  Terahertz (THz) communication signals are susceptible to severe degradation
because of the molecular interaction with the atmosphere in the form of
subsequent absorption and re-radiation. Recently, reconfigurable intelligent
surface (RIS) has emerged as a potential technology to assist in THz
communications by boosting signal power or providing virtual line-of-sight
paths. However, the re-radiated energy has either been modeled as a
non-line-of-sight scattering component or as additive Gaussian noise in the
literature. Since the precise characterization is still a work in progress,
this paper presents the first comparative investigation of the performance of
an RIS-aided THz system under these two extreme re-radiation models. In
particular, we first develop a novel parametric channel model that encompasses
both models of the re-radiation through a simple parameter change, and then
utilize that to design a robust block-coordinate descent (BCD) algorithmic
framework which maximizes a lower bound on channel capacity considering
imperfect channel state information. In this framework, the original problem is
split into two sub-problems: a) receive beamformer optimization, and b) RIS
phase-shift optimization. We also analytically demonstrate the limited
interference suppression capability of a passive RIS. Our numerical results
also demonstrate that slightly better throughput is achieved when the
re-radiation manifests as scattering.
