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Recently, intelligent reflecting surface (IRS) assisted mmWave networks are emerging, which bear the potential to address the blockage issue of the millimeter wave (mmWave) communication in a more cost-effective way. In particular, IRS is…
Hybrid beamforming (HB) has emerged as a promising technology to support ultra high transmission capacity and with low complexity for Millimeter Wave (mmWave) multiple-input and multiple-output (MIMO) system. However, the design of digital…
In an aerial hybrid massive multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) system, how to design a spectral-efficient broadband multi-user hybrid beamforming with a limited pilot and feedback…
This paper focuses on multiuser MIMO channel estimation and data transmission at millimeter wave (mmWave) frequencies. The proposed approach relies on the time-division-duplex (TDD) protocol and is based on two distinct phases. First of…
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…
Inspired by the remarkable learning and prediction performance of deep neural networks (DNNs), we apply one special type of DNN framework, known as model-driven deep unfolding neural network, to reconfigurable intelligent surface…
The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well as improved reliability in voice calls. Jointly optimizing beamforming, power control, and interference coordination…
Resource allocation in integrated sensing and communication (ISAC) systems needs to be optimized to balance the requirements of the communication and sensing modules considering complicated cross-layer data traffic and queue status in…
In millimeter wave communications, beam training is an effective way to achieve beam alignment. Traditional beam training method allocates training resources equally to each beam in the pre-designed beam training codebook. The performance…
This paper proposes a novel neural network architecture, that we call an auto-precoder, and a deep-learning based approach that jointly senses the millimeter wave (mmWave) channel and designs the hybrid precoding matrices with only a few…
Efficiency of gradient propagation in intermediate layers of convolutional neural networks is of key importance for super-resolution task. To this end, we propose a deep architecture for single image super-resolution (SISR), which is built…
Beam alignment is required in millimeter wave communication to ensure high data rate transmission. However, with narrow beamwidth in massive MIMO, beam alignment could be computationally intensive due to the large number of beam pairs to be…
A model-based deep learning (DL) architecture is proposed for reconfigurable intelligent surface (RIS)-assisted multi-user communications to reduce the number of bits required for transmitting phase shift information from the access point…
Millimeter wave (mmWave) communication with large array gains is a key ingredient of next generation (5G) wireless networks. Effective communication in mmWaves usually depends on the knowledge of the channel. We refer to the problem of…
This paper presents the first large-scale real-world evaluation for using LiDAR data to guide the mmWave beam prediction task. A machine learning (ML) model that leverages the LiDAR sensory data to predict the current and future beams was…
Beamforming techniques are utilized in millimeter wave (mmWave) communication to address the inherent path loss limitation, thereby establishing and maintaining reliable connections. However, adopting standard defined beamforming approach…
In this paper, we investigate the beam training problem in the multi-user millimeter wave (mmWave) communication system, where multiple reconfigurable intelligent surfaces (RISs) are deployed to improve the coverage and the achievable rate.…
In this paper, we design a deep learning based resource allocation framework, in the form of an auction, for simultaneous information and power transfer from a hybrid access point (AP) to information devices and energy harvesting devices,…
Accurate indoor positioning for wireless communication systems represents an important step towards enhanced reliability and security, which are crucial aspects for realizing Industry 4.0. In this context, this paper presents an…
A deep learning (DL)-based power control algorithm that solves the max-min user fairness problem in a cell-free massive multiple-input multiple-output (MIMO) system is proposed. Max-min rate optimization problem in a cell-free massive MIMO…