QMUL Centre for Networks, Communications and Systems News

New hybrid positioning system promises reliable tracking where GPS fails

Thu, 16 Jul 2026 23:00:00 +0100

Researchers have unveiled a new location‑tracking system that could dramatically improve navigation in places where GPS signals routinely fail, such as tunnels, dense cities and underground transport routes. In a new study presented at the IEEE International Conference on Communications in Glasgow, researchers from Queen Mary University of London and partners from around the world showcased the system, called Joint DAS and GNSS (JDG), which blends traditional satellite‑based GPS with a lesser‑known technology referred to as Distributed Acoustic Sensing (DAS). DAS uses existing fibre‑optic cables—already buried beneath roads and pavements—as ultra‑sensitive vibration sensors. When someone moves nearby, the fibres detect tiny shifts that can be translated into movement patterns. In a real‑world trial in southern England, the research team logged both GPS data and vibration signals from a roadside fibre‑optic cable as volunteers walked along the route. These combined signals were fed into a deep‑learning model that could continue predicting a person's location even when GPS was blocked, noisy or only sporadically available. The collaborators combined expertise from Queen Mary in London, Xi'an Jiaotong University, Xi'an, P.R. China, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India and Chicago State University, Chicago. The results were striking: the JDG system consistently outperformed GPS‑only tracking and other prediction methods, remaining accurate even during complete GPS outages. It also proved resilient on lower‑powered devices that collect fewer location points, suggesting it could support a wide range of smartphones and IoT sensors The team says the technology could strengthen location services for smart transport, emergency response, and autonomous navigation—particularly in cities and indoor or underground spaces where GPS performance is notoriously unreliable. ENDS "An Augmented GNSS-DAS Architecture for Continuous and Robust Positioning" presented at the IEEE International Conference on Communications May 2026 and published online on 14 July 2026. https://ieeexplore.ieee.org/document/11587254 doi: 10.1109/ICC59461.2026.11587254

From seabed to space: the integration challenge for heterogeneous optical networks

Sun, 05 Jul 2026 23:00:00 +0100

Dr. Paul Anthony Haigh, Associate Professor at Queen Mary University of London, is exploring how to seamlessly connect fibre, underwater, free-space and satellite optical communication systems into a single end-to-end network. The vision is to create a continuous optical path that carries data from the seabed all the way to space without converting signals between different transmission technologies, improving efficiency, speed and network performance. Dr Paul Anthony Haigh says: " Next-generation connectivity won't come from any single technology, but from getting sea, air, space and fibre networks to work as one integrated system. In this piece for Electro Optics, we explore why the offshore wind, ocean monitoring and submarine cable infrastructure we depend on today still lack a unified connectivity architecture, and what it will take to build one"

International Women in Engineering Day: meet Mona Jaber and Valentina Donzella.

Wed, 17 Jun 2026 23:00:00 +0100

In celebration of International Women in Engineering Day, we highlight the innovative research of Mona Jaber and Valentina Donzella. Dr Mona Jaber is Head of the Centre for Networks, Communications and Systems. As a child, Mona was fascinated by how engineering could solve real-world problems and she knew then that she wanted to be an engineer. That early curiosity has grown into a lifelong passion that now drives her research in artificial intelligence and Internet of Things technologies. In this video, Mona discusses her research and explains how the Internet of Things—networks of connected devices and sensors—can help create healthier, more sustainable cities by improving the way we manage resources, services and urban infrastructure. Professor Valentina Donzella is a member of the Centre for Intelligent Transport and the Deputy Head of the Centre for Advanced Robotics. Her research focuses on making intelligent technologies, such as robots and self-driving vehicles, safer and more reliable. She studies how sensors—including cameras, radar, thermal cameras and LiDAR—collect information about the world, and how factors such as bad weather, poor visibility or busy environments can affect the quality of that information. Valentina develops new methods to improve and combine data from different sensors, helping artificial intelligence systems make better decisions in real-world situations. She is particularly interested in using computer simulations and AI-generated data to test and train intelligent systems, as well as developing ways to assess data quality and system performance. Her work also explores how intelligent systems can operate safely using less data, helping to make future transport and robotic technologies both safer and more sustainable.

