Related papers: Bayesian EM Digital Twins Channel Estimation
Channel estimation is one of the most important parts in current mobile communication systems. Among the huge contributions in channel estimation studies, the discrete Fourier transform (DFT)-based channel estimation has attracted lots of…
We develop a broadband channel estimation algorithm for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters (ADCs). Our methodology exploits the joint sparsity of the mmWave MIMO…
This letter proposes decision-directed semi-blind channel estimation for massive multiple-input multiple-output low-Earth-orbit satellite communications. Two semi-blind estimators are proposed. The first utilizes detected data symbols in…
We report a digital twin (DT) framework of electrical tomography (ET) to address the challenge of real-time quantitative multiphase flow imaging based on non-invasive and non-radioactive technologies. Multiphase flow is ubiquitous in…
Accurate channel estimation is critical to fully exploit the beamforming gains when communicating with extremely large aperture arrays. The propagation distances between the user and receiver, which potentially has thousands of…
The recent proposed affine frequency division multiplexing (AFDM) employing a multi-chirp waveform has shown its reliability and robustness in doubly selective fading channels. In the existing embedded pilot-aided channel estimation…
Digital twins are becoming an important tool for designing, developing, testing, and optimizing next-generation wireless communication systems. Over the past decade, system softwarization has become a reality, and wireless communication…
We study distributed similarity estimation of quantum channels (DSEC), a primitive for cross-platform verification where two remote quantum devices are compared by estimating the inner product of their Choi states. We show that the optimal…
We propose super-resolution MIMO channel estimators for millimeter-wave (mmWave) systems that employ hybrid analog and digital beamforming and generalized spatial modulation, respectively. Exploiting the inherent sparsity of mmWave…
This work focuses on optimizing the hybrid quantum noise model to improve the capacity of Gaussian quantum channels using Machine Learning (ML) generated clusters. The work specifically leverages Gaussian Mixture Model (GMM) and the…
In this paper, we propose a novel channel estimation technique based on 2D spread pilots. The merits of this technique are its simplicity, its flexibility regarding the transmission scenarios, and the spectral efficiency gain obtained…
Extremely large antenna arrays and high-frequency operation are two key technologies that advance performance metrics such as higher data rates, lower latency, and wider coverage in sixth-generation communications. However, the adoption of…
Spectral estimation (SE) aims to identify how the energy of a signal (e.g., a time series) is distributed across different frequencies. This can become particularly challenging when only partial and noisy observations of the signal are…
Cluster-sparse channels often exist in frequencyselective fading broadband communication systems. The main reason is received scattered waveform exhibits cluster structure which is caused by a few reflectors near the receiver. Conventional…
Reconfigurable intelligent surface (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems have aroused extensive research interests due to the controllable communication environment and the performance of combating…
With the emergence and proliferation of new forms of large-scale services such as smart homes, virtual reality/augmented reality, the increasingly complex networks are raising concerns about significant operational costs. As a result, the…
A multi-imaging strategy is proposed and experimentally tested to improve the accuracy of photon counting with an electron multiplying charge-coupled device (EMCCD), by taking into account the random nature of its on-chip gain and the…
Error mitigation (EM) methods are crucial for obtaining reliable results in the realm of noisy intermediate-scale quantum (NISQ) computers, where noise significantly impacts output accuracy. Some EM protocols are particularly efficient for…
For frequency division duplex channels, a simple pilot loop-back procedure has been proposed that allows the estimation of the UL & DL channels at an antenna array without relying on any digital signal processing at the terminal side. For…
Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the l1-norm of…