This article investigates the mean square error (MSE)-optimal conditional mean estimator
(CME) in one-bit quantized systems in the context of channel estimation with jointly …

We consider computationally efficient maximum likelihood (ML) channel estimation for
massive multiple-input multiple-output (MIMO) systems using coarsely quantized …

This letter proposes a dual-driven learning network for channel estimation of massive
multiple-input-multiple-output (MIMO) systems with one-bit analog-to-digital converters …

This paper proposes a novel approach that utilizes differential encoding to overcome the
channel estimation problem in communication systems with low-resolution quantization …

In distributed base station (DBS) systems, the traditional direct position determination (DPD)
methods entail the transmission of raw data to the fusion center (FC), straining transmission …

Using one-bit analog-to-digital converters (ADCs) can drastically reduce the cost and energy
consumption of a wideband large array system. But it brings about challenges to the signal …

We consider the problem of harmonic retrieval from coarsely quantized measurements. We
formulate the sinusoidal parameter estimation problem into a sparse parameter estimation …

In this paper, we propose a learning-based detection framework for uplink massive multiple-
input and multiple-output (MIMO) systems with one-bit analog-to-digital converters. The …

Motivated by the ability of optical intelligent reflective surface (OIRS) to alter optical
channels, the effectiveness of OIRS on aggregated visible light communication (VLC)-radio …

Dynamic channel modelling allows communication interfaces to integrate continuous
learning operations for incremental BER reductions. These models scan temporal BER …