Year: 2024
Type: article
Abstract: Stacked intelligent metasurfaces (SIMs) are capable of emulating reconfigurable physical neural networks by utilizing electromagnetic (EM) waves as carriers. They can also perform various complex computational and signal processing tasks. An SIM is constructed by densely integrating multiple metasurface layers, each consisting of a large number of small meta-atoms that can control the EM waves passing through it. In this paper, we harness an SIM for two-dimensional (2D) direction-of-arrival (DOA) estimation. In contrast to conventional designs, an advanced SIM in front of a receiver array can be designed to automatically compute the 2D discrete Fourier transform (DFT) as the incident waves propagate through it. As a result, a receiver array can directly observe the angular spectrum of the incoming signal, and it can estimate the DOA by simply using probes to detect the energy distribution on the receiver array. This avoids the need for power inefficient radio frequency chains. To enable an SIM to perform the 2D DFT in the wave domain, we formulate an optimization problem that minimizes the mean square error (MSE) between the SIM’s EM response and the 2D DFT matrix. Then, a gradient descent algorithm is customized for iteratively updating the phase shift applied by each meta-atom of the SIM. To further improve the DOA estimation accuracy, we configure the phase shifts of the input layer of the SIM to generate a set of 2D DFT matrices associated with orthogonal spatial frequency bins. Additionally, we analytically evaluate the performance of the proposed SIM-based DOA estimator by deriving a tight upper bound for the MSE. Extensive numerical simulations verify the capability of an optimized SIM to perform DOA estimation and corroborate the theoretical analysis. Specifically, we show that an SIM is capable of performing DOA estimation with an MSE of the order of$10^{-4}$.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, Università degli Studi di Teramo, European Commission, National Research Foundation, National Research Foundation Singapore, Ministry of Education - Singapore, Agence Nationale de la Recherche, Ministry of Education, India, Info-communications Media Development Authority, HORIZON EUROPE Framework Programme, Engineering and Physical Sciences Research Council, Division of Electrical, Communications and Cyber Systems, H2020 European Research Council, CHIST-ERA
Awards: UKRI-India Future Networks Initiative, G1190173965, G1463304763, Platform Driving The Ultimate Connectivity, G1617124451, ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond, Joint Sensing and Communications for Future Interactive, Immersive, and Intelligent Connectivity Beyond Communications, Beyond 5G mmWave Circuits, Antennas and RIS, Pervasive Wireless Intelligence Beyond the Generations (PerCom), G2544329817, G2559059231, Reliable and Robust Quantum Computing, G2987309065, Physics-based wireless AI providing scalability and efficiency, G3480082138, TITAN Extension, Collaborative Research: SWIFT: Nonlinear and Inseparable Radar And Data (NIRAD) Transmission Framework for Pareto Efficient Spectrum Access in Future Wireless Networks, G4162724171, G4384862669, Pervasive Wireless Intelligence Beyond the Generations, Ubiquitous Quantum Communications, G5532616604, G6495392424, G6683820337, G6854926366, G7222178585, G8921317170
OpenAlex ID: W4399666068