Compressive Sensing Based Grant-Free Random Access for Massive MTC
Type
Conference PaperKAUST Department
Communication Theory LabComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Date
2020-09-29Online Publication Date
2020-09-29Print Publication Date
2020-08Permanent link to this record
http://hdl.handle.net/10754/665810
Metadata
Show full item recordAbstract
Massive machine-Type communications (mMTC) are expected to be one of the most primary scenarios in the next-generation wireless communications and provide massive connectivity for Internet of Things (IoT). To meet the demanding technical requirements for mMTC, random access scheme with efficient joint activity and data detection (JADD) is vital. In this paper, we propose a compressive sensing (CS)-based grant-free random access scheme for mMTC, where JADD is formulated as a multiple measurement vectors (MMV) CS problem. By leveraging the prior knowledge of the discrete constellation symbols, we develop an orthogonal approximate message passing (OAMP)-MMV algorithm for JADD, where the structured sparsity is fully exploited for enhanced performance. Moreover, expectation maximization (EM) algorithm is employed to learn the unknown sparsity ratio of the a priori distribution and the noise variance. Simulation results show that the proposed scheme achieves superior performance over other state-of-The-Art CS schemes.Citation
Mei, Y., Gao, Z., Mi, D., Xiao, P., & Alouini, M.-S. (2020). Compressive Sensing Based Grant-Free Random Access for Massive MTC. 2020 International Conference on UK-China Emerging Technologies (UCET). doi:10.1109/ucet51115.2020.9205389Conference/Event name
2020 International Conference on UK-China Emerging Technologies, UCET 2020ISBN
9781728194882Additional Links
https://ieeexplore.ieee.org/document/9205389/http://epubs.surrey.ac.uk/858548/1/Compressive%20Sensing%20Based%20Grant-Free%20Random%20Access%20for%20Massive%20MTC%20-%20AAM.pdf
ae974a485f413a2113503eed53cd6c53
10.1109/UCET51115.2020.9205389