Real-World Wireless Network Modeling and Optimization: From Model/Data-Driven Perspective

LI Yang; ZHANG Shutao; REN Xiaohui; ZHU Jianhang; HUANG Jiajie; HE Pengcheng; SHEN Kaiming; YAO Zhiqiang; GONG Jie; CHANG Tsunghui; SHI Qingjiang; LUO Zhiquan

doi:10.1049/cje.2022.00.191

Volume 31 Issue 6

Nov. 2022

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Article Navigation > Chinese Journal of Electronics > 2022 > 31(6): 991-1012

LI Yang, ZHANG Shutao, REN Xiaohui, et al. “Real-World Wireless Network Modeling and Optimization: From Model/Data-Driven Perspective”. Chinese Journal of Electronics, vol. 31 no. 6. doi: 10.1049/cje.2022.00.191

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LI Yang, ZHANG Shutao, REN Xiaohui, et al. “Real-World Wireless Network Modeling and Optimization: From Model/Data-Driven Perspective”. Chinese Journal of Electronics, vol. 31 no. 6. doi: 10.1049/cje.2022.00.191

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Real-World Wireless Network Modeling and Optimization: From Model/Data-Driven Perspective

doi: 10.1049/cje.2022.00.191

LI Yang^{1, 2
,},
ZHANG Shutao^{3, 1
,},
REN Xiaohui^4
,,
ZHU Jianhang^5
,,
HUANG Jiajie^5
,,
HE Pengcheng^6
,,
SHEN Kaiming^3
,,
YAO Zhiqiang^4
,,
GONG Jie^5
,,
CHANG Tsunghui^{3, 1
,},
SHI Qingjiang^{6, 1
,},
LUO Zhiquan^{3, 1, 2
,}

1.
Shenzhen Research Institute of Big Data, Shenzhen 518172, China
2.
Pengcheng Lab, Shenzhen 518055, China
3.
School of Science and Engineering, The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China
4.
College of Mathematics and Computational Sciences, Xiangtan University, Xiangtan 411105, China
5.
School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China
6.
School of Software Engineering, Tongji University, Shanghai 201804, China

Funds: This work was supported by the National Key R&D Program of China (2022YFA1003900), the National Natural Science Foundation of China (62101349, 62001411, 62171481), the Special Support Program of Guangdong (2019TQ05X150), and the Natural Science Foundation of Guangdong Province (2021A1515011124)

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Author Bio:
Yang LI received the Ph.D. degree in Department of Electrical and Electronic Engineering from The University of Hong Kong in 2019. From 2019 to 2020, he has been a Senior Research Engineer in Huawei Noah’s Ark Lab. He is the winner of the 2020 Innovation Pioneer Award of Huawei. Currently, he is a Research Scientist with Shenzhen Research Institute of Big Data. His research interests include radio resource management, learning to optimize, and large-scale optimization. (Email: liyang@sribd.cn)

Shutao ZHANG received the B.E. degree in communication engineering and the M.E. degree in electronics and communication engineering from Sun Yat-sen University, Guangzhou, China, in 2018 and 2020, respectively. He is currently pursuing the Ph.D. degree with The Chinese University of Hong Kong, Shenzhen. He is also enrolled in the Joint Education Program of the Shenzhen Research Institute of Big Data (SRIBD). From 2022 to 2023, he join Peng Cheng Laboratory as a visiting student. His research interests include sparse signal processing, digital twin network and wireless channel modeling. He received the IEEE ISWCS Best Paper Award in 2022. (Email: shutaozhang@link.cuhk.edu.cn)

Xiaohui REN was born in 1996. She received the B.S. degree from School of Mathematics and Information Science, Hebei University, in 2022. She is now a Ph.D. candidate in School of Mathematics and Computational Sciences of Xiangtan University since 2022. Her research interests include network optimization, traffic prediction and modeling. (Email: 2654966935@qq.com)

Jianhang ZHU was born in Henan, China, in 1999. He received the B.E. degree in communication engineering from the School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China, in 2021, where he is currently pursuing the M.E. degree with the School of Computer Science and Engineering. His research interests include age of information, edge computing, and the Internet of Things. (Email: zhujh26@mail2.sysu.edu.cn)

