21 research outputs found
Joint Beamforming Design and 3D DoA Estimation for RIS-aided Communication System
In this paper, we consider a reconfigurable intelligent surface
(RIS)-assisted 3D direction-of-arrival (DoA) estimation system, in which a
uniform planar array (UPA) RIS is deployed to provide virtual line-of-sight
(LOS) links and reflect the uplink pilot signal to sensors. To overcome the
mutually coupled problem between the beamforming design at the RIS and DoA
estimation, we explore the separable sparse representation structure and
propose an alternating optimization algorithm. The grid-based DoA estimation is
modeled as a joint-sparse recovery problem considering the grid bias, and the
Joint-2D-OMP method is used to estimate both on-grid and off-grid parts. The
corresponding Cram\'er-Rao lower bound (CRLB) is derived to evaluate the
estimation. Then, the beampattern at the RIS is optimized to maximize the
signal-to-noise (SNR) at sensors according to the estimated angles. Numerical
results show that the proposed alternating optimization algorithm can achieve
lower estimation error compared to benchmarks of random beamforming design.Comment: 6 pages, 6 figure
Optimal Discrete Beamforming of RIS-Aided Wireless Communications: an Inner Product Maximization Approach
This paper addresses non-convex optimization problems in communication
services using reconfigurable intelligent surfaces (RISs). Specifically, we
focus on optimal beamforming in RIS-aided communications, and formulate it as a
discrete inner product maximization problem. To solve this problem, we propose
a highly efficient divide-and-sort (DaS) search framework that guarantees
global optima with linear search complexity, both in the number of discrete
levels and reflecting cells. This approach is particularly effective for
large-scale problems. Our numerical studies and prototype experiments
demonstrate the speed and effectiveness of the proposed DaS. We also show that
for moderate resolution quantization (4-bits and above), there is no noticeable
difference between continuous and discrete phase configurations
Asymptotic CRB Analysis of Random RIS-Assisted Large-Scale Localization Systems
This paper studies the performance of a randomly RIS-assisted multi-target
localization system, in which the configurations of the RIS are randomly set to
avoid high-complexity optimization. We first focus on the scenario where the
number of RIS elements is significantly large, and then obtain the scaling law
of Cram\'er-Rao bound (CRB) under certain conditions, which shows that CRB
decreases in the third or fourth order as the RIS dimension increases. Second,
we extend our analysis to large systems where both the number of targets and
sensors is substantial. Under this setting, we explore two common RIS models:
the constant module model and the discrete amplitude model, and illustrate how
the random RIS configuration impacts the value of CRB. Numerical results
demonstrate that asymptotic formulas provide a good approximation to the exact
CRB in the proposed randomly configured RIS systems
Wireless Regional Imaging through Reconfigurable Intelligent Surfaces: Passive Mode
In this paper, we propose a multi-RIS-aided wireless imaging framework in 3D
facing the distributed placement of multi-sensor networks. The system creates a
randomized reflection pattern by adjusting the RIS phase shift, enabling the
receiver to capture signals within the designated space of interest (SoI).
Firstly, a multi-RIS-aided linear imaging channel modeling is proposed. We
introduce a theoretical framework of computational imaging to recover the
signal strength distribution of the SOI. For the RIS-aided imaging system, the
impact of multiple parameters on the performance of the imaging system is
analyzed. The simulation results verify the correctness of the proposal.
Furthermore, we propose an amplitude-only imaging algorithm for the RIS-aided
imaging system to mitigate the problem of phase unpredictability. Finally, the
performance verification of the imaging algorithm is carried out by proof of
concept experiments under reasonable parameter settings