Channel Estimation and Device Detection for Reconfigurable Intelligent Surface Aided Massive IoT Networks With Mixed-ADCs-Reference-Cited by-同舟云学术

Channel Estimation and Device Detection for Reconfigurable Intelligent Surface Aided Massive IoT Networks With Mixed-ADCs

Published:2023-10 Issue:10 Volume:27 Page:2737-2741
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Liu Ting¹^ORCID,Jiang Hao¹^ORCID,Yang Xi²^ORCID,Yang Zhaohui³^ORCID

Affiliation:

1. Institute of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China

2. Shanghai Key Laboratory of Multidimensional Information Processing, School of Communication and Electronic Engineering, East China Normal University, Shanghai, China

3. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

Funder

NSFC

Jiangsu NSF

Shanghai Pujiang Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/4234/10275739/10236509.pdf?arnumber=10236509

Reference10 articles.

1. Low-Cost Design of Massive Access for Cellular Internet of Things

2. Downlink NOMA for Short-Packet Internet of Things Communications With Low-Resolution ADCs

3. Energy-Efficient Distributed Learning With Coarsely Quantized Signals

4. Hybrid Far- and Near-Field Modeling for Reconfigurable Intelligent Surface Assisted V2V Channels: A Sub-Array Partition Based Approach

5. Physics-Based 3D End-to-End Modeling for Double-RIS Assisted Non-Stationary UAV-to-Ground Communication Channels

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