Communications Signal Processing Based Solutions for Massive Machine-to-Machine Networks (M3NETs)

Lead Research Organisation: Loughborough University
Department Name: Wolfson Sch of Mech, Elec & Manufac Eng

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Publications

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Zhang W (2023) Bayesian Optimization of Queuing-Based Multichannel URLLC Scheduling in IEEE Transactions on Wireless Communications

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Chen T (2020) Blockchain Secured Auction-Based User Offloading in Heterogeneous Wireless Networks in IEEE Wireless Communications Letters

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Mohsenivatani M (2020) Completion-Time-Driven Scheduling for Uplink NOMA-Enabled Wireless Networks in IEEE Communications Letters

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Zhang L (2021) Countermeasures Against Adversarial Examples in Radio Signal Classification in IEEE Wireless Communications Letters

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Liu X (2023) Distributed Intelligence in Wireless Networks in IEEE Open Journal of the Communications Society

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Franciso J. Aparicio-Navarro (2018) Multi-Stage Attack Detection Using Contextual Information

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Khan A (2019) Network-Coded NOMA With Antenna Selection for the Support of Two Heterogeneous Groups of Users in IEEE Transactions on Wireless Communications

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Peng T (2022) Opportunistic Fountain Coding With Coordinative Routing in IEEE Wireless Communications Letters

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Abdullah Z (2021) Optimization of Intelligent Reflecting Surface Assisted Full-Duplex Relay Networks in IEEE Wireless Communications Letters

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Hassan D (2021) Polynomial GSVD Beamforming for Two-User Frequency-Selective MIMO Channels in IEEE Transactions on Signal Processing

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Liu X (2023) Risk-Aware Contextual Learning for Edge-Assisted Crowdsourced Live Streaming in IEEE Journal on Selected Areas in Communications

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Alavi F (2019) Robust Energy-Efficient Design for MISO Non-Orthogonal Multiple Access Systems in IEEE Transactions on Communications

 
Description This research project has resulted in many novel algorithms and methods for spectrally efficient machine-to-machine (M2M) communications. In particular, we have proposed bockchain technology in combination with artificial intelligence techniques for the autonomous operation of devices in a wireless network, which has great potential for future generations of wireless networks that will have massive number of connected systems and will require autonomous scheduling, resource allocation, management and operation. We have also proposed new relaying technology based on hybrid reflecting intelligent surface and relay for enhancing coverage of wireless transmissions. We have investigated vulnerability of AI technology (machine learning) in wireless networks and IoT devices and proposed new adversarial machine learning techniques to mitigate attacks on machine learning-based wireless networks.
Exploitation Route The machine learning and blockchain technology have the potential to make huge impact in the design of future generations of wireless networks. Our focus has been exactly on these topics and we disseminated results in leading intentional conferences and journals that have cited by several researchers globally.
Sectors Digital/Communication/Information Technologies (including Software)

 
Description We have proposed several novel techniques including blockchain technology for autonomous operation of distributed wireless network and devices, reflective intelligence surfaces for enhancing capacity and coverage of wireless networks and adversarial machine learning for mitigating attacks on machine learning-based wireless networks. These are very timely and emerging research works in wireless networks and our publications have attracted considerable citations and have the potential to advance security of wireless networks and devices and therefore to make economic impact. Since, several industries are interested in trusted and secure communications for internet of things (IoT) and sensors, the proposed techniques are expected to impact the design and standardization of 6G and beyond networks
First Year Of Impact 2018
Sector Digital/Communication/Information Technologies (including Software)
Impact Types Economic

 
Description Symposium Chair - IEEE Globecom - Cognitive Radio and AI Enabled Networks, Madrid 2021
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
Impact This conference is normally attended by more than 1000 scholars from academia and industries. The research findings presented in this conference normally influence the standardization and technological advancement of future generation of wireless networks.
URL https://globecom2021.ieee-globecom.org/authors/call-symposium-papers
 
Description Pervasive Wireless Intelligence Beyond the Generations (PerCom)
Amount £430,184 (GBP)
Funding ID EP/X012301/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 09/2022 
End 09/2025
 
Description Transparent Transmitters and Programmable Metasurfaces for Transport and Beyond 5G
Amount £637,215 (GBP)
Funding ID EP/W037734/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 07/2023 
End 01/2027
 
Description International academic colloboration 
Organisation University of Genoa
Country Italy 
Sector Academic/University 
PI Contribution Development of new adversarial machine learning algorithms for modulation classification.
Collaborator Contribution Knowledge and expertise in adversarial machine learning.
Impact L. Zhang, S. Lambotharan, G. Zheng, B. AsSadhan and F. Roli, "Countermeasures Against Adversarial Examples in Radio Signal Classification," IEEE Wireless Communications Letters, vol. 10 (8), pp. 1830-1834, August 2021. L. Zhang, S. Lambotharan, G. Zheng, G, Liao, A. Demontis and F. Roli, "A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification," IEEE Wireless Communications Letters, vol.11(6), pp. 1161 - 1165, June 2022. L. Zhang, S. Lambotharan, G. Zheng G. Liao, B. AsSadhan and F. Roli," Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices," IEEE IoT journal, vol. 10(3), pp. 2646 - 2657, Feb. 2023
Start Year 2020
 
Description Invited Plenary Talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact I have given a plenary talk which included the results from this project and wireless communications research in general at the 18th International Symposium on Advanced Electrical and Communication Technologies (ISAECT), Rabat, Morocco, Nov. 2018. This has attracted significant interests from participants of the conference.
Year(s) Of Engagement Activity 2018