Related papers: Harnessing Supervised Learning for Adaptive Beamfo…
Satellite communications face severe bottlenecks in supporting high-fidelity synchronized audiovisual services, as conventional schemes struggle with cross-modal coherence under fluctuating channel conditions, limited bandwidth, and long…
Object detection and classification for aircraft are the most important tasks in the satellite image analysis. The success of modern detection and classification methods has been based on machine learning and deep learning. One of the key…
Recent advancement in next generation reconfigurable antenna and fluid antenna technology has influenced the wireless system with polarization reconfigurable (PR) channels to attract significant attention for promoting beneficial channel…
Millimeter-wave (mmWave) communication is considered as a key enabler of ultra-high data rates in the future cellular and wireless networks. The need for directional communication between base stations (BSs) and users in mmWave systems,…
Reconfigurable intelligent surfaces have emerged as a technology with the potential to enhance wireless communication performance for 5G and beyond. However, the technology comes with challenges in areas such as complexity, power…
In ultrasound (US) imaging, various types of adaptive beamforming techniques have been investigated to improve the resolution and contrast-to-noise ratio of the delay and sum (DAS) beamformers. Unfortunately, the performance of these…
This work investigates the impact of position and attitude perturbations on the beamforming performance of multi-satellite systems. The system under analysis is a formation of small satellites equipped with direct radiating arrays that…
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…
Integrated Sensing and Communications (ISAC) has emerged as a key enabler for sixth generation (6G) wireless systems by jointly supporting data transmission and environmental awareness within a unified framework. However, communication and…
This paper studies fast adaptive beamforming optimization for the signal-to-interference-plus-noise ratio balancing problem in a multiuser multiple-input single-output downlink system. Existing deep learning based approaches to predict…
Deep learning (DL)-based solutions have emerged as promising candidates for beamforming in massive Multiple-Input Multiple-Output (mMIMO) systems. Nevertheless, it remains challenging to seamlessly adapt these solutions to practical…
Benefiting from huge bandwidth resources, millimeter-wave (mmWave) communications provide one of the most promising technologies for next-generation wireless networks. To compensate for the high pathloss of mmWave signals, large-scale…
Satellite-based communications are expected to be a substantial future market in 6G networks. As satellite constellations grow denser and transmission resources remain limited, frequency reuse plays an increasingly important role in…
Millimeter-wave vehicular networks incur enormous beam-training overhead to enable narrow-beam communications. This paper proposes a learning and adaptation framework in which the dynamics of the communication beams are learned and then…
Beamforming has proven to be valuable in enabling full-duplex massive MIMO base stations, but doing so effectively often requires knowledge of the self-interference channel matrix H. Estimating this high-dimensional channel is costly in…
This paper introduces a novel quantum-based method for dynamic beamforming and re-forming in Unmanned Aircraft Systems (UASs), specifically addressing the critical challenges posed by the unavoidable hovering characteristics of UAVs.…
Developing resource allocation algorithms with strong real-time and high efficiency has been an imperative topic in wireless networks. Conventional optimization-based iterative resource allocation algorithms often suffer from slow…
Integrated Sensing and Communication (ISAC) has emerged as a key enabler for future wireless systems. The recently developed symbol-level precoding (SLP) technique holds significant potential for ISAC waveform design, as it leverages both…
Millimeter-wave (mmWave) hybrid analog-digital beamforming is a promising approach to satisfy the low-latency constraint in multiple unmanned aerial vehicles (UAVs) systems, which serve as network infrastructure for flexible deployment.…
This paper studies a multi-target multi-user integrated sensing and communication (ISAC) system where a multi-antenna base station (BS) communicates with multiple single-antenna users in the downlink and senses the unknown and random angle…