Call for Papers: Signal Processing for Fluid Antenna Systems: Foundations, Algorithms, and ...

Mon, 15 Jun 2026 23:00:00 +0100

Special Issue: Call for Papers Please find the the deatils about this Speciall Issue on AI-native Smart Radio Environments for 6G within the f IEEE Signal Processing Magazine with Dr. Maged Elkashlan as Guest Editor. Important Dates: 1 August 2026 --- White Paper Due 1 September 2026 --- Invitation Notification 15 November 2026 --- Full-Length Manuscripts Due 15 February 2027 --- First Review to Authors 15 April 2027 --- Revision Due 15 June 2027 --- Final Decision 1 August 2027 --- Final Package Due December 2027 --- Publication Scope Fluid Antenna Systems (FAS) introduce dynamically reconfigurable radiating apertures that transform every major branch of signal processing---channel estimation, DOA estimation, beamforming, sparse recovery, statistical detection, and machine learning---from inference under a fixed observation model into joint sensing-and-inference design problems. This Special Issue of IEEE Signal Processing Magazine invites tutorial-style overview articles, comprehensive surveys, and original contributions with broad appeal that address the signal processing challenges and opportunities introduced by FAS. Topics include channel modeling, performance bounds, channel estimation and tracking, beamforming and precoding, array signal processing, sparse recovery, statistical detection, machine learning, ISAC, RIS-aided FAS, near-field processing, hardware-aware design, and standardization. Submitted manuscripts must make clear contributions to signal processing theory, algorithms, or methodology. Papers that focus primarily on communication system-level performance evaluation (e.g., throughput, outage probability) without substantial signal processing innovation are outside the scope of this special issue. Manuscripts should conform to the standard format as indicated in the Manuscript Submission Guidelines on the IEEE Signal Processing Magazine website ( IEEE SPM ScholarOne Portal: https://mc.manuscriptcentral.com/spmag-ieee). All manuscripts must be submitted through the Author Portal. Select the "Signal Processing for Fluid Antenna Systems: Foundations, Algorithms, and Emerging Applications" topic from the drop-down menu.

Special Issue on Fluid Antenna Systems for Autonomous IoT: Agentic AI, Edge Intelligence, and ...

