Terahertz Multi-User Massive MIMO with Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming

Abstract

Terahertz (THz) communications open a new frontier for the wireless network thanks to their dramatically wider available bandwidth compared to the current micro-wave and forthcoming millimeter-wave communications. However, due to the short length of THz waves, they also suffer from severe path attenuation and poor diffraction. To compensate the THz-induced propagation loss, this paper proposes to combine two promising techniques, viz., massive multiple input multiple output (MIMO) and intelligent reflecting surface (IRS), in THz multi-user communications, considering their significant beamforming and aperture gains. Nonetheless, channel estimation and low-cost beamforming turn out to be two main obstacles to realizing this combination, due to the passivity of IRS for sending/receiving pilot signals and the large-scale use of expensive RF chains in massive MIMO. In view of these limitations, this paper first develops a cooperative beam training scheme to facilitate the channel estimation with IRS. In particular, we design two different hierarchical codebooks for the proposed training procedure, which are able to balance between the robustness against noise and searching complexity. Based on the training results, we further propose two cost-efficient hybrid beamforming (HB) designs for both single-user and multi-user scenarios, respectively. Simulation results demonstrate that the proposed joint beam training and HB scheme is able to achieve close performance to the optimal fully digital beamforming (FDB) which is implemented even under perfect channel state information (CSI).

References in corpus (14)

• Massive MIMO for Next Generation Wireless Systems
• Spatially Sparse Precoding in Millimeter Wave MIMO Systems
• Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
• Wireless Communications with Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement
• Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems
• Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays
• Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems
• Wireless Communications with Programmable Metasurface: New Paradigms, Opportunities, and Challenges on Transceiver Design
• Intelligent Reflecting Surface Assisted Multi-User OFDMA: Channel Estimation and Training Design
• Secure Wireless Communication via Intelligent Reflecting Surface
• Compressed Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed?
• Weighted Sum-Rate Optimization for Intelligent Reflecting Surface Enhanced Wireless Networks
• Millimeter Wave Beam Alignment: Large Deviations Analysis and Design Insights
• Achievable Rate maximization by Passive Intelligent Mirrors

Cited by in corpus (4)

• Joint Transceiver and Large Intelligent Surface Design for Massive MIMO MmWave Systems
• Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial
• Robust Design for Intelligent Reflecting Surface Assisted MIMO-OFDMA Terahertz Communications
• Intelligent Reflecting Surface Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design