Jiajie HUANG was born in Guangzhou, China, in 1999. He received the B.E. degree in communication engineering from the School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou, China, in 2021, where he is currently pursuing the M.E. degree with the School of Computer Science and Engineering. His research interests include age of information, intelligent network, and the Internet of Things. (Email: huangjj7@mail2.sysu.edu.cn)

Pengcheng HE was born in 1998. He received the B.S. degree from School of Software Engineering, Tongji University, in 2020. He is now a Ph.D. candidate in the School of Software Engineering, Tongji University since 2020. His research interests include optimization, machine learning, and signal processing. (Email: steven_he@tongji.edu.cn)

Kaiming SHEN received the B.E. degree in information security and the B.S. degree in mathematics from Shanghai Jiao Tong University, Shanghai, China in 2011, then the M.S. and Ph.D. degrees in electrical and computer engineering from University of Toronto, Ontario, Canada in 2013 and 2020, respectively. Since 2020, he has been an Assistant Professor with the School of Science and Engineering at The Chinese University of Hong Kong (Shenzhen), China. His main research interests include optimization, wireless communications, and information theory. Dr. Shen received the IEEE Signal Processing Society Young Author Best Paper Award in 2021. (Email: shenkaiming@cuhk.edu.cn)

Zhiqiang YAO received the M.S. and Ph.D. degrees from the School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China, in 2004 and 2010, respectively. He was a Postdoctoral Fellow at the Chinese University of Hong Kong, Shenzhen, China, in Prof. Zhi-Quan Luo’s research group. Since 2010, he has been with Xiangtan University, where he is currently a Full Professor and the Dean in the College of Automation and Electronic Information. His research interests include signal processing, communication, localization, and optimization. He is Senior Member of the Chinese Institute of Electronics and IEEE. (Email: yaozhiqiang@xtu.edu.cn)

Jie GONG received the B.S. and Ph.D. degrees in the Department of Electronic Engineering in Tsinghua University, Beijing, China, in 2008 and 2013, respectively. From Jul. 2012 to Jan. 2013, he visited the Institute of Digital Communications, University of Edinburgh, Edinburgh, UK. From Jul. 2013 to Oct. 2015, he worked as a postdoctorial Scholar in Tsinghua University. He is currently an asSociate Professor in the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China. He served as Editor for IEEE Transactions on Green Communications and Networking, Workshop Co-chair for IEEE/CIC ICCC 2022 and Publicity Co-chair for IEEE WCNC workshop since 2018. He was a co-recipient of the Best Paper Award from IEEE Communications Society Asia-Pacific Board in 2013. His research interests include green communications and networking, energy harvesting technology, mobile edge computing, and age of information. (Email: gongj26@mail.sysu.edu.cn)

Tsunghui CHANG received the B.S. degree in electrical engineering and the Ph.D. degree in communications engineering from the Taiwan Tsing Hua University, Hsinchu, China, in 2003 and 2008, respectively. He currently is an Associate Professor with the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China. Prior to being a Faculty Member, he held research positions with Taiwan Tsing Hua University, from 2008 to 2011, and the University of California, Davis, CA, USA, from 2011 to 2012. His research interests include signal processing and optimization problems in data communications, machine learning, and big data analysis. Dr. Chang is an Elected Member of IEEE Signal Processing Society (SPS) Signal Processing for Communications and Networking Technical Committee (SPCOM TC), the Funding Chair of IEEE SPS Integrated Sensing and Communication Technical Working Group (ISAC TWG), and the IEEE SPS Regional Director-at-Large of Region 10. He was on the Editorial Board for main SP journals, including an Associate Editor (2014C2018) and Senior Area Editor since February 2021 of the IEEE Transactions on Signal Processing, and an Associate Editor for the IEEE Transactions on Signal and Information Processing over Networks (2015C2018) and IEEE Open Journal of Signal Processing since January 2020. Dr. Chang was the recipient of the Young Scholar Research Award of National Taiwan University of Science and Technology in 2014, IEEE ComSoc Asian-Pacific Outstanding Young Researcher Award in 2015, Outstanding Faculty Research Award of SSE, CUHKSZ, in 2021, and IEEE SPS Best Paper Award in 2018 and 2021. (Email: tsunghui.chang@ieee.org)