Mon, 15 Jun 2026 23:00:00 +0100

Special Issue: Call for Papers Please find the the deatils about this Speciall Issue on AI-native Smart Radio Environments for 6G within the IEEE Internet of Things Journal with Dr. Maged Elkashlan as Guest Editor. Important Dates: Submission Deadline: December 31, 2026 First Review Due: February 15, 2027 Revision Due: March 15, 2027 Second Reviews Due/Notification: April 30, 2027 Final Manuscript Due: June 30, 2027 Publication Date: August 2027 Scope Fluid Antenna Systems (FAS) are emerging as a key technology for next-generation IoT networks by enabling dynamic adaptation of antenna positions, activation patterns, and radiation characteristics in real time. Unlike conventional fixed antennas, FAS can continuously reconfigure themselves to optimize connectivity, reliability, and spectrum utilization across diverse applications such as smart cities, Industry 4.0, precision agriculture, and intelligent healthcare. The integration of artificial intelligence further enhances FAS capabilities. Agentic AI can autonomously monitor wireless environments and optimize antenna configurations, while Edge AI enables real-time, distributed decision-making directly at IoT devices. Large Language Models (LLMs) can provide intuitive interfaces for network management and support semantic communication paradigms. Together, these technologies enable self-optimizing, self-healing, and adaptive IoT ecosystems. This Special Issue focuses on the convergence of FAS and AI for autonomous IoT networks. It seeks contributions on FAS design and optimization, AI-driven antenna control, distributed edge intelligence, LLM-enabled network management, and practical implementations demonstrating the benefits of AI-empowered FAS across a wide range of IoT applications. Topics of interest include (but are not limited to): · FAS system design and optimization for intelligent IoT ecosystems · Agentic AI systems for autonomous FAS control and optimization · Edge AI for distributed and real-time FAS adaptation · LLM-powered natural language interfaces for FAS configuration · Fluid antenna multiple access (FAMA) with AI-enhanced scheduling · Deep learning and reinforcement learning for FAS optimization · Multi-agent coordination for distributed FAS-IoT networks · Generative AI for FAS channel modeling and beamforming design · FAS-enabled integrated sensing and communication (ISAC) systems · Semantic communication enabled by LLMs and FAS integration · Self-evolving FAS networks with continuous learning capabilities · Explainable AI for interpretable FAS decision-making · Energy-efficient AI-FAS co-design for sustainable IoT · FAS for massive machine-type communications and ultra-reliable IoT · Smart city applications with AI-empowered FAS infrastructure · Industrial IoT and smart manufacturing with FAS connectivity · Healthcare IoT with FAS-enabled reliable communications · Autonomous vehicle networks with FAS coordination · FAS for precision agriculture and environmental monitoring · Experimental platforms and testbeds for AI-FAS integration · Standardization and commercialization of FAS for IoT systems · Security and privacy mechanisms for AI-empowered FAS networks. Submission: The original manuscripts to be submitted need to follow the guidelines at: https://ieee-iotj.org/wp-content/uploads/2025/02/IEEE-IoTJ-Author-Guidelines.pdf, which should not be concurrently submitted for publication in other venues. Authors should submit their manuscripts through the IEEE Author Portal at: https://ieee.atyponrex.com/journal/iot. The authors must select as "Special Issue on Fluid Antenna Systems for Autonomous IoT: Agentic AI, Edge Intelligence, and Foundation Models" when they reach the "Article Type" step in the submission process.

AI-native Smart Radio Environments for 6G: Evolving from Conventional Architectures to ...

Mon, 15 Jun 2026 23:00:00 +0100

Special Issue: Call for Papers Please find the the deatils about this Speciall Issue on AI-native Smart Radio Environments for 6G within the IEEE Network Journal with Dr. Maged Elkashlan as Guest Editor. More details can be found at the following link: https://www.comsoc.org/publications/magazines/ieee-network/cfp/ai-native-smart-radio-environments-6g-evolving-conventional Important Dates: Manuscript Submission Deadline: 30 September 2026 Initial Decision: 1 January 2027 Revision Manuscript Due: 1 February 2027 Final Decision: 1 March 2027 Final Manuscript Due: 15 March 2027 Publication Date: June 2027 Scope The sixth generation (6G) of wireless networks is expected to transform communication systems from highly connected infrastructures into fully intelligent and autonomous ecosystems. Central to this vision is the concept of self-governing networks, which can autonomously perceive their environment, make intelligent decisions, and execute actions without human intervention. Unlike current "AI for Wireless" approaches, where artificial intelligence is typically used as an external optimization tool, self-governing networks integrate AI directly into the network architecture, enabling proactive and system-wide management. This paradigm shift is particularly important as future 6G systems combine terrestrial, aerial, and satellite platforms, creating highly dynamic and complex operating environments. To address these challenges, networks must continuously monitor their context, formulate policies that optimize long-term objectives, and dynamically adapt resources and topology through programmable infrastructure. This Special Issue aims to establish the architectural and algorithmic foundations of AI-native self-governing wireless networks. It focuses on the complete autonomy lifecycle, including environmental sensing, situational awareness, intelligent reasoning, policy generation, distributed coordination, and autonomous actuation. Contributions are sought on technologies that enable networks to autonomously manage communication, computing, caching, and networking resources while adapting to changing conditions. The Special Issue particularly welcomes experimental and practical contributions, including real-world testbeds, hardware prototypes, proof-of-concept implementations, and industry–academia collaborations that demonstrate the feasibility of self-governing architectures. In line with the mission of IEEE Network, submissions should emphasize system-level impact, architectural innovation, and cross-layer autonomy. Authors are encouraged to highlight network- and architecture-level implications rather than focusing exclusively on physical-layer signal processing or mathematical optimization.

