한국통신학회 KICS

The short courses on the fundamentals and core technologies of communication networks conducted by the Communication Network Society

by Seokjoo Shin, Chosun University, South Korea

  The Communication Network Society of the KICS has been organizing essential short courses in communication and network-related topics. While there are numerous courses covering foundational knowledge of artificial intelligence and deep learning, and their applications in networks, there has been a scarcity of courses that delve deeply into fundamental concepts important to network majors and emerging issues in the field. Therefore, the Society has been preparing annual courses specifically for communication network researchers, and this year, two events were conducted.

  First, a two-day workshop covering various communication network topics was held from August 21st to 22nd. On the first day, the sessions addressed topics such as quantum artificial neural network theory and mobility applications, communication network applications of offline reinforcement learning, foundational and applied research on semantic communication, and 6G mobile communication. These sessions presented fresh and innovative directions in extending the applications of network and communication technologies. On the second day, lectures were conducted on topics like RAN-agnostic communication, network security protocols, and foundational aspects of federated learning, with a focus on applied research on wireless networks. These sessions provided in-depth understanding of the complex theories and application cases of communication technology.

  This event, conducted both online and offline, attracted the participation of over 100 researchers and students. Numerous questions were posed, creating an enthusiastic atmosphere among the participants.

  On December 6th, a workshop was conducted featuring lectures in English to facilitate the participation of foreign researchers and students. It focused on the recently prominent field of quantum neural network technology.

  Quantum neural networks leverage the high computational power of quantum computers to address machine learning and optimization problems. However, the practical application of quantum computing and quantum neural networks is still in its early stages, with ongoing research. This course aimed to provide an understanding of how quantum neural networks can be utilized to solve complex problems through future research and development.

  In the morning session, we reviewed widely used artificial neural networks, with a particular emphasis on convolutional neural networks. Additionally, participants learned essential concepts required to design artificial neural networks based on quantum computing.

  In the afternoon session, we covered the design of quantum gates for implementing quantum computing theory, along with the associated mathematical foundations. Participants also explored the configuration of various quantum circuits and their optimization through examples. In addition, we examined the structure and characteristics of quantum neural networks and explored why they can achieve better performance than traditional neural networks. The final session delved into quantum reinforcement learning, which involves implementing reinforcement learning based on quantum neural networks, with a focus on mobility applications.

  This course was conducted by Professor Joongheon Kim of Korea University. Many foreign researchers attended this online event, and a significant number of domestic researchers also participated, confirming the enthusiasm for recent quantum artificial intelligence technologies.