in typical indoor environments with line-of-sight (LoS) but strong multipath. Our module is provided to the community as open source and can be easily customized and extended.
Focusing on Information Context for ITS using a Spatial Age of Information Model
September, 2023
In order to cope with the vehicles’ mobility, such information is required to be as fresh as possible for proper operation of cooperative driving applications. The age of information (AoI) has been proposed as a metric for evaluating freshness of information; recently also within the context of intelligent transportation systems (ITS). We investigate mechanisms to reduce the AoI of data transported in form of beacon messages while controlling their emission rate. We aim to balance packet collision probability and beacon frequency using the average peak age of information (PAoI) as a metric. We propose a new way of interpreting the AoI by considering information context, thereby incorporating vehicles’ locations. As an example, we characterize such importance using the orientation and the distance of the involved vehicles.
TCOA: Triple-Check Offloading Algorithm for Roadside Units and Vehicular Microclouds in 5G Networks and Beyond
August, 2023
Next-generation intelligent transportation systems aim to achieve many cooperative perception and cooperative driving functions requiring considerable computational resources. Offloading such tasks via mobile edge computing is considered part of the solution and is currently being investigated in the scope of 5G networks and beyond. In this study, we propose an offloading system architecture to enable such offloading in a vehicular microcloud interconnected by a 5G core network. We model the system as a queueing model to derive closed-form solutions for selected performance metrics. Based on these insights, we propose the triple-check offloading algorithm (TCOA) to obtain both the best offloading ratio to the vehicular microcloud and the optimal maximum of the remaining vehicle instances in the vehicular microcloud. Our simulation results show that the proposed TCOA has better system performance than four other offloading schemes in terms of cost, response time, service rate, and cost response-time production service rate division (CRPSD).
Optimizing Terahertz Communication Between Nanosensors in the Human Cardiovascular System and External Gateways
July, 2023
This paper studies the intra-body communication channel between nanosensors flowing in the bloodstream and gateways attached to the skin using the terahertz (THz) spectrum. The channel model considers three layers through which the waveform travels: skin, tissue, and blood. To optimize the communication performance, this work investigates the impact of noise and mobility, and subsequently derives the trade-off between them. We illustrate the achievable bit error rate (BER) for THz intra-body channels considering communication through human tissue layers, including noise and random mobility of nanosensors in the blood system.
Centralized Model-Predictive Control with Human-Driver Interaction for Platooning
June, 2023
Cooperative adaptive cruise control presents an opportunity to improve road transportation through increase in road capacity and reduction in energy use and accidents. In this paper, we propose a centralized model predictive controller for a heterogeneous platoon of vehicles to reach a desired platoon velocity and individual inter-vehicle distances with driver-selected headway time. As a novel concept, we allow for interruption from a human driver in the platoon that temporarily takes control of their vehicle with the assumption that the driver will, at minimum, obey legal velocity limits and the physical performance constraints of their vehicle. The finite horizon cost function of our proposed platoon controller is inspired from the infinite horizon design. To the best of our knowledge, this is the first platoon controller that integrates human-driven vehicles. We illustrate the performance of our proposed design with a numerical study, demonstrating that the safety distance, velocity, and actuation constraints are obeyed.
Age of Information-based Performance of Ultrasonic Communication Channels for Nanosensor-to-Gateway Communication
May, 2023
We investigate the timely detection of abnormalities using nanosensors flowing in the blood vessels and reporting to external wearable devices. We develop analytic solutions to evaluate the information freshness using the average peak age of information (PAoI) metric. We model the mobility of nanosensors in the blood flow as a random process through a Markov chain. The communication capabilities with external devices to report detected abnormalities are modeled as a linear time-variant (LTV) channel. Besides, for communication with external devices, we study the impact of the mobility of nanosensors when using ultrasonic waveforms and integrate it with the PAoI formulation. As primary metrics, we use the bit error rate (BER), the packet error rate (PER), and the average PAoI. The results give clear insights into the impact of the position of the external monitor. We also illustrate that local communication performance almost does not influence the average PAoI.
