  The number of connected mobile devices and the amount of data traffic through
these devices are expected to grow many-fold in future communication networks.
To support the scale of this huge data traffic, more and more base stations and
wireless terminals are required to be deployed in existing networks.
Nevertheless, practically deploying a large number of base stations having
massive antenna arrays will substantially increase the hardware cost and power
consumption of the network. A promising approach for enhancing the coverage and
rate of wireless communication systems is the large intelligent surface-based
transceiver (LISBT), which uses a spatially continuous surface for signal
transmission and receiving. A typical LIS consists of a planar array having a
large number of reflecting metamaterial elements (e.g., low-cost printed
dipoles), each of which could act as a phase shift. It is also considered to be
a cost effective and energy efficient solution. Accurate channel state
information (CSI) in LISBT-assisted wireless communication systems is critical
for achieving these goals. In this paper, we propose a channel estimation
scheme based on the physical parameters of the system. that requires only five
pilot signals to perfectly estimate the channel parameters assuming there is no
noise at the receiver. In the presence of noise, we propose an iterative
estimation algorithm that decreases the channel estimation error due to noise.
The proposed scheme's training overhead and computational cost do not grow with
the number of antennas, unlike previous work on enormous multiple-input
multiple-output (MIMO). The channel estimate scheme based on the physical
properties of the Large intelligent surface-based transceiver (LISBT)-assisted
wireless communication systems is the subject of our future study.
