  Intelligent reflecting surface (IRS) is envisioned as a promising technology
to broaden signal coverage and enhance transmission in terahertz (THz)
communications. Due to the passivity of IRS, the channel measurement can not be
achieved by traditional pilot manner and the subsequent cooperative
transmission design remains an open problem. This paper investigates the
channel estimation and transmission solutions for massive multiple input
multiple output (MIMO) IRS-assisted THz system. The channel estimation is
realized by beam training and the quantization error is analyzed for evaluating
performance. In addition, a novel hierarchical search codebook design is
proposed as a low-complexity basis of beam training. Based on above
foundations, we propose a cooperative channel estimation procedure to tactfully
acquire the channel knowledge. Finally, by leveraging obtained channel
information, the designs of IRS and transceivers are directly provided in
closed form without reconstructing the full channel matrix or additional
optimization. Simulation and numerical results are presented to illustrate the
minimum signal to noise ratio (SNR) required for beam training and the efficacy
of the proposed transmission solutions.