Qingjiang SHI received the Ph.D. degree in electronic engineering from Shanghai Jiao Tong University, Shanghai, China, in 2011. From Sept. 2009 to Sept. 2010, he visited Prof. Z.-Q. (Tom) Luo’s research group at the University of Minnesota, Twin Cities. In 2011, he worked as a Research Scientist at Bell Labs China. From 2012, He was with the School of Information and Science Technology at Zhejiang Sci-Tech University. From Feb. 2016 to Mar. 2017, he worked as a Research Fellow at Iowa State University, USA. From Mar. 2018, he is currently a Full Professor with the School of Software Engineering at Tongji University. He is also with the Shenzhen Research Institute of Big Data. His interests lie in algorithm design and analysis with applications in machine learning, signal processing, and wireless networks. So far he has published more than 80 IEEE journals and filed about 40 national patents. Dr. Shi was an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING. He was the recipient of IEEE Signal Processing Society Best Paper Award in 2022, the Huawei Technical Cooperation Achievement Transformation Award (2nd Prize) in 2022, the Huawei Outstanding Technical Achievement Award in 2021, the Golden Medal at the 46th International Exhibition of Inventions of Geneva in 2018, the First Prize of Science and Technology Award from China Institute of Communications in 2017, the National Excellent Doctoral Dissertation Nomination Award in 2013, the Shanghai Excellent Doctorial Dissertation Award in 2012, and the Best Paper Award from the IEEE PIMRC’09 conference. (Email: shiqj@tongji.edu.cn)

Zhiquan LUO (corresponding author) received the B.S. degree in applied mathematics from Peking University, China, and the Ph.D. degree in operations research from MIT in 1989. From 1989 to 2003, he held a faculty position with the ECE Department of McMaster University, Canada. He held a tier-1 Canada Research Chair in information processing from 2001 to 2003. After that, he has been a Full Professor at the ECE Department, University of Minnesota and held an endowed ADC Chair in digital technology. Currently, he is the Vice President (Academic) of The Chinese University of Hong Kong (Shenzhen) and the Director of Shenzhen Research Institute of Big Data (SRIBD). Prof. Luo is a Fellow of IEEE and SIAM. He was elected to Fellow of Royal Society of Canada in 2014 and a Foreign Member of the Chinese Academy of Engineering (CAE) in 2021. He received four best paper awards from the IEEE Signal Processing Society, one best paper award from EUSIPCO, the Farkas Prize from INFORMS and the prize of Paul Y. Tseng Memorial Lectureship in Continuous Optimization as well as some best paper awards from international conferences. In 2021, he was awarded 2020 ICCM Best Paper Award by International Consortium of Chinese Mathematicians. He has published over 350 refereed papers, books and special issues. Prof. Luo has served as an Associate Editor for many internationally recognized journals and the Editor-in-Chief for IEEE Transactions on Signal Processing. His research mainly addresses mathematical issues in information sciences, with particular focus on the design, analysis and applications of large-scale optimization algorithms. (Email: luozq@cuhk.edu.cn)
Received Date: 2022-06-30
Accepted Date: 2022-11-03

Available Online: 2023-01-16

Publish Date: 2022-11-05

Abstract

Abstract

With the rapid development of the fifthgeneration wireless communication systems, a profound revolution in terms of transmission capacity, energy efficiency, reliability, latency, and connectivity is highly expected to support a new batch of industries and applications. To achieve this goal, wireless networks are becoming extremely dynamic, heterogeneous, and complex. The modeling and optimization for the performance of realworld wireless networks are extremely challenging due to the difficulty to predict the network performance as a function of network parameters, and the prohibitively huge number of parameters to optimize. The conventional network modeling and optimization approaches rely on drive test, trial-and-error, and engineering experience, which are labor intensive, error-prone, and far from optimal. On the other hand, while the research community has spent significant efforts in understanding the fundamental limits of radio channels and developing physical layer techniques to operate close to it, very little is known about the performance limits of wireless networks, where millions of radio channels interact with one another in complex manners. This paper reviews the very recent mathematical and learning based techniques for modeling and optimizing the performance of real-world wireless networks in five aspects, including channel modeling, user demand and traffic modeling, throughput modeling and prediction, network parameter optimization, and IRS empowered performance optimization, and also presents the corresponding notable performance gains.
- Mathematical methods,
- Learning based methods,
- Network performance modeling,
- Network performance optimization

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References(141)

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