  This paper proposes a joint active and passive beamforming design for
reconfigurable intelligent surface (RIS)-aided wireless communication systems,
adopting a piece-wise near-field channel model. While a traditional near-field
channel model, applied without any approximations, offers higher modeling
accuracy than a far-field model, it renders the system design more sensitive to
channel estimation errors (CEEs). As a remedy, we propose to adopt a piece-wise
near-field channel model that leverages the advantages of the near-field
approach while enhancing its robustness against CEEs. Our study analyzes the
impact of different channel models, including the traditional near-field, the
proposed piece-wise near-field and far-field channel models, on the
interference distribution caused by CEEs and model mismatches. Subsequently, by
treating the interference as noise, we formulate a joint active and passive
beamforming design problem to maximize the spectral efficiency (SE). The
formulated problem is then recast as a mean squared error (MSE) minimization
problem and a suboptimal algorithm is developed to iteratively update the
active and passive beamforming strategies. Simulation results demonstrate that
adopting the piece-wise near-field channel model leads to an improved SE
compared to both the near-field and far-field models in the presence of CEEs.
Furthermore, the proposed piece-wise near-field model achieves a good trade-off
between modeling accuracy and system's degrees of freedom (DoF).
