Unlocking Potentials of MIMO Full-duplex Radios for Heterogeneous Networks (UPFRONT)
Lead Research Organisation:
Loughborough University
Department Name: Wolfson Sch of Mech, Elec & Manufac Eng
Abstract
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Organisations
Publications
Wang W
(2018)
Robust Multigroup Multicast Transmission for Frame-Based Multi-Beam Satellite Systems
in IEEE Access
Xia W
(2020)
Model-Driven Beamforming Neural Networks
in IEEE Wireless Communications
Xia W
(2020)
A Deep Learning Framework for Optimization of MISO Downlink Beamforming
in IEEE Transactions on Communications
Xia W
(2022)
Multiagent Collaborative Learning for UAV Enabled Wireless Networks
in IEEE Journal on Selected Areas in Communications
Yan X
(2019)
The Application of Power-Domain Non-Orthogonal Multiple Access in Satellite Communication Networks
in IEEE Access
Yan X
(2018)
Performance Analysis of NOMA-Based Land Mobile Satellite Networks
in IEEE Access
Yan X
(2020)
Ergodic Capacity of NOMA-Based Uplink Satellite Networks With Randomly Deployed Users
in IEEE Systems Journal
You M
(2021)
Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks
in IEEE Transactions on Wireless Communications
Yu D
(2024)
Kalman Filter Based Channel Tracking for RIS-Assisted Multi-User Networks
in IEEE Transactions on Wireless Communications
Yuan Y
(2021)
Meta-Reinforcement Learning Based Resource Allocation for Dynamic V2X Communications
in IEEE Transactions on Vehicular Technology
Yuan Y
(2021)
Transfer Learning and Meta Learning-Based Fast Downlink Beamforming Adaptation
in IEEE Transactions on Wireless Communications
Zhang J
(2020)
Fast Specific Absorption Rate Aware Beamforming for Downlink SWIPT via Deep Learning
in IEEE Transactions on Vehicular Technology
Zhang J
(2020)
Specific Absorption Rate-Aware Beamforming in MISO Downlink SWIPT Systems
in IEEE Transactions on Communications
Zhang J
(2020)
Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration
in IEEE Transactions on Wireless Communications
Zhang J
(2021)
Fast Meta Learning for Adaptive Beamforming
Zhang J
(2022)
Embedding Model-Based Fast Meta Learning for Downlink Beamforming Adaptation
in IEEE Transactions on Wireless Communications
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
(2022)
A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification
in IEEE Wireless Communications Letters
Zhang L
(2021)
Countermeasures Against Adversarial Examples in Radio Signal Classification
in IEEE Wireless Communications Letters
Zhang W
(2023)
Bayesian Optimization of Queuing-Based Multichannel URLLC Scheduling
in IEEE Transactions on Wireless Communications
Zhang X
(2021)
Auction-Based Multichannel Cooperative Spectrum Sharing in Hybrid Satellite-Terrestrial IoT Networks
in IEEE Internet of Things Journal
Zhang X
(2021)
Secure Transmission in Cell-Free Massive MIMO With RF Impairments and Low-Resolution ADCs/DACs
in IEEE Transactions on Vehicular Technology
Zhang X
(2022)
Stochastic Geometry-Based Analysis of Cache-Enabled Hybrid Satellite-Aerial-Terrestrial Networks With Non-Orthogonal Multiple Access
in IEEE Transactions on Wireless Communications
Zhang X
(2020)
A Reinforcement Learning-Based User-Assisted Caching Strategy for Dynamic Content Library in Small Cell Networks
in IEEE Transactions on Communications
Zhang X
(2019)
Calibrated Learning for Online Distributed Power Allocation in Small-Cell Networks
in IEEE Transactions on Communications
Zhang Y
(2022)
Secure Transmission in Cell-Free Massive MIMO With Low-Resolution DACs Over Rician Fading Channels
in IEEE Transactions on Communications
Zheng G
(2017)
Optimization of Hybrid Cache Placement for Collaborative Relaying
in IEEE Communications Letters
Zhou G
(2020)
Energy Efficiency and Delay Optimization for Edge Caching Aided Video Streaming
in IEEE Transactions on Vehicular Technology
Zhu Y
(2020)
Spectrum and Energy Efficiency in Dynamic UAV-Powered Millimeter Wave Networks
in IEEE Communications Letters
Zhu Y
(2018)
Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-Antenna Dense Small Cell Networks
in IEEE Transactions on Wireless Communications
Zhu Y
(2018)
Performance Analysis of Cache-Enabled Millimeter Wave Small Cell Networks
in IEEE Transactions on Vehicular Technology
Zhu Y
(2017)
