Related papers: Deep learning-based beam alignment in mmWave vehic…
Beamforming in millimeter-wave (mmWave) high-mobility environments typically incurs substantial training overhead. While prior studies suggest that sub-6 GHz channels can be exploited to predict optimal mmWave beams, existing methods depend…
Communication systems at millimeter-wave (mmW) and sub-terahertz frequencies are of increasing interest for future high-data rate networks. One critical challenge faced by phased array systems at these high frequencies is the efficiency of…
Channel knowledge map (CKM) is a novel technique for achieving environment awareness, and thereby improving the communication and sensing performance for wireless systems. A fundamental problem associated with CKM is how to construct a…
Low overhead channel estimation based on compressive sensing (CS) has been widely investigated for hybrid wideband millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. The channel sparsifying dictionaries used in prior…
In millimeter wave (mmWave) communication systems, beamforming with large antenna arrays is critical to overcome high path losses. Separating all-digital beamforming into analog and digital stages can provide the large reduction in power…
Millimeter wave communication systems can leverage information from sensors to reduce the overhead associated with link configuration. LIDAR (light detection and ranging) is one sensor widely used in autonomous driving for high resolution…
Multiple-input multiple-output (MIMO) systems are well suited for millimeter-wave (mmWave) wireless communications where large antenna arrays can be integrated in small form factors due to tiny wavelengths, thereby providing high array…
Position-aided beam selection methods have been shown to be an effective approach to achieve high beamforming gain while limiting the overhead and latency of initial access in millimeter wave (mmWave) communications. Most research in the…
In this paper, we develop a deep learning (DL)-guided hybrid beam and power allocation approach for multiuser millimeter-wave (mmWave) networks, which facilitates swift beamforming at the base station (BS). The following persisting…
The speed at which millimeter-Wave (mmWave) channel estimation can be carried out is critical for the adoption of mmWave technologies. This is particularly crucial because mmWave transceivers are equipped with large antenna arrays to combat…
In the beyond fifth-generation (B5G) and upcoming sixth-generation (6G) wireless communication systems, millimeter (mmWave) wave technology is a promising solution for offering additional bandwidth resources and mitigating spectrum…
Millimeter wave (mmWave) systems will likely employ directional beamforming with large antenna arrays at both the transmitters and receivers. Acquiring channel knowledge to design these beamformers, however, is challenging due to the large…
Millimeter-wave massive multiple-input multiple-output systems employ highly directional beamforming to overcome severe path loss, and their performance critically depends on accurate beam alignment. Conventional codebook-based methods…
Compared to the current wireless communication systems, millimeter wave (mm-Wave) promises a wide range of spectrum. As viable alternatives to existing mm-Wave channel models, various map-based channel models with different modeling methods…
This paper proposes a model-driven deep learning (MDDL)-based channel estimation and feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input multiple-output (MIMO) systems, where the angle-delay domain channels'…
To establish reliable and long-range millimeter-wave (mmWave) communication, beamforming is deemed to be a promising solution. Although beamforming can be done in the digital and analog domains, both approaches are hindered by several…
Millimeter-wave massive MIMO with lens antenna array can considerably reduce the number of required radio-frequency (RF) chains by beam selection. However, beam selection requires the base station to acquire the accurate information of…
Beamforming design for intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the acquisition of accurate channel state information (CSI). However, channel estimation (CE) in IRS-MUC…
Millimeter-wave (mmwave) communication represents a potential solution to capacity shortage in vehicular networks. However, effective beam alignment between senders and receivers requires accurate knowledge of the vehicles' position for…
Compressed Sensing (CS) based channel estimation techniques have recently emerged as an effective way to acquire the channel of millimeter-wave (mmWave) systems with a small number of measurements. These techniques, however, are based on…