Data Sharing in Virtual Edge Computing using Coded Caching
April, 2023
Multi-access edge computing (MEC) has been identified as a powerful concept for offloading computational tasks and for storing popular data in close proximity of end users; avoiding frequent communication to a back-end cloud server. In the context of vehicular applications, similar functionality can be provided by vehicles collaboratively offering storage and computational resources on-board, i.e., a virtual MEC concept. Data management in a virtual edge is particularly challenging due to the high degree of mobility. Coded caching is a concept to store data on distributed systems in form of fragments. When needed, these fragments are transmitted to the requesting node in a coded form so that the total number of transmissions is reduced (i.e., optimizing for reduced download times and reduced resource utilization). In this paper, we introduce a new protocol for data sharing among vehicles participating in virtual edge computing using coded caching. Our results show that coded caching improve the efficiency of data sharing by up to 50% in a virtual edge computing environment.
Digital Communication Techniques in Macroscopic Air-Based Molecular Communication
March, 2023
An air-based macroscopic molecular communication testbed exploiting fluorescence properties of water-based solutions of Uranine and Rhodamine 6G dyes is presented in this work. The testbed comprises of an industrial sprayer as its transmitter, a 2 m long tube as the transmission channel, and a high-speed camera-based detector. The considered transmission distances cover a range over several tens of centimeters to meters. The analytical end-to-end system model is extended to include the noise model in this work. Various modulation schemes exploiting the concentration levels of the sprayed dyes as the information source have been implemented and their performances are compared to the standard on-off keying. Spatial domain, along with the concentration of the dyes has been introduced as an additional degree of freedom into the testbed to improve the bit rate, and the performance is compared with respect to those modulation schemes using color and concentration levels of the dyes as degrees of freedom. Various equalization techniques and detection algorithms have also been implemented and compared. All comparative analyses are performed with respect to the measurements obtained from the testbed, the analytical models, and the particle-based Pogona simulator.
ViTaLS - A Novel Link-Layer Scheduling Framework for Tactile Internet over Wi-Fi
February, 2023
The pioneering field of Tactile Internet (TI) will enable the transfer of human skills over long distances through haptic feedback. Realizing this demands a roundtrip latency of sub-5 ms. we propose Video-Tactile Latency Scheduler (ViTaLS) - a novel link layer framework for tuning the video-tactile frame transmissions to suit their heterogeneous QoS requirements. We also present ViTaLS-optimal - a variant of ViTaLS, for further reducing the tactile latency. Objectively, we show that ViTaLS-optimal yields a latency improvement of up to 82 %. Based on experiments conducted on a real TI testbed, we subjectively demonstrate that ViTaLS-optimal outperforms the VH-multiplexer.
When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds
January, 2023
This survey introduces six typical IoT applications in the Metaverse, including collaborative healthcare, education, smart city, entertainment, real estate, and socialization. In the IoT-inspired Metaverse, we also comprehensively survey four pillar technologies that enable augmented reality (AR) and virtual reality (VR), namely, responsible artificial intelligence (AI), high-speed data communications, cost-effective mobile edge computing (MEC), and digital twins. According to the physical-world demands, we outline the current industrial efforts and seven key requirements for building the IoT-inspired Metaverse: immersion, variety, economy, civility, interactivity, authenticity, and independence.
Improving IEEE 802.11ax UORA Performance: Comparison of Reinforcement Learning and Heuristic Approaches
December, 2022
In the Wi-Fi domain, machine learing (ML) is applied to solve challenges such as efficient channel access and fair coexistence with other technologies in unlicensed bands. In this paper, we address the performance of uplink orthogonal frequency division multiple random access (UORA) in IEEE 802.11ax networks. Optimization of UORA is a good case for applying ML because of its inherent complexity and dependence on situation and time-dependent parameters. In particular, we use deep reinforcement learning to tune UORA parameters. Our simulation results show that even though the ML-based solution leads to close to optimal results, its operation is comparable to a much simpler, non-ML heuristic.
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- Explainability of Neural Networks for Symbol Detection in Molecular
Communication Channels
Recent research in molecular communication (MC) suggests machine learning (ML) models for symbol detection, avoiding the unfeasibility of end-to-end channel models. Ho...
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- November 15, 2023
Keynote at IEEE LATINCOM 2023
Falko Dressler gave a keynote titled 6G Virtualized Edge ... - November 03, 2023
Talk at KAIST Seminar on Mobile & Wireless in EE
Falko Dressler gave a seminar talk titled Virtualized Edg... - October 12, 2023
Paper presentation at IEEE VTC 2023-Fall
Atefeh Rezaei presented our paper titled Resource Allocat... - October 03, 2023
Paper presentation at European Wireless 2023
Agon Memedi presented our paper titled One-Class Support ... - October 02, 2023
Poster presentation at ACM MobiCom 2023
Jonas Kuß presented our paper titled A Measurement Syste...