TY - JOUR
T1 - Nonlinear MIMO for Industrial Internet of Things in Cyber-Physical Systems
AU - Gong, Yi
AU - Zhang, Lin
AU - Liu, Renping
AU - Yu, Keping
AU - Srivastava, Gautam
N1 - Funding Information:
Manuscript received June 12, 2020; revised August 24, 2020; accepted September 3, 2020. Date of publication September 18, 2020; date of current version May 3, 2021. This work was supported in part by CERNET Innovation Project under Grant NGIICS20190301, in part by the Construction of System-level Connected Vehicle Test and Verification Platform under Grant 2019-00892-2-1, and in part by the University of Technology Sydney (UTS) in Australia. Paper no. TII-20-2856. (Corresponding author: Keping Yu.) Yi Gong is with the School of Information and Communication Engineering, Beijing University of Posts and Communications (BUPT), Beijing 100876, China, and also with the University of Technology Sydney (UTS), Global Big Data Technologies Center (GBDTC), Sydney 2007 NSW, Australia (e-mail: gongyi@bupt.edu.cn).
Publisher Copyright:
© 2005-2012 IEEE.
PY - 2021/8
Y1 - 2021/8
N2 - Massive multiple-input multiple-output (MIMO) wireless communication technology with the characteristics of hyperconnectivity is an ideal channel to connect the industrial Internet of Things (IIoT) and the cyber-physical system. It provides stable and reliable connectivity from the data center to distributed user terminals and the IIoT. However, traditional massive MIMO suffers from high power consumption and fabrication cost. The design of energy-efficient massive MIMO technology is essential for larger scale industrial deployments. In this article, we design three types of nonlinear RF chain structures, which not only reduce the power consumption of massive MIMO systems but also save fabrication costs. Information theoretic analysis demonstrates the power efficiency performance of our nonlinear system design. Our nonlinear MIMO system designs can increase the power efficiency by up to 2.3 times compared with the traditional MIMO system. We have demonstrated that our systems can achieve the same uplink rate as traditional MIMO by increasing the number of receiving antennas but with less overall power consumption. We also proposed an algorithm to overcome the problem of low computational efficiency due to high-dimensional integration when calculating the uplink achievable rate of nonlinear MIMO. Moreover, we reveal that when the skew-normal distribution is used as signaling, the nonlinear MIMO systems can achieve better performance than the Gaussian distribution.
AB - Massive multiple-input multiple-output (MIMO) wireless communication technology with the characteristics of hyperconnectivity is an ideal channel to connect the industrial Internet of Things (IIoT) and the cyber-physical system. It provides stable and reliable connectivity from the data center to distributed user terminals and the IIoT. However, traditional massive MIMO suffers from high power consumption and fabrication cost. The design of energy-efficient massive MIMO technology is essential for larger scale industrial deployments. In this article, we design three types of nonlinear RF chain structures, which not only reduce the power consumption of massive MIMO systems but also save fabrication costs. Information theoretic analysis demonstrates the power efficiency performance of our nonlinear system design. Our nonlinear MIMO system designs can increase the power efficiency by up to 2.3 times compared with the traditional MIMO system. We have demonstrated that our systems can achieve the same uplink rate as traditional MIMO by increasing the number of receiving antennas but with less overall power consumption. We also proposed an algorithm to overcome the problem of low computational efficiency due to high-dimensional integration when calculating the uplink achievable rate of nonlinear MIMO. Moreover, we reveal that when the skew-normal distribution is used as signaling, the nonlinear MIMO systems can achieve better performance than the Gaussian distribution.
KW - Cyber-physical systems
KW - Internet of Things (IoT)
KW - information theory
KW - low power consumption
KW - nonlinear mimo systems
KW - uplink achievable rate
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U2 - 10.1109/TII.2020.3024631
DO - 10.1109/TII.2020.3024631
M3 - Article
AN - SCOPUS:85105582819
SN - 1551-3203
VL - 17
SP - 5533
EP - 5541
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 8
M1 - 9200720
ER -