Summer research internships for undergraduate students

Fri, 12 Jun 2026 23:00:00 +0100

Ten talented undergraduate students from across a wide range of Science and Engineering programmes are embarking on exciting summer research internships under the mentorship of academic supervisors. This fantastic opportunity has been made possible through the QMUL Summer Training Research Initiative to Support Diversity and Equality (STRIDE) and the London Mathematical Society's Undergraduate Research Bursaries (URB) scheme. Spanning the full breadth of Science and Engineering, these diverse and innovative projects offer students a unique chance to explore research, develop new skills, and gain first-hand experience of academic discovery. We hope the programme will inspire the next generation of researchers and ignite a lasting passion for scientific inquiry. Below, you can find the full list of projects, students, and supervisors taking part in this year's programme. Zahra Ibrahim Ahmed Yusuf: An inclusive approach to measuring depression in neurodivergent young adults from diverse backgrounds (supervisor Giorgia Michelini) Tahran Tinnin Motlib-Siddiqui: Bioelectronic Sensors for Lanthanides (supervisor Lin Su) Radoslaw Bukowiński: LoRa-Based Satellite Ground Station Development and Link Analysis using the TinyGS Network (supervisor Fatma Benkhelifa) Mohammed Rizwan Miah: Offshore Aquaculture Renewables (supervisor Eldad Avital) Elsie Chidera Obiako: Developing AI tools for image-based diagnosis (supervisor Shaheer U Saeed) Amina Abulrahim Montalto: Domestic Water Recycling (supervisor Eldad Avital) Nursen Adiba Chowdhury: Synthesis, Fabrication and Characterization of Novel Antiferroelectric Materials (supervisor Giuseppe Viola) Ivet Lobo: Combinatorial search algorithms- AI and Machine Learning vs Integer Optimization (supervisor Thomas Prellberg) Zishan Xu: Higher order hyperbolic problems with singularities (LMS URB, supervisor Claudia Garetto) Oliver Leo Carter: Matroids that maximase a valuative invariant (LMS URB, supervisors Alex Fink and Mark Jerrum)

IEEE Distinguished IoT Webinar: "IoT-Enabled Intelligent Transportation Systems for ...

Thu, 09 Apr 2026 23:00:00 +0100

Mona Jaber delivered an invite talk to the IEEE Distinguished Webinars series. Title: IoT-Enabled Intelligent Transportation Systems for Sustainable Future Cities Abstract: Intelligent Transportation Systems (ITS) integrate digital technologies, such as sensing, communications, data analytics, and artificial intelligence (AI), to make transportation safer, more efficient, reliable, and sustainable. This talk explores emerging IoT-enabled sensing technologies and AI-driven approaches that are reshaping ITS, with a particular focus on improving road safety through the co-design of smart infrastructure and smart vehicles. The first part of the talk focuses on smart roads. Conventional sensing modalities for ITS, such as cameras and LiDAR, are widely used to support safe, efficient, and low-emission mobility. However, these technologies face well-known limitations, including degraded performance under adverse weather or visibility conditions. To address these challenges, we present Distributed Acoustic Sensing (DAS), a novel sensing paradigm that leverages existing buried optical fibre infrastructure to monitor road traffic. In contrast with existing sensing methods, DAS enables continuous, energy-efficient sensing over distances of up to 50 km, is robust to adverse conditions, and is inherently privacy preserving. The second part of the talk focuses on smart vehicles and human-centred AI. While autonomous vehicles are not subject to fatigue, distraction, or intoxication, this alone does not guarantee safer roads for pedestrians and wheelers. These often have unconstrained and unpredictable behaviour in complex traffic environments, which is challenging to predict. The talk will present a contextual stacked ensemble model that outperforms the state of the art while achieving up to 25× lower inference latency, enabling real-time pedestrian intent prediction. Please visit https://iot.ieee.org/education.html for slides and video recording.

