OWIN6G in short

In the Optical and WIreless sensors Networks for 6G scenarios (OWIN6G) project, key industry and academic stakeholders are brought together with the aim of developing a structured European training programme (TP) in optical technologies to facilitate disruptive wireless sensor applications within sixth-generation (6G) networks. OWIN6G will be the first Doctoral Network dedicated to training new generation of early-stage researchers (i.e., doctoral candidates, DCs) in the field of wireless sensor networks (WSNs) for the Internet of Things/Internet of Everything as part of the 6G and beyond focusing on novel sensors, solar-cells for energy harvesting and optical detection, and hybrid RF-optical wireless technologies, and the application of machine learning to improve adoption, optimization, and security aspects in sensor networks.

OWIN6G will contribute significantly to the fundamental scientific understanding, technical know-hows and innovation of the future hybrid RF/optical WSN through the collaborative research involving ten individual DCs projects addressing specific challenges and applications. OWIN6G will make significant contributions to the fundamental scientific understanding, technical know-how and innovation of the future hybrid optical/RF sensor network. In addition to technical TP through PhD courses, dedicated tutorials and workshops organized by the Doctoral Network, DCs will be offered complementary non-technical training activities, including entrepreneurship, authoring scientific papers/patents, dissemination, etc. Having industrial partners participate will further enhance DC’s technological progress by focusing on standardization, commercialization, and handling of real-world projects in a real-world environment.

OWIN6G technology Overview

Individual Reseach Projects (IRPs)

Doctoral Candidate: Yiming Shen

Objectives: Designing and developing a distributed optical sensor system for Sensor Nodes used within WSN for real-time monitoring physical (temperature, strain, vibration) and biological (foodborne pathogens) parameters. The output of the distributed sensor array will be transmitted via the sensor node. 

Beneficiary: Eblana Photonics 

Enrollment in: TU Dublin

Supervisor: Prof. Yuliya Semenova

Doctoral Candidate: Atiyeh Nora Pouralizadeh

Objectives: To investigate (i) the limits of UWB PLC networks taking frontend and propagation effects into account; and (ii) UWB frontend design. Developing appropriate propagation models and validate them, by exemplary measurements, and perform initial performance analyses of UWB PLC backbone for WSN, compared to emerging fiber-to-the-room (FTTR) solutions.

Beneficiary: Fraunhofer Heinrich Hertz Institute

Enrollment: TU Berlin 

Supervisor: Prof. Volker Jungnickel

Doctoral Candidate: Satish Kumar Modalavalasa

Objectives: To develop (i) methods of digital twin based on data fusion from optical wireless network and millimeter wave vehicular sensor network; (ii) advanced technique(s) to predict collision in ITS or for implementation in vehicular or nonstatic industrial environment; and (iii) a simplified experimental testbed to validate such an approach.

BeneficiaryCzech Technical University in Prague

Enrollment: CTU Prague

Supervisor: Prof. Stanislav Zvanovec

Doctoral Candidate: Francisco Rau

Objectives: This includes investigating (i) 802.11 MAC scheduling algorithms for ultra-dense hybrid WSN (a  mixture of Wi-Fi, OWC, and PLC technologies),  with different traffic patterns, including media applications and sensor communications; (ii) AI/ML-driven MAC scheduling algorithms for 802.11ax networks and beyond; (iii) energy-efficient awareness mechanisms to include in the MAC scheduler; trade-offs between high data rate and low energy consumption stations; and (iv); the design and implementation of relevant scenarios to evaluate the performance of the envisaged solutions in a network simulator; as well as determine Key Performance Indicators (KPI) to effectively evaluate the performance of the envisaged solutions.

Beneficiary: Maxlinear Hispania

Enrollment: Universitat de  Valencia

Supervisor: Dr. Carlos Herranz

Doctoral Candidate: Luis Miguel Giraldo

Objectives: This includes (i) developing SDN strategies for security and communications improvements of optical WSN; (ii) defining automated security actions based on machine learning on hardware dedicated DSP; (iii) defining a set of quality-of-service figures and their relationships according to WSN 6G scenarios requirements; (iv) analyzing interaction on management network level, from devices, sensoring, network topology, hardware platform, inner communication protocol chipset design, derived from those strategies that will improve the overall efficiency of the WSN. Those strategies will rely on those QoS factors to deploy actions regarding security aware contexts for an optical WSN.

