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Reliable evaluation for the AI-enabled intrusion detection system from data perspective. [PDF]

PLoS One
Zhang HJ, Yang K, Ran P, He S, Chen J.
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AI-embedded IoT healthcare optimization with trust-aware mobile edge computing. [PDF]

Sci Rep
Alamri M, Haseeb K, Humayun M, Alshammeri M.   +3 more
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Meeting abstracts of the Toronto Resuscitation Conference. [PDF]

Scand J Trauma Resusc Emerg Med
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Enhanced Random Access for Massive-Machine-Type Communications

IEEE Internet of Things Journal, 2021
In this article, we study a random access (RA) scheme to alleviate the RA channel (RACH) overload problem in the massive-machine-type communication (mMTC) environment. We first propose a timing advance-based preamble resource expansion (TAPRE) scheme which effectively increases preamble resources and reduces the preamble collision probability by ...
Byung-Hyun Lee, Hyun-Suk Lee, Seokjae Moon, Jang-Won Lee   +3 more
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Practical Synchronization Waveform for Massive Machine-Type Communications

IEEE Transactions on Communications, 2019
This paper proposes a practical synchronization waveform that is resilient to frequency error for machine-type communications with applications in massive Internet of Things (IoT). Mathematical properties of the waveform are derived, which are keys to addressing the practical issues.
Jingjing Zhang, Michael Mao Wang, Tingting Xia   +2 more
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Introduction on Massive Machine-Type Communications (mMTC)

2019
With the rise of a new round of scientific and technological revolutions and industrial changes in the world, the emergence of a large number of new applications, new businesses, new fields and new markets pose more requirements and challenges to existing mobile communication technologies [1].
Fanggang Wang, Guoyu Ma
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Pilot beamforming for massive machine type communication systems

2017 IEEE/CIC International Conference on Communications in China (ICCC), 2017
In this paper, we propose a novel pilot beamforming and CSI acquisition strategy for machine-type-communication systems to achieve reduction in pilot overhead and improve the channel estimation performance. Key idea of the proposed beam-forming technique is to sparsify the time-domain channel vector using the beamforming.
Hyoungju Ji, Jun Won Choi, Byonghyo Shim
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