Active Computing & AI Physics & Astronomy

Synergizing Artificial Intelligence with XL-MIMO for Terahertz Communication and Sensing

Summary

Original abstract (not yet simplified)

Terahertz (THz) communication is an up-and-coming candidate technology for 6G, aiming to meet the stringent performance requirements of next-generation communications, such as hyper rates on the order of terabits-per-second. However, a notable challenge in THz communications is the increased path losses. Fortunately, extremely large-scale multiple-input multiple-output (XL-MIMO) technology can effectively compensate for this issue. The combined implementation of THz and...

View original technical description
Terahertz (THz) communication is an up-and-coming candidate technology for 6G, aiming to meet the stringent performance requirements of next-generation communications, such as hyper rates on the order of terabits-per-second. However, a notable challenge in THz communications is the increased path losses. Fortunately, extremely large-scale multiple-input multiple-output (XL-MIMO) technology can effectively compensate for this issue. The combined implementation of THz and XL-MIMO, offering extensive spatial degrees of freedom and ultra-wideband capabilities, has emerged as a crucial technology for high-precision target sensing and high-throughput communications, effectively meeting the needs of integrated sensing and communication (ISAC). However, the large antenna aperture of XL-MIMO will make near-field communications dominant. On the other hand, the ultra-wideband nature of THz signals will introduce the beam-split effect. There is an urgent need to consider these unique characteristics to synergize artificial intelligence (AI) with XL-MIMO for developing THz communication and sensing.This proposal aims to design AI-native XL-MIMO THz communication by developing novel techniques: 1) Intelligent THz XL-MIMO Communication Design. Developing low-complexity, learning-aided channel estimation methods for XL-MIMO communication systems while studying intelligent precoding to manage hybrid field interference for mixed near-field and far-field communication users. 2) Hybrid-Field THz XL-MIMO ISAC Design. Developing ISAC precoder for target sensing and electromagnetic property sensing, while developing a network-level ISAC performance analysis framework. 3) Practical implementation of Intelligent THz XL-MIMO ISAC. Developing resilient AI-native XL-MIMO ISAC using generative diffusion model and intelligent XL-MIMO ISAC testbed. The main research approaches include electromagnetic wave theory, nonlinear optimization, and reinforcement learning, etc.

Related Research

Grants with similar aims, by meaning.

TRANSPOSE - Thz tRANsceiver deSign enables by nonreciPrOcal magnetleSs componEnts for 6G communication
Intelligent Reflecting Surface (IRS) Assisted Ultra-massive MIMO THz Communications for 6G
New Air Interface Techniques for Future Massive Machine Communications
Massive MIMO wireless networks: Theory and methods
Wireless Networks at Optical Speed with Deterministic Performance

Original classification

HORIZON

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.