Entropy Reduced Mobile Networks Empowering Industrial Applications

doi:10.13190/j.jbupt.2020-260

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (6): 1-9.doi: 10.13190/j.jbupt.2020-260

Entropy Reduced Mobile Networks Empowering Industrial Applications

ZHANG Ping¹, XU Xiao-dong², HAN Shu-jun², NIU Kai³, XU Wen-jun³, LAN Yue-heng⁴

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. National Engineering Laboratory for Mobile Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;
3. The Key Laboratory of Universal Wireless Communications(Ministry of Education), Beijing University of Posts and Telecommunications, Beijing 100876, China;
4. School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2020-11-25 Online:2020-12-28 Published:2020-11-30

Abstract

Abstract: Currently, the mobile networks represented by the fifth generation of mobile communications system (5G) are facing various challenges in empowering industrial applications. The requirements and challenges of 5G empowering industrial applications in communication, control, computation, and security are analyzed. It formulates the sixth generation of mobile communications system(6G) evolution of the mobile networks for empowering industrial application, in a special form named as entropy reduced mobile networks. Based on information theory and directed by systems theory, the entropy reduced mobile networks emphasizes the utilization of endogenous intelligence of semantic information and endogenous simplicity architecture to achieve the global optimization for realizing mobile networks empowering industrial applications, which formulates a potential evolution path to 6G.

Key words: industry application, entropy reduced mobile networks, the fifth generation of mobile communications system, the sixth generation of mobile communications system

CLC Number:

TN911.22

ZHANG Ping, XU Xiao-dong, HAN Shu-jun, NIU Kai, XU Wen-jun, LAN Yue-heng. Entropy Reduced Mobile Networks Empowering Industrial Applications[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 1-9.

References

[1] 5G应用产业方阵. 5G行业虚拟专网网络架构[EB/OL]. 2020(2020-07-29)[2020-12-03]. http://www.chuangze.cn/third_1.asp?txtid=2148.
[2] 王欣. 拥抱5G新世界[EB/OL]. 2019(2019-05-28)[2020-12-03]. https://www.rolandberger.com/zh/Publications/%E6%8B%A5%E6%8A%B15G%E6%96%B0%E4%B8%96%E7%95%8C.html.
[3] Han Shujun, Xu Xiaodong, Fang Sisai, et al. Energy efficient secure computation offloading in NOMA-based mMTC networks for IoT[J]. IEEE Internet of Things Journal, 2019, 6(3):5674-5690.
[4] Feng Daquan, She Changyang, Ying Kai, et al. Towards ultra-reliable low-latency communications:typical scenarios, possible solutions, and open issues[J]. IEEE Vehicular Technology Magazine, 2019, 14(2):94-102.
[5] Tao Xiaofeng, Han Yan, Xu Xiaodong, et al. Recent advances and future challenges for mobile network virtualization[J]. Science China Information Sciences, 2017, 60(4):040301.
[6] Du Shuxing, Liu Bo, Ma Huixun, et al. ⅡOT-based intelligent control and management system for motorcycle endurance test[J]. IEEE Access, 2018, 6:30567-30576.
[7] 王卫斌, 朱进国, 王全. 5G核心网演进需求及关键技术[J]. 中兴通讯技术, 2020, 26(1):67-72. Wang Weibin, Zhu Jinguo, Wang Quan. Evolution requirements and key technologies of 5G core network[J]. ZTE Technology Journal, 2020, 26(1):67-72.
[8] 马立川, 裴庆祺, 肖慧子. 万物互联背景下的边缘计算安全需求与挑战[J]. 中兴通讯技术, 2019, 25(3):37-42. Ma Lichuan, Pei Qingqi, Xiao Huizi. Security requirements and challenges in edge computing for Internet of everything[J]. ZTE Technology Journal, 2019, 25(3):37-42.
[9] Omoniwa B, Hussain R, Javed M A, et al. Fog/edge computing-based IoT (FECIoT):architecture, applications, and research issues[J]. IEEE Internet of Things Journal, 2019, 6(3):4118-4149.
[10] Fu Junsong, Liu Yun, Chao H C, et al. Secure data storage and searching for industrial IoT by integrating fog computing and cloud computing[J]. IEEE Transactions on Industrial Informatics, 2018, 14(10):4519-4528.
[11] Xiong Jinbo, Ma Rong, Chen Lei, et al. A personalized privacy protection framework for mobile crowdsensing in ⅡoT[J]. IEEE Transactions on Industrial Informatics, 2020, 16(6):4231-4241.
[12] Esfahani A, Mantas G, Matischek R, et al. A lightweight authentication mechanism for M2M communications in industrial IoT environment[J]. IEEE Internet of Things Journal, 2019, 6(1):288-296.
[13] ITU-R R12-SG05. IMT vision-framework and overall objectives of the future development of IMT for 2020 and beyond [R/OL]. 2015(2015-09-16)[2020-12-03]. https://www.itu.int/rec/R-REC-M. 2083/en.
[14] 杜滢, 朱浩, 杨红梅, 等. 5G移动通信技术标准综述[J]. 电信科学, 2018, 34(8):2-9. Du Ying, Zhu Hao, Yang Hongmei, et al. Review of 5G mobile communication technology standard[J]. Telecommunications Science, 2018, 34(8):2-9.
[15] Gabriel B. Private 5G mobile networks for industrial IoT, a heavy reading white paper produced for Qualcomm [EB/OL]. 2019(2019-07-26)[2020-12-03]. https://www.qualcomm.com/media/documents/files/private-5g-networks-for-industrial-iot.pdf.
[16] 张平, 牛凯, 田辉, 等. 6G移动通信技术展望[J]. 通信学报, 2019, 40(1):141-148. Zhang Ping, Niu Kai, Tian Hui, et al. Technology prospect of 6G mobile communications[J]. Journal on Communications, 2019, 40(1):141-148.
[17] Xu Wenjun, Xu Yue, Lee C H, et al. Data-cognition-empowered intelligent wireless networks:data, utilities, cognition brain, and architecture[J]. IEEE Wireless Communications, 2018, 25(1):56-63.
[18] Zhang Ping, Xu Xiaodong, Qin Xiaoqi, et al. Evolution toward artificial intelligence of things under 6G ubiquitous X[J]. Journal of Harbin Institute of Technology (New Series), 2020, 27(3):116-135.
[19] 张平, 张建华, 戚琦, 等. Ubiquitous-X:构建未来6G网络[J]. 中国科学:信息科学, 2020, 50(6):913-930. Zhang Ping, Zhang Jianhua, Qi Qi, et al. Ubiquitous-X:constructing the future 6G networks[J]. Scientia Sinica (Informationis), 2020, 50(6):913-930.
[20] Chen Shanzhi, Liang Yingchang, Sun Shaohui, et al. Vision, requirements, and technology trend of 6G:how to tackle the challenges of system coverage, capacity, user data-rate and movement speed[J]. IEEE Wireless Communications, 2020, 27(2):218-228.
[21] Sun Wen, Liu Jiajia, Yue Yanlin. AI-enhanced offloading in edge computing:when machine learning meets industrial IoT[J]. IEEE Network, 2019, 33(5):68-74.
[22] FG-NET-2030. Network 2030:a blueprint of technology applications and market drivers and prospects [EB/OL]. 2018(2018-10-01)[2020-12-03]. https://www.researchgate.net/publication/334655833_Network_2030_A_Blueprint_of_Technology_Applications_and_Market_Drivers_Towards_the_Year_2030_and_Beyond.
[23] Balfe S, Gallery E, Mitchell C J, et al. Challenges for trusted computing[J]. IEEE Security & Privacy Magazine, 2008, 6(6):60-66.
[24] Liu Mengting, Yu F R, Teng Yinglei, et al. Performance optimization for blockchain-enabled industrial internet of things (ⅡoT) systems:a deep reinforcement learning approach[J]. IEEE Transactions on Industrial Informatics, 2019, 15(6):3559-3570.
[25] Veugen T, de Haan R, Cramer R, et al. A framework for secure computations with two non-colluding servers and multiple clients, applied to recommendations[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(3):445-457.
[26] Gu Zhifang, Chen He, Xu Pingping, et al. Physical layer authentication for non-coherent massive SIMO-enabled industrial IoT communications[J]. IEEE Transactions on Information Forensics and Security, 2020, 15:3722-3733.