Secure Communications in Millimeter Wave Ad Hoc Networks
in IEEE Transactions on Wireless Communications
Zhu Y
(2018)
Secrecy Rate Analysis of UAV-Enabled mmWave Networks Using Matérn Hardcore Point Processes
in IEEE Journal on Selected Areas in Communications
Zhu Y
(2019)
Blockchain-Empowered Decentralized Storage in Air-to-Ground Industrial Networks
in IEEE Transactions on Industrial Informatics
Zhu Y
(2020)
Stochastic Geometry Analysis of Large Intelligent Surface-Assisted Millimeter Wave Networks
in IEEE Journal on Selected Areas in Communications
| Description | We have made several findings regarding self-interference cancellation and performance of full-duplex cellular networks. These findings includes 1). For SIC, we have investigated the design, isolation, and radiation pattern performance of coaxially fed orthogonally polarized broadband dual rectangular spiral antenna configurations for in-band full duplex communications. We found that at the operating frequency 3.2 GHz within a 60 MHz bandwidth, a very high SIC isolation of 45 dB can be achieved. 2) We provide a theoretical framework for the study of massive multiple-input multiple-output (MIMO)-enabled full-duplex (FD) cellular networks in which the residual self-interference (SI) channels follow the Rician distribution for both uplink (UL) and downlink (DL). The results indicate that the UL rate bottleneck in the FD baseline single-input single-output system can be overcome via exploiting massive MIMO. 3) We recently investigate the optimization of uplink (UL) channel state information (CSI) training in the FD based multiuser MIMO systems. Our results show that the performance of the proposed UL training outperforms the fixed length training and the traditional half-duplex training and it closely matches the performance with an exhaustive search. |
| Exploitation Route | 1) The first finding provides a detailed guideline for the choice of the SIC scheme depending on the bandwidth used. 2) The findings from our performance analysis may be viewed as a reality-check, since we show that, under state-of-the-art system parameters, the spectral efficiency gain of FD massive MIMO over its half-duplex counterpart is largely limited by the cross-mode interference between the DL and the UL. The anticipated twofold increase in SE is shown to be only achievable when the number of antennas tends to be infinitely large. 3) We also investigated the benefit of FD in cloud radio access networks (C-RAN). Our results indicate that significant spectral efficiency gains can be achieved compared to the half duplex operation, particularly in the presence of sufficient-capacity fronthaul links and advanced interference cancellation capabilities. |
| Sectors | Digital/Communication/Information Technologies (including Software) |
| Description | AI-enabled Massive MIMO |
| Amount | £950,863 (GBP) |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2020 |
| End | 08/2022 |
| Description | The Leverhulme Trust Research Grant |
| Amount | £199,163 (GBP) |
| Organisation | The Leverhulme Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 03/2018 |
| End | 03/2021 |
| Description | Chaired a Workshop in IEEE SPAWC 2016 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Together with the lead PI, Prof. Wong, we organised a special session in IEEE International Workshop on Signal Processing Advances in Wireless Communications in Edinburgh, 2016. We solicited 5 high-quality submissions from top researchers in the area of full-duplex radios. The special session provided a useful venue to exchange ideas, and attracted a large number of audience who attended the conference. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Giving a Thought Leadership talk at BT |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Industry/Business |
| Results and Impact | I was invited to give a Thought Leadership talk at BT's Adastral Park in July 2023 on deep learning for communications networks, one of the research outcomes from this grant. It attracted about 30 engineers which sparked very interesting discussions on the use of deep learning for optimizing massive MIMO communications systems. This engagement has motivated further collaborative research with BT. |
| Year(s) Of Engagement Activity | 2023 |