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
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.
Organisations
Publications
4. A. Shojaeifard
(2018)
Full-Duplex versus Half-Duplex Large Scale Antenna System
A. Shojaeifard
(2018)
Full-Duplex Enabled Cloud Radio Access Network
Ali B
(2019)
Full-Duplex Amplify-and-Forward Relay Selection in Cooperative Cognitive Radio Networks
in IEEE Transactions on Vehicular Technology
An K
(2018)
On the Secrecy Performance of Land Mobile Satellite Communication Systems
in IEEE Access
Cao H
(2018)
A Novel Optimal Mapping Algorithm With Less Computational Complexity for Virtual Network Embedding
in IEEE Transactions on Network and Service Management
Chalise B
(2017)
Beamforming Optimization for Full-Duplex Wireless-Powered MIMO Systems
in IEEE Transactions on Communications
Chen T
(2020)
Blockchain Secured Auction-Based User Offloading in Heterogeneous Wireless Networks
in IEEE Wireless Communications Letters
Chen T
(2022)
A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks
in IEEE Internet of Things Journal
Chen Y
(2018)
Optimum Placement of UAV as Relays
in IEEE Communications Letters
Cumanan K
(2017)
Physical Layer Security Jamming: Theoretical Limits and Practical Designs in Wireless Networks
in IEEE Access
| 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 | - Thanks to this grant, I was invited by OneWeb, a leading satelite communications provider to offer expert opinions on the feasibility of full-duplex broadband satellites. This is confidential and won't be shared further. - A deep learning based MIMO optimization method resulting from the project's funded outcome "A Deep Learning Framework for Optimization of MISO Downlink Beamforming" published IEEE Transactions on Communications in 2019, was successfully implemented and demonstrated in 2022 in a further project "AI-enabled Massive MIMO" funded by Innovate UK. |
| Sector | Digital/Communication/Information Technologies (including Software) |
| Impact Types | Economic,Policy & public services |
| Description | AI-enabled Massive MIMO |
| Amount | £950,863 (GBP) |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2020 |
| 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 | 04/2018 |
| 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 |