Evolutionary computation is a computational paradigm inspired by the principles of biological evolution, and it has found applications in various fields, including wireless communications. Evolutionary algorithms simulate the process of natural selection, reproduction, and mutation to evolve solutions to optimization problems. In the context of wireless communications, evolutionary techniques are employed to optimize and adapt wireless systems to dynamic and complex environments. Wireless communication systems often face optimization challenges, such as resource allocation, power control, and network configuration. Evolutionary computation can optimize the allocation of resources like frequency bands, time slots, and power to maximize network performance and minimize interference. Wireless communication environments are dynamic and subject to changes in user demand, interference, and channel conditions. Evolutionary computation provides adaptive solutions that can continuously evolve and adjust to changing circumstances, making it well-suited for dynamic wireless scenarios. Many wireless communication problems involve multiple conflicting objectives, such as maximizing throughput while minimizing power consumption. Evolutionary computation excels in handling multi-objective optimization, offering a set of solutions representing trade-offs between conflicting goals (Pareto front). Research challenges still exist, including the need for efficient algorithms capable of handling real-time optimization, scalability for large-scale networks, and addressing diverse and evolving wireless communication standards. In this special session, we would like to invite worldwide researcher to share and present their latest research progresses on theory, methodology and application about evolutionary computation in wireless communications, including but not limited to evolutionary algorithms, machine learning and deep learning.
Please follow the submission guideline from the IEEE WCCI 2024 Submission Website. Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Special Session on Evolutionary Computation in Wireless Communications. All papers accepted and presented at WCCI2024 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI.
Dr. Weiwei Jiang, Beijing University of Posts and Telecommunications, China (jww@bupt.edu.cn)
Weiwei Jiang received the B.Sc. and Ph.D. degrees from the Department of Electronic Engineering, Tsinghua University, Beijing, China, in 2013 and 2018, respectively. He is currently an assistant professor with the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications. His current research interests include artificial intelligence for networking and communication, satellite communication and smart grid communication.
Dr. Jianbin Mu, Zhejiang University of Technology, China
Jianbin Mu received his BSc degree from Nanjing University of Science and Technology in 2013, and his PhD degree from Shanghai Jiao Tong University in 2021. He is now a lecture in College of Information Engineering, Zhejiang University of Technology. His research interests include networked control systems, and distributed model predictive control.
Dr. Miao He, Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, China
Miao He received the Ph.D. degree from Tsinghua University in 2020, and the bachelor degree from China University of Political Science and Law in 2015. She was a visiting scholar in UC, Berkeley and a senior researcher in HEC, Lausanne. She is currently a postdoc researcher in Yanqi Lake Beijing Institute of Mathematical Sciences and Applications. Her research interests lie in ubiquitous computing, deep learning and information theory.
Dr. Weixi Gu, China Academy of Industrial Internet, China
Weixi Gu received the Ph.D. degree from Tsinghua University (THU), and the Bachelor degree from Shanghai Jiao Tong University. He was the Postdoc at University of California, Berkeley. He is currently a principal researcher at China Academy of Industrial Internet (CAII). His research interests include mobile computing, Industrial Internet of Things, and machine learning.