Related papers: Dynamic Channel Knowledge Map Construction in MIMO…
This paper addresses channel estimation and data equalization on frequency-selective 1-bit quantized Multiple Input-Multiple Output (MIMO) systems. No joint processing or Channel State Information is assumed at the transmitter, and…
Massive MIMO communication systems, by virtue of utilizing very large number of antennas, have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. In this paper, we consider uplink…
In this paper, we investigate channel estimation techniques for 5G multicarrier systems. Due to the characteristics of the 5G application scenarios, channel estimation techniques have been tested in Orthogonal Frequency Division…
Diffusion model (DM)-based channel estimation, which generates channel samples via a posteriori sampling stepwise with denoising process, has shown potential in high-precision channel state information (CSI) acquisition. However, slow…
Accurate localization in non-line-of-sight (NLoS) environments remains challenging even with both angle-of-arrival (AoA) and time-of-arrival (ToA) measurements. In complex urban scenarios, the absence of line-of-sight (LoS) paths and the…
Accurate and efficient acquisition of wireless channel state information (CSI) is crucial to enhance the communication performance of wireless systems. However, with the continuous densification of wireless links, increased channel…
Multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems rely on digital or hybrid digital and analog designs for beamforming against frequency-selective fading, which suffer from high hardware…
This paper investigates robust semantic communications over multiple-input multiple-output (MIMO) fading channels. Current semantic communications over MIMO channels mainly focus on channel adaptive encoding and decoding, which lacks…
In the future sixth-generation (6G) era, to support accurate localization sensing and efficient communication link establishment for intelligent agents, a comprehensive understanding of the surrounding environment and proper channel…
Channel knowledge maps (CKMs) learn the relation between transmitter (Tx) and receiver (Rx) positions and channel knowledge to support environment-aware wireless communications. Implicit neural methods can model continuous channel variation…
This paper investigates the construction of channel knowledge map (CKM) from sparse channel measurements. Dif ferent from conventional two-/three-dimensional (2D/3D) CKM approaches assuming fixed base station configurations, we present a…
The rapid development of low-altitude economy has placed higher demands on the sensing of small-sized unmanned aerial vehicle (UAV) targets. However, the complex and dynamic low-altitude environment, like the urban and mountainous areas,…
In this work, we address the problem of estimating sparse communication channels in OFDM systems in the presence of carrier frequency offset (CFO) and unknown noise variance. To this end, we consider a convex optimization problem, including…
The acquisition of the channel covariance matrix is of paramount importance to many strategies in multiple-input-multiple-output (MIMO) communications, such as the minimum mean-square error (MMSE) channel estimation. Therefore, plenty of…
Accurate channel state information (CSI) acquisition for massive multiple-input multiple-output (MIMO) systems is essential for future mobile communication networks. Channel fingerprint (CF), also referred to as channel knowledge map, is a…
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…
Accurate channel estimation is essential for achieving the performance gains offered by reconfigurable intelligent surface (RIS)-aided wireless communications. A variety of channel estimation methods have been proposed for such systems;…
In this paper, we propose a learning-based block-wise planar channel estimator (LBPCE) with high accuracy and low complexity to estimate the time-varying frequency-selective channel of a multiple-input multiple-output (MIMO) orthogonal…
We consider channel estimation specific to turbo equalization for multiple-input multiple-output (MIMO) wireless communication. We develop a soft-decision-driven sequential algorithm geared to the pipelined turbo equalizer architecture…
Forecasting faithful trajectories of multivariate time series from practical scopes is essential for reasonable decision-making. Recent methods majorly tailor generative conditional diffusion models to estimate the target temporal…