First CNCS Industry Exhibition

Tue, 17 Mar 2026 00:00:00 +0100

The Centre for Networks, Communications, and Systems successfully hosted its first Industry Exhibition, marking a significant milestone for the centre. The event welcomed over 30 attendees, and we had the pleasure of showcasing our research to industry partners and guests. It was a proud moment to see the quality of work and the collective effort across the centre, spanning both the Networks Group and the Communications Systems Research Group. The exhibition also featured an inspiring keynote from our Head of School, which set the tone for engaging discussions and future collaboration. If you missed our event, you can still visit our posters displayed on the 4th floor of Peter Landin.

Three women leading research in Science and Engineering

Sun, 01 Mar 2026 00:00:00 +0100

To mark International Women's Day, we spotlight three women leading research in Science and Engineering. Meet Silvia Liverani (Head of the Centre for Probability, Statistics and Data Science) Mona Jaber (Head of the Centre for Networks, Communications, and Systems) and Ana Sobrido (Head of the Centre for Centre for Sustainable Engineering). Silvia Liverani I love uncovering the structure hidden in messy data using statistical models to find those patterns. My research focuses on developing advanced statistical methods for complex datasets, and one aspect I really enjoy is that I get to collaborate with researchers in other fields, including biologists, psychologists, clinicians, etc. I have been the Head of the Centre in Probability, Statistics and Data Science since 2023. The Centre is an exciting group of academics, PDRAs and PhD students, spanning from pure mathematics to applied statistics and image processing. Mona Jaber As a child, I was fascinated by how engineering could solve real-world problems and I knew then that I wanted to be an engineer. That early curiosity has grown into a lifelong passion that now drives my research in artificial intelligence and Internet of Things technologies, accelerating our progress toward more sustainable urban environments. Today, as Head of the Centre for Networks, Communications, and Systems, I have the privilege of working alongside exceptional colleagues on truly inspiring projects. What excites me most is not only the individual breakthroughs, but the possibility of bringing these innovations together, connecting ideas, systems, and disciplines, to then help shape a more sustainable future. Ana Sobrido My love for science started as a kid in school, when watching chemical reactions unfold felt like witnessing magic, sparking a curiosity to understand the hidden rules behind them. This led me to pursue a career in Chemistry where I developed a particular interest in materials for energy. My research pioneers sustainable materials and innovative manufacturing approaches to enable the next generation of energy storage and conversion technologies, helping accelerate the transition to a more resilient and low-carbon future. As Head of the Centre for Sustainable Engineering, I am excited about building on strong existing foundations to address the most pressing sustainability challenges. I look forward to working with fantastic colleagues, driving innovation and impactful research and excellence in teaching and learning, while fostering an open, inclusive, and inspiring environment for all.

Dr. Maged Elkashlan recognised as IEEE VTS Top Performing Editor 2025

Fri, 27 Feb 2026 00:00:00 +0100

We are delighted to congratulate Dr. Maged Elkashlan on being recognised by the IEEE Vehicular Technology Society as a Top Performing Editor for his outstanding contributions as an Associate Editor of IEEE Transactions on Vehicular Technology in 2025. This distinction reflects his exceptional dedication, professionalism, and commitment to maintaining the highest standards of quality and rigor in scholarly publishing within the vehicular and wireless communications research community. His service significantly contributes to advancing innovation and excellence in the field.

Professor Arumugam Nallanathan among the world's most highly cited researchers for 2025.

