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Reconfigurable intelligent surface (RIS) is an emerging technology for wireless communications. In this paper, extensive system level simulations are conducted for analyzing the performance of multi-RIS and multi-base-station (BS)…

信息论 · 计算机科学 2025-02-11 Yifei Yuan , Yuhong Huang , Xin Su , Boyang Duan , Nan Hu , Marco Di Renzo

Reconfigurable intelligent surface (RIS) has been recognized as an essential enabling technique for the sixth-generation (6G) mobile communication network. Specifically, an RIS is comprised of a large number of small and low-cost reflecting…

This paper proposes a three-dimensional (3D) geometry-based channel model to accurately represent intelligent reflecting surfaces (IRS)-enhanced integrated sensing and communication (ISAC) networks using rate-splitting multiple access…

信息论 · 计算机科学 2025-01-28 Zhangfeng Ma , Ruichen Zhang , Bo Ai , Zhuxian Lian , Linzhou Zeng , Dusit Niyato

Stacked intelligent metasurfaces (SIM) represents an advanced signal processing paradigm that enables over-the-air processing of electromagnetic waves at the speed of light. Its multi-layer structure exhibits customizable increased…

信号处理 · 电气工程与系统科学 2024-02-15 Hao Liu , Jiancheng An , Derrick Wing Kwan Ng , George C. Alexandropoulos , Lu Gan

In the past few years, Deep Reinforcement Learning (DRL) has become a valuable solution to automatically learn efficient resource management strategies in complex networks. In many scenarios, the learning task is performed in the Cloud,…

网络与互联网体系结构 · 计算机科学 2022-12-01 Seyyidahmed Lahmer , Federico Chiariotti , Andrea Zanella

Intelligent reflecting surfaces (IRSs) tune wireless environments to increase spectrum and energy efficiencies. In view of much recent attention to the IRS concept as a promising technology for 6G wireless communications, we present a…

信号处理 · 电气工程与系统科学 2019-11-05 Jun Zhao

Reconfigurable intelligent surfaces (RISs) have attracted wide interest from industry and academia since they can shape the wireless environment into a desirable form with a low cost. In practice, RISs have three types of implementations:…

信息论 · 计算机科学 2021-02-16 Shuhao Zeng , Hongliang Zhang , Boya Di , Yunhua Tan , Zhu Han , H. Vincent Poor , Lingyang Song

Deep reinforcement learning (DRL) is a promising outer-loop intelligence paradigm which can deploy problem solving strategies for complex tasks. Consequently, DRL has been utilized for several scientific applications, specifically in cases…

机器学习 · 计算机科学 2023-04-05 Sahil Bhola , Suraj Pawar , Prasanna Balaprakash , Romit Maulik

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to assist terrestrial infrastructure for keeping wireless connectivity in various emergency scenarios. To maximize the coverage rate of N ground users (GUs) by…

信息论 · 计算机科学 2020-02-06 Jin Qiu , Jiangbin Lyu , Liqun Fu

Internet of Things (IoT) devices have become increasingly ubiquitous with applications not only in urban areas but remote areas as well. These devices support industries such as agriculture, forestry, and resource extraction. Due to the…

Reconfigurable Intelligent Surfaces (RISs) are promising and relatively low-cost tools for improving signal propagation in wireless communications. An RIS assists a base station in optimizing the channel and maximizing its capacity by…

Intelligent reflecting surfaces (IRS) have become the subject of many current research efforts, as the ongoing wireless spectrum crunch has made the need to open higher frequency bands a priority. IRS are one of the alternatives proposed to…

信息论 · 计算机科学 2025-12-01 Alessandro Nordio , Alberto Tarable , Francisco J. Escribano

With the advent of 5G and the research into beyond 5G (B5G) networks, a novel and very relevant research issue is how to manage the coexistence of different types of traffic, each with very stringent but completely different requirements.…

信号处理 · 电气工程与系统科学 2026-03-16 Fabio Saggese , Luca Pasqualini , Marco Moretti , Andrea Abrardo

Reconfigurable Intelligent Surface (RIS) is envisioned to be an enabling technique in 6G wireless communications. By configuring the reflection beamforming codebook, RIS focuses signals on target receivers to enhance signal strength. In…

信息论 · 计算机科学 2024-11-07 Huiying Yang , Rujing Xiong , Yao Xiao , Zhijie Fan , Tiebin Mi , Robert Caiming Qiu , Zenan Ling

We study the allocation of reconfigurable intelligent surfaces (RISs) in a multi-cell wireless network, where base stations compete for control of shared RIS units deployed at the cell edges. These RISs, provided by an independent operator,…

网络与互联网体系结构 · 计算机科学 2026-03-06 Martin Mark Zan , Stefan Schwarz

The dynamic allocation of spectrum in 5G / 6G networks is critical to efficient resource utilization. However, applying traditional deep reinforcement learning (DRL) is often infeasible due to its immense sample complexity and the safety…

机器学习 · 计算机科学 2026-03-02 Oluwaseyi Giwa , Tobi Awodunmila , Muhammad Ahmed Mohsin , Ahsan Bilal , Muhammad Ali Jamshed

Optimizing discrete phase shifts in large-scale reconfigurable intelligent surfaces (RISs) is challenging due to their non-convex and non-linear nature. In this letter, we propose a heuristic-integrated deep reinforcement learning (DRL)…

信号处理 · 电气工程与系统科学 2025-05-08 Wei Wang , Peizheng Li , Angela Doufexi , Mark A. Beach

The wireless in-band full-duplex (IBFD) technology can in theory double the system capacity over the conventional frequency division duplex (FDD) or time-division duplex (TDD) alternatives. But the strong self-interference of the IBFD can…

信号处理 · 电气工程与系统科学 2022-11-23 Wei Zhang , Yi Jiang , Bin Zhou

Reconfigurable intelligent surface (RIS) is an emerging technology that is under investigation for different applications in wireless communications. RISs are often analyzed and optimized by considering simplified electromagnetic…

Conventional active array radars often jointly design the transmit and receive beamforming for effectively suppressing interferences. To further promote the interference suppression performance, this paper introduces a reconfigurable…

信号处理 · 电气工程与系统科学 2024-01-30 Shengyao Chen , Qi Feng , Longyao Ran , Feng Xi , Zhong Liu