Massive MIMO wireless networks: Theory and methods
Lead Research Organisation:
Queen Mary University of London
Department Name: Sch of Electronic Eng & Computer Science
Abstract
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Publications
Akbar S
(2017)
Massive Multiuser MIMO in Heterogeneous Cellular Networks With Full Duplex Small Cells
in IEEE Transactions on Communications
Al-Kadri M
(2017)
Full-Duplex Small Cells for Next Generation Heterogeneous Cellular Networks: A Case Study of Outage and Rate Coverage Analysis
in IEEE Access
Fan D
(2017)
Angle Domain Signal Processing-Aided Channel Estimation for Indoor 60-GHz TDD/FDD Massive MIMO Systems
in IEEE Journal on Selected Areas in Communications
Fan D
(2018)
Angle Domain Channel Estimation in Hybrid Millimeter Wave Massive MIMO Systems
in IEEE Transactions on Wireless Communications
He S
(2019)
Two-Level Transmission Scheme for Cache-Enabled Fog Radio Access Networks
in IEEE Transactions on Communications
Huang W
(2019)
Joint Power, Altitude, Location and Bandwidth Optimization for UAV With Underlaid D2D Communications
in IEEE Wireless Communications Letters
Jiang N
(2018)
Random Access Analysis for Massive IoT Networks Under a New Spatio-Temporal Model: A Stochastic Geometry Approach
in IEEE Transactions on Communications
Jiang N
(2018)
Analyzing Random Access Collisions in Massive IoT Networks
in IEEE Transactions on Wireless Communications
Ma J
(2017)
Pattern Division for Massive MIMO Networks With Two-Stage Precoding
in IEEE Communications Letters
Pan C
(2019)
Robust Beamforming Design for Ultra-Dense User-Centric C-RAN in the Face of Realistic Pilot Contamination and Limited Feedback
in IEEE Transactions on Wireless Communications
| Description | We developed a novel direction of arrival (DOA)-aided channel estimation for hybrid millimeter wave (mmWave) massive MIMO system with the uniform planar array (UPA) at base station (BS). To explore the physical characteristics of antenna array in mmWave systems, the parameters of each channel path are decomposed into the DOA information and the channel gain information. We first estimate the initial DOAs of each uplink path through the two dimensional discrete Fourier transform (2D-DFT), and enhance the estimation accuracy via the angle rotation technique. We then estimate the channel gain information using small amount of training resources, which significantly reduces the training overhead and the feedback cost. As millimeter wave massive MIMO is a potential candidate for 5G and beyond, these developed channel estimation schemes are highly useful for the future wireless communications. |
| Exploitation Route | We planned to organize a workshop to disseminate the results to industries. Also, we are in the process of extending this wave from millimeter frequency band to THz communications. |
| Sectors | Digital/Communication/Information Technologies (including Software) |
| Description | Millimeter Wave Massive-MIMO is one of the main technologies for the capacity enhancement in ''5G and beyond'' cellular networks. Our findings in this project have been disseminated in numerous top IEEE journals and IEEE Flagship conferences and attracted the interest of non-academic industries. More specifically, we developed a novel direction of arrival (DOA)-aided channel estimation for hybrid millimeter wave (mmWave) massive MIMO system with the uniform planar array (UPA) at base station (BS). To explore the physical characteristics of antenna array in mmWave systems, the parameters of each channel path are decomposed into the DOA information and the channel gain information. We first estimate the initial DOAs of each uplink path through the two dimensional discrete Fourier transform (2D-DFT), and enhance the estimation accuracy via the angle rotation technique. We then estimate the channel gain information using small amount of training resources, which significantly reduces the training overhead and the feedback cost. Industries are now exploring millimeter wave band of 30-300 GHz for 6G. Hence, our findings of channel estimation in Millimeter Wave Massive MIMO system are highly useful and made non-academic industrial impact in the development of next generation 6G cellular networks. |
| First Year Of Impact | 2018 |
| Sector | Digital/Communication/Information Technologies (including Software) |
| Impact Types | Economic |