相关论文: Deep-Learning Based Reconfigurable Intelligent Sur…

Reconfigurable intelligent surface (RIS) technique stands as a promising signal enhancement or signal cancellation technique for next generation networks. We design a novel passive beamforming weight at RISs in a multiple-input…

This paper addresses the crucial need for reliable wireless communication in vehicular networks, particularly vital for the safety and efficacy of (semi-)autonomous driving amid increasing traffic. We explore the use of Reconfigurable…

We present a resilient deep neural network (DNN) framework for decentralized transport and coverage using uncrewed aerial systems (UAS) operating in $\mathbb{R}^n$. The proposed DNN-based mass-transport architecture constructs a layered…

Future wireless networks are envisioned to deliver not only gigabit communications but also ubiquitous sensing. Reconfigurable intelligent surfaces (RISs) have emerged to reshape radio propagation, recently showing considerable promise for…

The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary complex neural network architectures. The cascaded network…

Reconfigurable intelligent surface (RIS) is one of the most promising technologies for 5G-Adv and 6G. It has the characteristics of low cost, low complexity, and easy deployment, which provides a new opportunity to develop intelligent…

Existing works mainly rely on the far-field planar-wave-based channel model to assess the performance of reconfigurable intelligent surface (RIS)-enabled wireless communication systems. However, when the transmitter and receiver are in…

This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequency-division duplex massive multiple-input multiple-output…

Nonorthogonal multiple access (NOMA) with multi-antenna base station (BS) is a promising technology for next-generation wireless communication, which has high potential in performance and user fairness. Since the performance of NOMA depends…

Downlink reconfigurable intelligent surface (RIS)-assisted multi-input-multi-output (MIMO) systems are considered with far-field, near-field, and hybrid-far-near-field channels. According to the angular or distance information contained in…

Deep neural network has been ensured as a key technology in the field of many challenging and vigorously researched computer vision tasks. Furthermore, classical ResNet is thought to be a state-of-the-art convolutional neural network (CNN)…

In this article, we study the problem of robust reconfigurable intelligent surface (RIS)-aided downlink communication over heterogeneous RIS types in the supervised learning setting. By modeling downlink communication over heterogeneous RIS…

Massive Multiple-Input Multiple-Output (massive MIMO) technology stands as a cornerstone in 5G and beyonds. Despite the remarkable advancements offered by massive MIMO technology, the extreme number of antennas introduces challenges during…

By activating blocked users and altering successive interference cancellation (SIC) sequences, reconfigurable intelligent surfaces (RISs) become promising for enhancing non-orthogonal multiple access (NOMA) systems. The downlink RIS-aided…

The Reconfigurable Intelligent Surface (RIS) constitutes one of the prominent technologies for the next generation of wireless communications. It is envisioned to enhance the signal coverage in cases when the direct link of the…

Deep convolutional neural networks (DCNNs) have been used to achieve state-of-the-art performance on many computer vision tasks (e.g., object recognition, object detection, semantic segmentation) thanks to a large repository of annotated…

We propose a complex-valued neural-network (CV-NN) framework to optimally configure stacked intelligent surfaces (SIS) in next-generation multi-antenna systems. Unlike conventional solutions that separately tune analog metasurface phases or…

Indoor multi-robot communications face two key challenges: one is the severe signal strength degradation caused by blockages (e.g., walls) and the other is the dynamic environment caused by robot mobility. To address these issues, we…

This paper considers reconfigurable intelligent surface (RIS)-assisted point-to-point multiple-input multiple-output (MIMO) communication systems, where a transmitter communicates with a receiver through an RIS. Based on the main target of…

There is widespread interest in emerging technologies, especially resistive crossbars for accelerating Deep Neural Networks (DNNs). Resistive crossbars offer a highly-parallel and efficient matrix-vector-multiplication (MVM) operation. MVM…