Massive Unsourced Random Access Under Carrier Frequency Offset

doi:10.12142/ZTECOM.202303007

ZTE Communications ›› 2023, Vol. 21 ›› Issue (3): 45-53.DOI: 10.12142/ZTECOM.202303007

收稿日期:2022-05-22 出版日期:2023-09-21 发布日期:2023-03-22

Massive Unsourced Random Access Under Carrier Frequency Offset

XIE Xinyu¹, WU Yongpeng¹(), YUAN Zhifeng^2,³, MA Yihua^2,³

^1.Shanghai Jiao Tong University, Shanghai 200240, China
^2.ZTE Corporation, Shenzhen 518057, China
^3.State Key Laboratory of Mobile Network and Mobile Multimedia Technology, Shenzhen 518055, China

Received:2022-05-22 Online:2023-09-21 Published:2023-03-22
About author:XIE Xinyu received his BS degree in telecommunication engineering from Xidian University, China in 2019. He is currently working toward a PhD degree in electronic engineering at Shanghai Jiao Tong University, China. His research interests include massive random access and compressed sensing.|WU Yongpeng (yongpeng.wu@sjtu.edu.cn) received his BS degree in telecommunication engineering from Wuhan University, China in July 2007, and PhD degree in communication and signal processing from the National Mobile Communications Research Laboratory, Southeast University, China in 2013. He is currently a tenure-track associate professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. His research interests include massive MIMO/MIMO systems, massive machine type communication, physical layer security, and signal processing for wireless communications.|YUAN Zhifeng received his MS degree in signal and information processing from Nanjing University of Post and Telecommunications, China in 2005. From 2004 to 2006, he was mainly engaged in FPGA/SOC ASIC design. He has been a member of the Wireless Technology Advance Research Department, ZTE Corporation since 2006 and has been responsible for the research of the new multiple access group since 2012. His research interests include wireless communication, MIMO systems, information theory, multiple access, error control coding, adaptive algorithm, and high-speed VLSI design.|MA Yihua received his BE degree from Southeast University, China in 2015 and MS degree from Peking University, China in 2018. He is now a pre-research expert engineer in the Department of Wireless Algorithm, ZTE Corporation. His main research interests include mMTC, grant-free transmissions, NOMA, and joint communication and sensing. In these areas, he has published and applied more than 10 papers and 20 patents.
Supported by:
the ZTE Industry?University?Institute Cooperation Funds(HC?CN?20201116001)

摘要/Abstract

Abstract:

Unsourced random access (URA) is a new perspective of massive access which aims at supporting numerous machine-type users. With the appearance of carrier frequency offset (CFO), joint activity detection and channel estimation, which is vital for multiple-input and multiple-output URA, is a challenging task. To handle the phase corruption of channel measurements under CFO, a novel compressed sensing algorithm is proposed, leveraging the parametric bilinear generalized approximate message passing framework with a Markov chain support model that captures the block sparsity structure of the considered angular domain channel. An uncoupled transmission scheme is proposed to reduce system complexity, where slot-emitted messages are reorganized relying on clustering unique user channels. Simulation results reveal that the proposed transmission design for URA under CFO outperforms other potential methods.

Key words: activity detection, channel estimation, frequency offset, massive machine-type communication, massive MIMO

. [J]. ZTE Communications, 2023, 21(3): 45-53.

XIE Xinyu, WU Yongpeng, YUAN Zhifeng, MA Yihua. Massive Unsourced Random Access Under Carrier Frequency Offset[J]. ZTE Communications, 2023, 21(3): 45-53.

图/表 4

Figure 1 Factor graph for Bayesian inference

Figure 2 NMSEs versus the iteration number under different SNRs with M=32, Ns=100, and Ka=50

Figure 3 Joint AD and CE (JADCE) performance of various algorithms with M=32, Ka=50

Figure 4 Error probabilities of various unsourced random access (URA) schemes under CFO as a function of SNR with Ns=100, Ka=50

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