Summary
In this project, we aim to develop and experimentally demonstrate terahertz (THz) communication technologies for the sixth generation (6G) of wireless networks. In particular, we will integrate ultra-massive multiple-input-multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) technologies into THz systems and apply directional beamforming to establish reliable, long-distance, and ultra-fast THz communication links. To realize channel training for directional beamforming, we will design hierarchical multi-resolution codebooks and find the optimal phase-shift matrix for the IRS. Since the presence of the IRS complicates the original one-hop communication topology into a two-hop topology and user equipments (UEs) are usually moving, to reduce the channel training overhead and maintain high-quality links, we will study beam management (BM) problems, including adaptive beam alignment and beam tracking. Besides channel training, we will also design joint resource allocation algorithms to fully reap the potentials of the THz networks and support the diverse needs of UEs. To assess the performance of the proposed schemes in a real-world environment, we will also develop an easy-to-use software-defined IRS-assisted THz testbed for experimental demonstration. With seven years of research experience, Dr. Xu has developed a wide range of research expertise in massive MIMO, millimeter-wave networks, IRS-assisted communications in sub-6GHz systems, machine learning, etc. The implementation of this project will not only further extend his research field into IRS-assisted UM-MIMO THz communications, but will also significantly improve his project management and leadership skills.
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| Web resources: | https://cordis.europa.eu/project/id/101024636 |
| Start date: | 01-12-2021 |
| End date: | 30-11-2023 |
| Total budget - Public funding: | 212 933,76 Euro - 212 933,00 Euro |
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Original description
In this project, we aim to develop and experimentally demonstrate terahertz (THz) communication technologies for the sixth generation (6G) of wireless networks. In particular, we will integrate ultra-massive multiple-input-multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) technologies into THz systems and apply directional beamforming to establish reliable, long-distance, and ultra-fast THz communication links. To realize channel training for directional beamforming, we will design hierarchical multi-resolution codebooks and find the optimal phase-shift matrix for the IRS. Since the presence of the IRS complicates the original one-hop communication topology into a two-hop topology and user equipments (UEs) are usually moving, to reduce the channel training overhead and maintain high-quality links, we will study beam management (BM) problems, including adaptive beam alignment and beam tracking. Besides channel training, we will also design joint resource allocation algorithms to fully reap the potentials of the THz networks and support the diverse needs of UEs. To assess the performance of the proposed schemes in a real-world environment, we will also develop an easy-to-use software-defined IRS-assisted THz testbed for experimental demonstration. With seven years of research experience, Dr. Xu has developed a wide range of research expertise in massive MIMO, millimeter-wave networks, IRS-assisted communications in sub-6GHz systems, machine learning, etc. The implementation of this project will not only further extend his research field into IRS-assisted UM-MIMO THz communications, but will also significantly improve his project management and leadership skills.Status
SIGNEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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