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Found 18 papers, 1 papers with code
Parametric Channel Estimation for RIS-Assisted Wideband Systems
In this paper, we develop a novel parametric ML channel estimator for RIS-assisted wideband systems, which can handle line-of-sight (LOS) paths in the base station (BS)-RIS and RIS-UE links as well as NLOS paths between the UE, BS, and RIS.
Achieving Beamfocusing via Two Separated Uniform Linear Arrays
This paper investigates coordinated beamforming using a modular linear array (MLA), composed of a pair of physically separated uniform linear arrays (ULAs), treated as sub-arrays.
Approaching Maximum Likelihood Performance via End-to-End Learning in MU-MIMO Systems
Multi-user multiple-input multiple-output (MU-MIMO) systems allow multiple users to share the same wireless spectrum.
An Efficient Modified MUSIC Algorithm for RIS-Assisted Near-Field Localization
In this paper, we consider a single-anchor localization system assisted by a reconfigurable intelligent surface (RIS), where the objective is to localize multiple user equipments (UEs) placed in the radiative near-field region of the RIS by estimating their azimuth angle-of-arrival (AoA), elevation AoA, and distance to the surface.
Symbol-Level Precoding for Near-Field ISAC
The forthcoming 6G and beyond wireless networks are anticipated to introduce new groundbreaking applications, such as Integrated Sensing and Communications (ISAC), potentially leveraging much wider bandwidths at higher frequencies and using significantly larger antenna arrays at base stations.
The Roles of Spatial Frequencies and Degrees-of-Freedom in Near-Field Communications
As wireless technology begins to utilize physically larger arrays and/or higher frequencies, the transmitter and receiver will reside in each other's radiative near field.
Spatial Correlation Modeling and RS-LS Estimation of Near-Field Channels with Uniform Planar Arrays
It is based on prior knowledge of the three-dimensional coverage region where scattering clusters exists and we derive a tractable one-dimensional integral expression.
Accurate Direct Positioning in Distributed MIMO Using Delay-Doppler Channel Measurements
Distributed multiple-input multiple-output (D-MIMO) is a promising technology for simultaneous communication and positioning.
Parametric Near-Field Channel Estimation for Extremely Large Aperture Arrays
Accurate channel estimation is critical to fully exploit the beamforming gains when communicating with extremely large aperture arrays.
Nonlinear Distortion Radiated from Large Arrays and Active Reconfigurable Intelligent Surfaces
In this paper, we study the distortion created by nonlinear amplifiers in both ELAAs and active RIS.
Optimal Dual-Polarized Planar Arrays for Massive Capacity Over Point-to-Point MIMO Channels
We optimize the rank and condition number by identifying the optimal antenna spacing in dual-polarized planar antenna arrays with imperfect isolation.
Exploiting the Depth and Angular Domains for Massive Near-Field Spatial Multiplexing
This article presents the foundational properties of communication in the radiative near-field region and then exemplifies how these properties enable two unprecedented spatial multiplexing schemes: depth-domain multiplexing of multiple users and angular multiplexing of data streams to a single user.
Finite Beam Depth Analysis for Large Arrays
Furthermore, it is sufficient to characterize the BD for a broadside transmitter, as the beam pattern with a non-broadside transmitter can be approximated by that of a smaller/projected array with a broadside transmitter.
Untrained Neural Network based Bayesian Detector for OTFS Modulation Systems
In this paper, we propose an untrained DNN based on the deep image prior (DIP) and decoder architecture, referred to as D-DIP that replaces the MMSE denoiser in the iterative detector.
Bayesian Neural Network Detector for an Orthogonal Time Frequency Space Modulation
The orthogonal time-frequency space (OTFS) modulation is proposed for beyond 5G wireless systems to deal with high mobility communications.
Graph Neural Network Aided MU-MIMO Detectors
Multi-user multiple-input multiple-output (MU-MIMO) systems can be used to meet high throughput requirements of 5G and beyond networks.
Bayesian-based Symbol Detector for Orthogonal Time Frequency Space Modulation Systems
Our simulation results show that in contrast to the state-of-the-art OTFS detectors, the proposed detector is able to achieve a BER of less than $10^{-5}$, when SNR is over $14$ dB, under high ICI environments.
Improving Cell-Free Massive MIMO Detection Performance via Expectation Propagation
The simulation results show that the proposed detector achieves significant improvements in terms of the bit-error rate and sum spectral efficiency performances as compared to the ones of the state-of-the-art CF detectors.
