  Active reconfigurable intelligent surface (ARIS) is a newly emerging RIS
technique that leverages radio frequency (RF) reflection amplifiers to empower
phase-configurable reflection elements (REs) in amplifying the incident signal.
Thereby, ARIS can enhance wireless communications with the strengthened
ARIS-aided links. In this letter, we propose exploiting the signal
amplification capability of ARIS for channel estimation, aiming to improve the
estimation precision. Nevertheless, the signal amplification inevitably
introduces the thermal noise at the ARIS, which can hinder the acquisition of
accurate channel state information (CSI) with conventional channel estimation
methods based on passive RIS (PRIS). To address this issue, we further
investigate this ARIS-specific channel estimation problem and propose a
least-square (LS) based channel estimator, whose performance can be further
improved with the design on ARIS reflection patterns at the channel training
phase. Based on the proposed LS channel estimator, we optimize the training
reflection patterns to minimize the channel estimation error variance.
Extensive simulation results show that our proposed design can achieve accurate
channel estimation in the presence of the ARIS noises.
