Intelligent-Driven Green Resource Allocation for Industrial Internet of Things in 5G Heterogeneous Networks

Yu, Peng; Yang, Mo; Xiong, Ao; Ding, Yahui; Li, Wenjing; Qiu, Xuesong; Li, Meng; Kadoch, Michel; Cheriet, Mohamed

doi:10.1109/tii.2020.3041159

Cited by 45 publications

(20 citation statements)

References 22 publications

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“…A significant amount of work is focused on the resource allocation to improve the energy efficiency of wireless communication systems [10]- [17]. With the goal of maximizing the energy efficiency of orthogonal frequency division multiple access HetNets employing wireless backhaul, Ref.…”

Section: A Related Workmentioning

confidence: 99%

Energy Efficient Train-Ground mmWave Mobile Relay System for High Speed Railways

Wang

Niu

et al. 2023

IEEE Trans. on Green Commun. Netw.

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The rapid development of high-speed railways (HSRs) puts forward high requirements on the corresponding communication system. Millimeter wave (mmWave) can be a promising solution due to its wide bandwidth, narrow beams, and rich spectrum resources. However, with the large number of antenna elements employed, energy-efficient solutions at mmWave frequencies are in great demand. Based on a mmWave HSR communication system with multiple mobile relays (MRs) on top of the train, a dynamic power-control scheme for train-ground communications is proposed. The scheme follows the regular movement characteristics of high-speed trains and considers three phases of train movement: the train enters the cell, all MRs are covered in the cell, and the train leaves the cell. The transmit power is further refined according to the number of MRs in the cell and the distance between the train and the remote radio head. By minimizing energy consumption under

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Section: A Related Workmentioning

confidence: 99%

Energy Efficient Train-Ground mmWave Mobile Relay System for High Speed Railways

Wang

Niu

et al. 2023

IEEE Trans. on Green Commun. Netw.

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“…After years of development, it has continuously broken through the technical constraints and now successfully developed into the fifth-generation mobile communication technology. We usually simplify this name to 5G technology [16], which all comes from a simple formula [17].…”

Section: Theoretical Basismentioning

confidence: 99%

Design and Optimization of Children’s Education Online Monitoring System Based on 5G and Internet of Things

Zhong

2022

Scientific Programming

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At present, the problem of children’s education informationization is becoming more and more prominent. With the strengthening of national education, children’s online education has become one of the main forms. In order to educate children online, this paper proposes an online education system based on 5G technology and Internet of Things technology, which mainly solves the problems existing in current education. The results show the following: (1) UI test results basically meet the requirements of users; for the pursuit of personalized users, further development and improvement are needed. (2) Compared with children’s module, the response time of manager module increased by 12%, and all the response times did not exceed 10s, so the user experience was very good. The access success rate of children’s module is 99%, and that of managers’ module is 98%. It is necessary to further study what factors interfere with the success rate, which leads to the failure of 100% success. (3) After optimization, the total energy consumption is the lowest compared with NOMA and TDMA, which is the best energy efficiency optimization method to solve the communication of Internet of Things. The simulation of the system is in good condition, and the follow-up research work of developers will take this system as the core to improve more details, hoping to put it into market operation formally.

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“…The DAAs are widely analyzed and discussed in the context of the heterogeneous networks [4][5][6]. This problem is often connected with the throughput profiling [7] or the IoT (Internet of Things) and 5G networks [8,9]. In [7] authors proposed a solution for a dense industrial IoT network where many influencing to each other cells may be distinguished.…”

Section: Related Workmentioning

confidence: 99%

“…In [7] authors proposed a solution for a dense industrial IoT network where many influencing to each other cells may be distinguished. It was pointed that the proposed framework [9] can be improved by the DL what will lead to a better accuracy of the RI state estimation.…”

Section: Related Workmentioning

confidence: 99%

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

Cwalina

Rajchowski

Olejniczak

et al. 2021

Sensors

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Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost.

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Intelligent-Driven Green Resource Allocation for Industrial Internet of Things in 5G Heterogeneous Networks

Cited by 45 publications

References 22 publications

Energy Efficient Train-Ground mmWave Mobile Relay System for High Speed Railways

Energy Efficient Train-Ground mmWave Mobile Relay System for High Speed Railways

Design and Optimization of Children’s Education Online Monitoring System Based on 5G and Internet of Things

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

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