Radar sensing will be integrated into the 6G communication system to support various
applications. In this integrated sensing and communication system, a radar target may also …

In this paper, we propose an online training framework for mmWave Massive MIMO channel
estimation (CE) with limited pilots, where the training is based on real-time received pilot …

Recently, compressive sensing based massive multiple input multiple output (MIMO)
channel estimation (CE) has attracted intensive research interest. By exploiting the …

In this paper, we propose a federated online training framework for deep neural network
(DNN)-based channel estimation (CE) in frequency-division duplexing (FDD) multi-user …

This paper analyzes the impact of non-Gaussian multipath component (MPC) amplitude
distributions on the performance of Compressed Sensing (CS) channel estimators for OFDM …

We propose a Bayesian deep learning framework for model driven online sparse channel
estimation task in Multi-user MIMO systems. Tools from Bayesian neural network and …

In practice, visible light signals undergo non-line-of-sight (NLOS) propagation, and in visible
light-based positioning (VLP) methods, the NLOS links are usually treated as disturbance …

In this letter, we reveal that in the massive multiple-input multiple-output system with large
bandwidth, sub-channels of orthogonal frequency division multiplexing share approximately …

Pilot and channel state information (CSI) feedback overhead in the downlink and uplink
paths are two major implementation challenges in frequency-division duplex (FDD) based …

Wireless communication channels are highly prone to interference in addition to the
presence of additive white Gaussian noise (AWGN). Stochastic gradient (SG)-based non …