BeneficiaryUniversitat de  Valencia

Enrollment in: Universitat de  Valencia

Supervisor: Dr. Joaquin Perez

Doctoral Candidate: Alexandros Aslanidis

Objectives: Includes (i) analyse the requirements of WSN application scenarios; (ii) identify KPIs in order to meet these requirements; (iii) adopt simulation models to achieve a suitable compromise between accuracy and computational resources; (iv) develop novel optimization engines based on multi-objective optimization analysis, game theory and genetic algorithms; (v) provide a set of designs for OWIN6G for the various applications considered. 

BeneficiaryHarokopio University

Enrollment in: Harokopio University

Supervisor: Prof. Thomas Kamlalakis

Doctoral Candidate: Christos Giachoudis

Objectives: To ensure high connection reliability between the medical sensors and the access point including based on the use suitable relaying solutions; machine learning based solutions for improved scheduling and nodes’ energy consumption; proof-of-concept demonstration for a simple optical wireless body area network.

BeneficiaryÉcole Centrale Méditerranée

Enrollment in: École Centrale Méditerranée 

Supervisor: Dr. Ali Khalighi

Doctoral Candidate: Atiye Fatima Usmani

Objectives: The objective of this IRP is to provide a network level optimization of the OWIN6G hybrid WSN in terms of network protocol and topology design.  The targeted scenario include localization and environment monitoring destined for indoor settings. A scenario where sensor gateways will rely on optical cameras as both data receivers and people localization.

BeneficiaryInstituto de Telecomunicaçoes

Enrollment in: Universidade de Aveiro

Supervisor: Dr. Luis Nero Alves

Doctoral Candidate: Raul Zamorano Allanes

Objectives: Designing and implementing a solar powered sensor node for collecting data and transmission over an optical channel to the base station, which could be a fixed point or an unmanned aerial vehicle.  

Beneficiary: Northumbria University

Enrollment: Northumbria University

Supervisor: Prof. Fary Ghassemlooy

Doctoral Candidate: TBA

Objectives: Investigating the feasibility, design, implementation, and performance limits of flexible solar cells-based receiver for data communication and indoor localization and asset tracking within a PoE backbone network. 

BeneficiaryIntegrated System Technologies

Enrollment: Northumbria University

Supervisor: Dr. Geoff Archenhold

Workpackages (WPs)

Objectives: Design, and development of novel SNs with (i) distributed biochemical optical sensor for environmental monitoring, and medical diagnostics; (ii) standalone mobile electro-optical sensor nodes for indoor applications; (iii) solar-cell-based power units;  and (iv) hybrid RF-optical transceivers.

Objectives: To (i) optimize the energy usage of WSN for IoT/IoE applications in sensitive medical/industrial environments, which is crucial for battery-powered SNs; (ii) analyze the limitations of sensor infrastructure, including PLC as a cost-effective backbone; (iii) propose relaying and switching solutions in order to reduce power consumption as well as provide the necessary tools to improve the backbone for RF and optical wireless communication in a wireless sensor network; (iv) provide tools for improving hybrid RF-optical wireless communication backbones in WSNs; and (v) design efficient WSN MAC layer protocols that incorporate machine learning and perform a trade-off between data rates and power consumption.

Objectives: To (i) develop functional and non-functional requirements for a range of OWIN6G application scenarios; (ii) investigating SDN-based management for OWIN6G with adoptability and enhanced security as well as creating an appropriate platform; (iii) provide an optimization framework for hybrid OWC/RF architectures; and (iv) develop the project’s pilots to be used as experimental demos as part of DC research projects.

Objectives: To (i) coordinate the training activities of OWIN6G; (ii) continuously monitoring the progress of DCs research activities; and (iii) liaise with European Committee on all aspects of OWIN6G to ensure its smooth running.

Objectives: To (i) organize two training schools (years 2 and 3), two workshops (years 1 and 2), two industrial dissemination day events, and one final conference; (ii) coordinate OWIN6G’s dissemination activities; (iii) coordinate the exploitation of research results; and (iv) contribute to standardization and handle patent management.