Reconfigurable intelligent surface assisted grant-free massive access
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ArticleKAUST Department
King Abdullah University of Science and Technology (KAUST),Computer, Electrical and Mathematical Sciences and Engineering Division,Thuwal,Kingdom of Saudi Arabia,23955-6900Electrical and Computer Engineering Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Date
2022-04-29Permanent link to this record
http://hdl.handle.net/10754/676708
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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.Citation
Zhou, X., Ying, K., Liu, S., Ke, M., Gao, Z., & Alouini, M.-S. (2022). Reconfigurable intelligent surface assisted grant-free massive access. Intelligent and Converged Networks, 3(1), 134–143. https://doi.org/10.23919/icn.2022.0009Sponsors
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).Additional Links
https://ieeexplore.ieee.org/document/9765812/ae974a485f413a2113503eed53cd6c53
10.23919/icn.2022.0009
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