Fri, 05 Dec 2025 00:00:00 +0100

Professor Nallanathan has been named a Highly Cited Researcher in Computer Science for the fourth consecutive year. He is one of just 119 researchers recognised globally in this field, and one of only 12 listed from the UK. Congratulations to Professor Arumugam Nallanathan, founding head of the Communication Systems Research (CSR) Group and Professor of Wireless Communications Fill article avaible here https://www.qmul.ac.uk/eecs/news-and-events/news/items/eecs-professor-among-the-worlds-most-highly-cited-researchers-for-2025.html

Queen Mary Joins AI-RAN Alliance to Drive Innovation in AI-Enabled Wireless Networks

Thu, 06 Nov 2025 00:00:00 +0100

The School of Electronic Engineering and Computer Science (EECS) at Queen Mary University of London (QMUL) is proud to announce its membership in the AI-RAN Alliance, marking a significant step forward in advancing research and innovation in AI-driven communication systems. This collaboration bridges the gap between academic research and industrial application, fostering the development of AI-native architectures and next-generation wireless technologies that will shape the evolution of 5G, 6G, and beyond. Through this partnership, QMUL will contribute its expertise to the Alliance's AI-for-RAN, AI-on-RAN, and Data-for-AI working groups, helping shape the next generation of adaptive, efficient, and self-optimizing mobile networks. QMUL researchers view AI as a transformative force in wireless communication, enabling: Real-time, AI-driven network control Energy-efficient RAN operation Scalable support for massive IoT and autonomous systems Continuous learning through simulation-driven design This synergy between academic research and industrial deployment ensures that new technologies are not only theoretically sound but also practically validated, accelerating the transition from research to real-world implementation.

Digital Twins Take Centre Stage: Inspiring Ideas and Collaboration at QMUL's IEEE Panel

Thu, 30 Oct 2025 00:00:00 +0100

The Old Library at Queen Mary University of London was alive with conversation and ideas as more than 60 researchers, professionals, and students gathered for the IEEE UK and Ireland Section panel, "Twinned Realities: Shaping Our World with Digital Models." on 30th October 2025! Led by Dr. Mona Jaber, Reader in Internet of Things at QMUL, the event brought together leading voices in digital innovation to explore how digital twin technologies are reshaping the way we model, manage, and understand complex systems. The panel featured Prof. Akram Alomainy, Paul M. Cunningham, Dr. Caroline Roney, Prof. Christopher Pain, Dr. Jason Shepherd, and Prof. Berk Canberk, who shared insights spanning medicine, infrastructure, AI, and systems engineering. Discussions covered everything from cardiac digital twins used in in-silico clinical trials to sustainable city modelling and intelligent service platforms that bridge the physical and digital worlds. Reflecting on the discussion, Prof. Akram Alomainy highlighted the transformative power of collaboration in this fast-moving field: "Digital twins sit at the intersection of science, engineering, and creativity. What makes them truly exciting is how they bring together expertise from so many disciplines to solve real-world problems in smarter, faster, and more human-centred ways." Dr. Jaber described the event as "a wonderful exchange of ideas that showcased the creativity and collaboration driving this field forward." With more than sixty participants engaging during the session and many staying afterward to continue conversations, the enthusiasm in the room reflected growing momentum behind digital twin research and its cross-sector potential. As one attendee put it, "Digital twins are no longer just simulations; they're becoming living digital entities. Their connection with Agentic AI could redefine how we build and interact with complex systems." The event closed with a strong sense of optimism and plans for future collaboration between academia and industry. Dr. Jaber thanked all speakers and attendees for making the panel a success: "The level of engagement and discussion was inspiring; I look forward to seeing how these conversations grow into new ideas and partnerships."

IEEE Communications Society Heinrich Hertz Award for Best Communications Letter awarded to Dr ...

Thu, 14 Aug 2025 23:00:00 +0100

Congratulation to Dr Maged Elkashlan and Professor Michael Chai who are selected co-recipients of the IEEE Communications Society Heinrich Hertz Award for Best Communications Letter for their paper, "Active RIS Versus Passive RIS: Which is Superior with the Same Power Budget?," IEEE Communications Letters, vol. 26, no. 5, pp. 1150-1154, May 2022. You can access the full paper here: https://ieeexplore.ieee.org/document/9734027