Channel Estimation and Transmission for Intelligent Reflecting Surface Assisted THz Communications

Abstract

Terahertz (THz) communications are promising to be the next frontier for wireless network but suffer from severe attenuation and poor diffraction. To address these challenges, this paper integrates two state-of-the-art technology, i.e., massive multiple input multiple output (MIMO) and reconfigurable intelligent surfaces (RISs), into THz communication to stablish effective and stable connection. Owing to the passivity of the RISs, channel estimation remains an open problem, besides, traditional fully-digital beamforming (FDB) can not be applied in massive MIMO due to its high hardware cost. In sight of this, this paper develops a cooperative channel estimation procedure for RIS-assisted MIMO system via beam training that exploits the advantages of massive MIMO and poor scattering nature of THz channel. The whole procedure is developed based on cost-efficient hybrid beamforming (HB) architectures. Moreover, this paper designs two different codebooks for efficiently realizing the proposed estimation procedure via 3-tree hierarchical search. The two codebooks are referred to as tree dictionary (TD) codebook and phase shifter deactivation (PSD) codebook, with different advantages catering for various scenarios. Using the estimation information, this paper develops two closed-form transmission designs, i.e., direct allocation (DA) design and zero-forcing allocation (ZFA) design, for maximizing the overall spectral efficiency.

Spectral and Energy Efficiency of IRS-Assisted MISO Communication With Hardware Impairments

“…1. Both non-ideal case in (11) and ideal case in (12) increase with the transmit power but by respective scales.…”

Intelligent Reflective Surfaces for Wireless Networks: An Overview of Applications, Approached Issues, and Open Problems

“…In [35], the channel estimation is realized by beam training in NLOS conditions, i.e., there is no direct path between the communication ends. A hierarchical codebook design is provided as the basis of beam training to reduce the estimation complexity in the THz MIMO systems.…”

“…Again, the cascaded BS-IRS-user channel estimation is formulated as a sparse recovery problem. A matching pursuit (MP)-based high-resolution estimation is performed, which outperforms the scheme in [35] in terms of the NMSE. The computational complexity of this algorithm depends on the dictionary matrix which leads to a prohibitive complexity in practical implementations.…”

Tensor-Based Algebraic Channel Estimation for Hybrid IRS-Assisted MIMO-OFDM

“…Compressed sensing (CS) tools were adopted by [17] to exploit the row-column-block sparsity of the cascaded multipath channel. Hierarchical beamforming codebook as well as cooperative search strategies were proposed in [18]. A deep learning framework containing a twin convolutional neural network was applied in [19] to jointly estimate the direct and cascaded channels.…”