4.8 Article

Energy-Efficient Resource Allocation and Data Transmission of Cell-Free Internet of Things

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 20, 页码 15107-15116

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3030675

关键词

Resource management; Internet of Things; Wireless communication; Massive MIMO; Energy efficiency; Sensors; Optimization; Data transmission; energy efficiency (EE); Internet of Things (IoT); machine learning (ML); resource allocation

资金

  1. National Natural Science Foundation of China [61771342, 61701345, 61704122, 61801327, 61901301]
  2. Natural Science Foundation of Tianjin [18JCQNJC70900, 18JCZDJC31900]
  3. Tianjin Higher Education Creative Team Funds Program

向作者/读者索取更多资源

The Internet of Things (IoT) aims to connect all things, facing challenges to reliability and sustainability due to the increasing number of things and data. The proposed cell-free IoT system can enhance reliability and robustness compared with cellular IoT system, considering resource allocation and data transmission optimization. The presented algorithm improves energy efficiency and shows better reliability and sustainability for cell-free IoT.
The Internet of Things (IoT) is a huge network consisting of various information-sensing devices combined with the Internet. The IoT aims to connect all things with the network to facilitate identification and management. The increasing number of things, connections, and volume of data is challenging the reliability and sustainability of the IoT. To push forward the development of the IoT, a cell-free IoT system is proposed based on a cell-free wireless communication network. Under the architecture of cell-free IoT, the cell concept for wireless communication in the IoT system has been diluted, and the reliability and robustness of the IoT system can be improved when compared with the cellular IoT system. Moreover, this article considers resource allocation and data transmission of cell-free IoT. An optimization model is designed for resource allocation to ensure quality data transmission. Furthermore, a novel heuristic algorithm is proposed for solving the optimization model. The heuristic algorithm is memetic of two machine learning methods. Extensive simulations are conducted to study the performance of the presented cell-free IoT. Energy efficiency is improved by the proposed algorithm compared with existing algorithms. The results show that cell-free IoT can achieve better reliability and sustainability.

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