相关论文: Reliable long timescale decision-directed channel …

Low-dose CT (LDCT) denoising remains an important yet challenging problem in medical imaging. Although recent learning-based methods have shown promising performance, those optimized using classical pixel-level objectives often produce…

This paper investigates channel estimation for linear time-varying (LTV) wireless channels under double sparsity, i.e., sparsity in both the delay and Doppler domains. An on-grid approximation is first considered, enabling rigorous…

Deep learning has been extensively used in wireless communication problems, including channel estimation. Although several data-driven approaches exist, a fair and realistic comparison between them is difficult due to inconsistencies in the…

In recent years, orthogonal chirp-division multiplexing (OCDM) has been increasingly considered as an alternative multicarrier scheme, e.g., to orthogonal frequency-division multiplexing, in digital communication applications. Among reasons…

Deep generative models offer a powerful alternative to conventional channel estimation by learning complex channel distributions. By integrating the rich environmental information available in modern sensing-aided networks, this paper…

We present a unified receiver processing framework for communication over delay-scale (DS)-spread channels that arise in underwater acoustic (UWA) communications that addresses both channel estimation (CE) and data detection for different…

In this paper, we propose an iterative receiver based on gridless variational Bayesian line spectra estimation (VALSE) named JCCD-VALSE that \emph{j}ointly estimates the \emph{c}arrier frequency offset (CFO), the \emph{c}hannel with high…

The recent proposed orthogonal time frequency space (OTFS) modulation shows signifcant advantages than conventional orthogonal frequency division multiplexing (OFDM) for high mobility wireless communications. However, a challenging problem…

In time-varying fading channels, channel coefficients are estimated using pilot symbols that are transmitted every coherence interval. For channels with high Doppler spread, the rapid channel variations over time will require considerable…

In this paper, we propose a low-complexity channel estimation scheme of affine frequency division multiplexing (AFDM) based on generalized complex exponential basis expansion model (GCE-BEM) over doubly selective channels. The GCE-BEM is…

In low latency applications and in general, for overspread channels, channel delay spread is a large percentage of the transmission frame duration. In this paper, we consider OTFS in an overspread channel exhibiting a delay spread that…

This paper proposes a deep learning-based channel estimation method for multi-cell interference-limited massive MIMO systems, in which base stations equipped with a large number of antennas serve multiple single-antenna users. The proposed…

A perturbation-based nonlinear compensation scheme assisted by a feedback from the forward error correction (FEC) decoder is numerically and experimentally investigated. It is shown by numerical simulations and transmission experiments that…

In this paper, we propose an enhancement of a blind channel estimator based on a subspace approach in a MIMO OFDM context (Multi Input Multi Output Orthogonal Frequency Division Multiplexing) in high mobility scenario. As known, the…

This paper proposes an off-grid channel estimation scheme for orthogonal time-frequency space (OTFS) systems adopting the sparse Bayesian learning (SBL) framework. To avoid channel spreading caused by the fractional delay and Doppler shifts…

In this work, we discuss techniques for coherently detecting turbo coded orthogonal frequency division multiplexed (OFDM) signals, transmitted through frequency selective Rayleigh (the magnitude of each channel tap is Rayleigh distributed)…

Receivers with joint channel estimation and signal detection using superimposed pilots (SP) can achieve high transmission efficiency in orthogonal time frequency space (OTFS) systems. However, existing receivers have high computational…

In this work, a new Bayesian framework for OFDM channel estimation is proposed. Using Jaynes' maximum entropy principle to derive prior information, we successively tackle the situations when only the channel delay spread is a priori known,…

Communication systems are usually designed by assuming perfect channel state information (CSI). However, in many practical scenarios, only a noisy estimate of the channel is available, which may strongly differ from the true channel. This…

Due to its time-varying nature, oscillator phase noise can significantly degrade the performance of channel estimation, carrier recovery, and data detection blocks in high-speed wireless communication systems. In this paper, we analyze…