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The combination of Integrated Sensing and Communication (ISAC) and Mobile Edge Computing (MEC) enables devices to simultaneously sense the environment and offload data to the base stations (BS) for intelligent processing, thereby reducing…

信号处理 · 电气工程与系统科学 2025-05-01 Peng Liu , Zesong Fei , Xinyi Wang , Xiaoyang Li , Weijie Yuan , Yuanhao Li , Cheng Hu , Dusit Niyato

Semantic communication systems aim to transmit task-relevant information between devices capable of artificial intelligence, but their performance can degrade when heterogeneous transmitter-receiver models produce misaligned latent…

信号处理 · 电气工程与系统科学 2025-12-08 Mario Edoardo Pandolfo , Kyriakos Stylianopoulos , George C. Alexandropoulos , Paolo Di Lorenzo

This paper presents a deep learning (DL) approach for estimating and detecting symbols in signals transmitted through reconfigurable intelligent surfaces (RIS). The proposed network utilizes fully connected layers to estimate channels and…

信号处理 · 电气工程与系统科学 2020-07-28 Saud Khan , Komal S Khan , Noman Haider , Soo Young Shin

Stacked intelligent metasurfaces (SIMs) represent a breakthrough in wireless hardware by comprising multilayer, programmable metasurfaces capable of analog computing in the electromagnetic (EM) wave domain. By examining their architectural…

信号处理 · 电气工程与系统科学 2026-03-27 Hetong Wang , Yashuai Cao , Tiejun Lv

Semantic communication (SemCom) powered by generative artificial intelligence enables highly efficient and reliable information transmission. However, it still necessitates the transmission of substantial amounts of data when dealing with…

信息论 · 计算机科学 2025-06-17 Guojun Huang , Jiancheng An , Lu Gan , Dusit Niyato , Mérouane Debbah , Tie Jun Cui

Leveraging the multilayer realization of programmable metasurfaces, stacked intelligent metasurfaces (SIM) enable fine-grained wave-domain control. However, their wideband deployment is impeded by two structural factors: (i) a single,…

信号处理 · 电气工程与系统科学 2026-03-16 Zheao Li , Jiancheng An , Chau Yuen

Next-generation wireless networks are expected to utilize the limited radio frequency (RF) resources more efficiently with the aid of intelligent transceivers. To this end, we propose a promising transceiver architecture relying on stacked…

Integrated sensing and communication (ISAC) and intelligent reflecting surface (IRS) are viewed as promising technologies for future generations of wireless networks. This paper investigates the channel estimation problem in an IRS-assisted…

信号处理 · 电气工程与系统科学 2024-04-09 Yu Liu , Ibrahim Al-Nahhal , Octavia A. Dobre , Fanggang Wang

We present a physically consistent multiport framework for stacked intelligent metasurfaces (SIMs) with linear and explicit nonlinear terminations. The model provides closed-form input--output relations in the linear case and fixed-point…

信号处理 · 电气工程与系统科学 2026-05-25 Andrea Abrardo , Alberto Toccafondi

Intelligent metasurface has recently emerged as a promising technology that enables the customization of wireless environments by harnessing large numbers of low-cost reconfigurable scattering elements. However, prior studies have…

信息论 · 计算机科学 2025-05-05 Jiancheng An , Marco Di Renzo , Mérouane Debbah , H. Vincent Poor , Chau Yuen

Reconfigurable intelligent surface has recently emerged as a promising technology for shaping the wireless environment by leveraging massive low-cost reconfigurable elements. Prior works mainly focus on a single-layer metasurface that lacks…

信息论 · 计算机科学 2023-02-15 Jiancheng An , Marco Di Renzo , Merouane Debbah , Chau Yuen

Stacked intelligent metasurface (SIM) is an emerging technology that capitalizes on reconfigurable metasurfaces for several applications in wireless communications. SIM is considered an enabler for integrating communication, sensing and…

信息论 · 计算机科学 2024-12-02 Marco Di Renzo

Stacked intelligent metasurface (SIM) has emerged as a technology enabling wave domain beamforming through multiple stacked reconfigurable intelligent surfaces (RISs). SIM has been implemented so far with diagonal RIS (D-RIS), while SIM…

信息论 · 计算机科学 2024-05-14 Matteo Nerini , Bruno Clerckx

Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pattern classification. Contrary to the DNNs trained end to…

计算机视觉与模式识别 · 计算机科学 2019-05-09 Cheng-Yaw Low , Jaewoo Park , Andrew Beng-Jin Teoh

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…

信号处理 · 电气工程与系统科学 2021-12-06 Jiguang He , Henk Wymeersch , Marco Di Renzo , Markku Juntti

The recent combination of the rising architectures, known as stacked intelligent metasurface (SIM) and holographic multiple-input multiple-output (HMIMO), drives toward breakthroughs for next-generation wireless communication systems. Given…

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…

信号处理 · 电气工程与系统科学 2024-10-29 Do Hai Son , Vu Tung Lam , Tran Thi Thuy Quynh

Stacked intelligent metasurfaces (SIMs) have recently gained significant interest since they enable precoding in the wave domain that comes with increased processing capability and reduced energy consumption. The study of SIMs and high…

Land cover maps generated from semantic segmentation of high-resolution remotely sensed images have drawn mucon in the photogrammetry and remote sensing research community. Currently, massive fine-resolution remotely sensed (FRRS) images…

计算机视觉与模式识别 · 计算机科学 2025-06-30 Naftaly Wambugu , Ruisheng Wang , Bo Guo , Tianshu Yu , Sheng Xu , Mohammed Elhassan

This paper investigates a Stacked Intelligent Metasurfaces (SIM)-assisted Integrated Sensing and Communications (ISAC) system. An extended target model is considered, where the BS aims to estimate the complete target response matrix…