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
Abdullah Z
(2022)
Low-Complexity Antenna Selection and Discrete Phase-Shifts Design in IRS-Assisted Multiuser Massive MIMO Networks
in IEEE Transactions on Vehicular Technology
Abdullah Z
(2020)
A Hybrid Relay and Intelligent Reflecting Surface Network and Its Ergodic Performance Analysis
in IEEE Wireless Communications Letters
Abdullah Z
(2021)
Optimization of Intelligent Reflecting Surface Assisted Full-Duplex Relay Networks
in IEEE Wireless Communications Letters
Alavi F
(2019)
Robust Energy-Efficient Design for MISO Non-Orthogonal Multiple Access Systems
in IEEE Transactions on Communications
Aparicio-Navarro F
(2018)
Multi-Stage Attack Detection Using Contextual Information
Awe O
(2021)
Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks
in Wireless Networks
Basutli B
(2018)
Network Capacity Enhancement in HetNets Using Incentivized Offloading Mechanism
in IEEE Access
Bsebsu A
(2020)
Joint beamforming and admission control for cache-enabled Cloud-RAN with limited fronthaul capacity
in IET Signal Processing
Chadza T
(2020)
Learning to Learn Sequential Network Attacks Using Hidden Markov Models
in IEEE Access
Chatzigeorgiou I
(2019)
On the Decoding Failure Probability of Random Network Coded Cooperation
Chen T
(2022)
A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks
in IEEE Internet of Things Journal
Chen T
(2020)
Blockchain Secured Auction-Based User Offloading in Heterogeneous Wireless Networks
in IEEE Wireless Communications Letters
Franciso J. Aparicio-Navarro
(2018)
Multi-Stage Attack Detection Using Contextual Information
Ghafir I
(2019)
Hidden Markov Models and Alert Correlations for the Prediction of Advanced Persistent Threats
in IEEE Access
Ghafir I
(2018)
A Basic Probability Assignment Methodology for Unsupervised Wireless Intrusion Detection
in IEEE Access
Hassan D
(2021)
Polynomial GSVD Beamforming for Two-User Frequency-Selective MIMO Channels
in IEEE Transactions on Signal Processing
Khan A
(2019)
Blockchain-Based Distributive Auction for Relay-Assisted Secure Communications
in IEEE Access
Khan A
(2020)
Trusted UAV Network Coverage Using Blockchain, Machine Learning, and Auction Mechanisms
in IEEE Access
Khan A
(2020)
Machine Learning Aided Blockchain Assisted Framework for Wireless Networks
in IEEE Network
Khan A
(2020)
Random linear network coding based physical layer security for relay-aided device-to-device communication
in IET Communications
Khan A
(2019)
Network-Coded NOMA With Antenna Selection for the Support of Two Heterogeneous Groups of Users
in IEEE Transactions on Wireless Communications
Li S
(2020)
Outage Probability Analysis for the Multi-Carrier NOMA Downlink Relying on Statistical CSI
in IEEE Transactions on Communications
Liu X
(2021)
Contextual Learning for Content Caching With Unknown Time-Varying Popularity Profiles via Incremental Clustering
in IEEE Transactions on Communications
Liu X
(2022)
Distributed Intelligence in Wireless Networks
Liu X
(2023)
Distributed Intelligence in Wireless Networks
in IEEE Open Journal of the Communications Society
Liu X
(2019)
Joint Transcoding Task Assignment and Association Control for Fog-Assisted Crowdsourced Live Streaming
in IEEE Communications Letters
Liu X
(2023)
Risk-Aware Contextual Learning for Edge-Assisted Crowdsourced Live Streaming
in IEEE Journal on Selected Areas in Communications
Mohsenivatani M
(2020)
Completion-Time-Driven Scheduling for Uplink NOMA-Enabled Wireless Networks
in IEEE Communications Letters
Peng T
(2022)
Opportunistic Fountain Coding With Coordinative Routing
in IEEE Wireless Communications Letters
Zhang L
(2023)
Attention-Based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices
in IEEE Internet of Things Journal
Zhang L
(2021)
Countermeasures Against Adversarial Examples in Radio Signal Classification
in IEEE Wireless Communications Letters
Zhang L
(2022)
A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification
in IEEE Wireless Communications Letters
Zhang W
(2023)
Bayesian Optimization of Queuing-Based Multichannel URLLC Scheduling
in IEEE Transactions on Wireless 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 |