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


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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