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Intelligent and Converged Networks 2022, 3(1): 134-143 https://doi.org/10.23919/ICN.2022.0009
Open Access | Issue | Published: 30 March 2022

Reconfigurable intelligent surface assisted grant-free massive access

Show Author's Information Xingyu Zhou1,  Keke Ying1,  Shicong Liu1,  Malong Ke1,  Zhen Gao2( ),  Mohamed-Slim Alouini3
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing 100081, China, and also with National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
Keywords:
reconfigurable intelligent surface (RIS), massive machine-type communications (mMTC), grant-free random access (GF-RA), active device detection, channel estimation, approximate message passing (AMP)
Cite this article:
Zhou X, Ying K, Liu S, et al. Reconfigurable intelligent surface assisted grant-free massive access . Intelligent and Converged Networks, 2022, 3(1): 134-143. https://doi.org/10.23919/ICN.2022.0009
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Abstract Full text About this article

Massive machine-type communications (mMTC) is envisioned to be one of the pivotal scenarios in the fifth-generation (5G) wireless communication, where the explosively emerging Internet-of-Things (IoT) applications have triggered the demand for services with low-latency and high-reliability. To this end, grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency. In this paper, we propose to leverage the burgeoning reconfigurable intelligent surface (RIS) for grant-free massive access working at millimeter-wave (mmWave) frequency to further boost access reliability. By attaching independently controllable phase shifts, reconfiguring, and refracting the propagation of incident electromagnetic waves, the deployed RISs could provide additional diversity gain and enhance the access channel conditions. On this basis, to address the challenging active device detection (ADD) and channel estimation (CE) problem, we develop a joint-ADDCE (JADDCE) method by resorting to the existing approximate message passing (AMP) algorithm with expectation maximization (EM) to extract the structured common sparsity in traffic behaviors and cascaded channel matrices. Finally, simulations are carried out to demonstrate the superiority of our proposed scheme.


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About this article

Reconfigurable intelligent surface assisted grant-free massive access

Show Author's information Xingyu Zhou1, Keke Ying1, Shicong Liu1, Malong Ke1, Zhen Gao2( ), Mohamed-Slim Alouini3
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing 100081, China, and also with National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia

Abstract

Massive machine-type communications (mMTC) is envisioned to be one of the pivotal scenarios in the fifth-generation (5G) wireless communication, where the explosively emerging Internet-of-Things (IoT) applications have triggered the demand for services with low-latency and high-reliability. To this end, grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency. In this paper, we propose to leverage the burgeoning reconfigurable intelligent surface (RIS) for grant-free massive access working at millimeter-wave (mmWave) frequency to further boost access reliability. By attaching independently controllable phase shifts, reconfiguring, and refracting the propagation of incident electromagnetic waves, the deployed RISs could provide additional diversity gain and enhance the access channel conditions. On this basis, to address the challenging active device detection (ADD) and channel estimation (CE) problem, we develop a joint-ADDCE (JADDCE) method by resorting to the existing approximate message passing (AMP) algorithm with expectation maximization (EM) to extract the structured common sparsity in traffic behaviors and cascaded channel matrices. Finally, simulations are carried out to demonstrate the superiority of our proposed scheme.

Keywords: reconfigurable intelligent surface (RIS), massive machine-type communications (mMTC), grant-free random access (GF-RA), active device detection, channel estimation, approximate message passing (AMP)

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Published: 30 March 2022
Issue date: March 2022

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (NSFC) (No. 62071044), the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2022D09), Beijing Institute of Technology Research Fund Program for Young Scholars (No. XSQD-202121009), and Ensan Foundation (No. 2022006).

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