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http://dx.doi.org/10.22156/CS4SMB.2020.10.11.023

Secret Key-Dimensional Distribution Mechanism Using Deep Learning to Minimize IoT Communication Noise Based on MIMO  

Cho, Sung-Nam (Korea Institute of Science and Technology Information)
Jeong, Yoon-Su (Department of information Communication Convergence Engineering, Mokwon University)
Publication Information
Journal of Convergence for Information Technology / v.10, no.11, 2020 , pp. 23-29 More about this Journal
Abstract
As IoT devices increase exponentially, minimizing MIMO interference and increasing transmission capacity for sending and receiving IoT information through multiple antennas remain the biggest issues. In this paper, secret key-level distribution mechanism using deep learning is proposed to minimize MIMO-based IoT communication noise. The proposed mechanism minimizes resource loss during transmission and reception process by dispersing IoT information sent and received through multiple antennas in batches using deep learning. In addition, the proposed mechanism applied a multidimensional key distribution processing process to maximize capacity through multiple antenna multiple stream transmission at base stations without direct interference between the APs. In addition, the proposed mechanism synchronizes IoT information by deep learning the frequency of use of secret keys according to the number of IoT information by applying the method of distributing secret keys in dimension according to the number of frequency channels of IoT information in order to make the most of the multiple antenna technology.
Keywords
MIMO; IoT; Key-level distribution; Multi Access; IoT Big data;
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