Cited by Enabling Urban MmWave Communications with UAV-Carried IRS via Deep Reinforcement Learning

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications DOI

Enyu Shi, Jiayi Zhang, Hongyang Du

и другие.

Proceedings of the IEEE, Год журнала: 2024, Номер 112(4), С. 331 - 364

Опубликована: Апрель 1, 2024

An introduction of intelligent interconnectivity for people and things has posed higher demands more challenges sixth-generation (6G) networks, such as high spectral efficiency energy (EE), ultralow latency, ultrahigh reliability. Cell-free (CF) massive multiple-input-multiple-output (mMIMO) reconfigurable surface (RIS), also called reflecting (IRS), are two promising technologies coping with these unprecedented demands. Given their distinct capabilities, integrating the to further enhance wireless network performances received great research development attention. In this article, we provide a comprehensive survey on RIS-aided CF mMIMO communication systems. We first introduce system models focusing architecture application scenarios, channel models, protocols. Subsequently, summarize relevant studies operation resource allocation, providing in-depth analyses discussions. Following this, present practical faced by systems, particularly those introduced RIS, hardware impairments (HIs) electromagnetic interference (EMI). corresponding solutions facilitate implementation Furthermore, explore an interplay between other emerging 6G technologies, millimeter wave (mmWave) terahertz (THz), simultaneous information power transfer (SWIPT), next-generation multiple access (NGMA), unmanned aerial vehicle (UAV). Finally, outline several directions future

Язык: Английский

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Optimal and intelligent 3D positioning of relay in dynamic UAV network DOI