Entropy Reduced Mobile Networks Empowering Industrial Applications

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	. Polar Coded Modulation for 6G System [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 1-11.
[2]	ZHU Zishen, ZHANG Chenyu, WANG Luhan, LU Zhaoming, WEN Xiangming. Open Source 5G Architecture Based on Heterogeneous Computing Acceleration [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(1): 63-68.
[3]	LIU Yu, WEN Xiang-ming, WANG Lu-han, LU Zhao-ming, DU Ke-liang. High-Performance UPF Prototype Based on VPP [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 89-95.
[4]	YAN Shi, PENG Mu-gen, WANG Wen-bo. Integration of Communication, Sensing and Computing: the Vision and Key Technologies of 6G [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(4): 1-11.
[5]	KANG Wei-min, YANG Hong-wen. Application of Constellation Shaping in Faster than Nyquist Transmission [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(1): 32-37.
[6]	WANG Xiao-xiao, DAN Zhen-lei, GU Chen-wei, ZHU Wei-ping, LIN Min. Secure Beamforming Scheme for Multi-Antenna UAV Communication Systems [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 103-109.
[7]	HE Jian-hua, ZHAO Hui, XU Xiao-bin, YAN Lei, WANG Shang-guang. Data Collection Method of Space-Based Internet of Things Based on Improved Double Level Distributed LT Code [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 118-125.
[8]	CUI Chun-feng, WANG Sen, LI Ke, DONG Jing, ZHENG Zhi-min. 6G Vision, Scenarios and Network Requirements [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 10-17.
[9]	MA Lu, LIU Ming, LI Chao, LU Zhao-ming, MA Huan. A Cloud-Edge Collaborative Computing Task Scheduling Algorithm for 6G Edge Networks [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 66-73.
[10]	ZHANG Yao-zhen, LIU Yu. A 28 GHz Transformer Matched Differential Cascode Power Amplifier Based on SiGe Technology [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 36-41.
[11]	GUAN Wan-qing, ZHANG Hai-jun, LU Zhao-ming. Intelligent Resource Allocation Algorithm for 6G Multi-Tenant Network Slicing Based on Deep Reinforcement Learning [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 132-139.
[12]	MA Ying-jie, ZHAO Geng, FAN Xiao-hong, ZHANG Xin-ran, GAO Yuan. Quantum Chaotic Extended Sequence Algorithm for 5G F-OFDM [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(2): 90-94.
[13]	WANG Ying, LI Hong-lin, FEI Zi-xuan, ZHAO Hong-yu, WANG Hong. Research and Prospect of TCP Optimization in 5G Multi-Access Networks [J]. Journal of Beijing University of Posts and Telecommunications, 2019, 42(1): 1-15.
[14]	TANG Lun, ZHAO Pei-pei, ZHAO Guo-fan, CHEN Qian-bin. Dynamic Deployment Algorithm for Service Function Chaining with QoS Guarantee [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(6): 90-96.
[15]	ZHANG Rui, ZHU Min, ZHANG Ji, FENG Dan, BAI Bao-ming. Study on 5G Incremental Redundancy HARQ Transmission Strategy [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(5): 92-97.