27 research outputs found
Hybrid Digital-Wave Domain Channel Estimator for Stacked Intelligent Metasurface Enabled Multi-User MISO Systems
Stacked intelligent metasurface (SIM) is an emerging programmable metasurface
architecture that can implement signal processing directly in the
electromagnetic wave domain, thereby enabling efficient implementation of
ultra-massive multiple-input multiple-output (MIMO) transceivers with a limited
number of radio frequency (RF) chains. Channel estimation (CE) is challenging
for SIM-enabled communication systems due to the multi-layer architecture of
SIM, and because we need to estimate large dimensional channels between the SIM
and users with a limited number of RF chains. To efficiently solve this
problem, we develop a novel hybrid digital-wave domain channel estimator, in
which the received training symbols are first processed in the wave domain
within the SIM layers, and then processed in the digital domain. The wave
domain channel estimator, parametrized by the phase shifts applied by the
meta-atoms in all layers, is optimized to minimize the mean squared error (MSE)
using a gradient descent algorithm, within which the digital part is optimally
updated. For an SIM-enabled multi-user system equipped with 4 RF chains and a
6-layer SIM with 64 meta-atoms each, the proposed estimator yields an MSE that
is very close to that achieved by fully digital CE in a massive MIMO system
employing 64 RF chains. This high CE accuracy is achieved at the cost of a
training overhead that can be reduced by exploiting the potential low rank of
channel correlation matrices
A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums
Previous studies have confirmed the adverse impact of fading correlation on
the mutual information (MI) of two-dimensional (2D) multiple-input
multiple-output (MIMO) systems. More recently, the trend is to enhance the
system performance by exploiting the channel's degrees of freedom in the
elevation, which necessitates the derivation and characterization of
three-dimensional (3D) channels in the presence of spatial correlation. In this
paper, an exact closed-form expression for the Spatial Correlation Function
(SCF) is derived for 3D MIMO channels. This novel SCF is developed for a
uniform linear array of antennas with nonisotropic antenna patterns. The
proposed method resorts to the spherical harmonic expansion (SHE) of plane
waves and the trigonometric expansion of Legendre and associated Legendre
polynomials. The resulting expression depends on the underlying arbitrary
angular distributions and antenna patterns through the Fourier Series (FS)
coefficients of power azimuth and elevation spectrums. The novelty of the
proposed method lies in the SCF being valid for any 3D propagation environment.
The developed SCF determines the covariance matrices at the transmitter and the
receiver that form the Kronecker channel model. In order to quantify the
effects of correlation on the system performance, the information-theoretic
deterministic equivalents of the MI for the Kronecker model are utilized in
both mono-user and multi-user cases. Numerical results validate the proposed
analytical expressions and elucidate the dependence of the system performance
on azimuth and elevation angular spreads and antenna patterns. Some useful
insights into the behaviour of MI as a function of downtilt angles are
provided. The derived model will help evaluate the performance of correlated 3D
MIMO channels in the future.Comment: Accepted in IEEE Transactions on signal processin