結合智慧5G網路的行動通訊：現況、應用與展望

在本文中，我們試圖強調人工智慧（Artificial Intelligence, AI）是5G時代革命性技術中最基本的特徵之一，在蜂巢式網路中，幾乎每個重要面向都有初步智慧的出現。然而，面對日益複雜的架構問題和蓬勃發展的新興服務，如果缺乏完整的AI功能，則仍然不足以充分用於5G蜂巢式網路。因此，我們除了介紹AI基本概念以及討論AI與5G蜂巢式網路候選技術之間的關係之外，並充分討論如何將感測、學習、優化與智慧互動架構交互結合，以促進AI賦能因素對5G蜂巢式網路的成功運用。其次，我們提出一款彈性、可快速部署的跨層AI框架，以因應5G更高版本的即將到來（Yao, Sohul, Marojevic, and Reed, 2019）。第三，我們提供AI賦能5G服務的應用案例，其中容納重要的5G特定功能，同時也討論出AI的未來價值，以求更完美網路演變歷程的實現。

關鍵字

5G時代；人工智慧；行動通訊；服務應用；無線接取網路

並列摘要

In this paper, we try to emphasize that artificial intelligence (AI) is one of the most basic features of the revolutionary technology of the fifth generation (5G) era. In the cellular networks, almost every important aspect has appeared initial intelligence. However, in the face of increasingly complex architectural problems and thriving new service requirements, if in lack of full AI functionality, they are still not sufficient for 5G cellular networks. Therefore, we further introduce the basic concepts of AI and discuss the relationship of candidate technologies between AI and 5G cellular networks. In addition, this article discusses the interconnections among sensing, learning, optimization, and smart interaction architecture to facilitate the successful use of these enabling factors. Secondly, we propose a flexible, fast-deployable, and cross-layer AI framework to meet the needs of the upcoming 5G higher version. Third, we provide an AI-enabled 5G service application example that accommodates important 5G specific features and we also discuss the future value of AI to achieve a more perfect network evolution.

並列關鍵字

5G era ； artificial intelligence ； mobile communication ； service application ； radio access network

參考文獻

Aly R. M., Zaki A., Badawi W. K., and Aly M. H., 2019, “Time Coding OTDM MIMO System Based on Singular Value Decomposition for 5G Applications,” Applied Sciences, 9(13), 2691. doi:10.3390/app9132691

Andrews J. G., Buzzi S., Choi W., Hanly S. V., Lozano A., Soong A. C. K., and Zhang J. C., 2014, “What Will 5G Be?” IEEE Journal on Selected Areas in Communications, 32(6), 1065-1082. doi:10.1109/JSAC.2014.2328098

Aziz N. A. A., Ibrahim Z., Aziz N. H. A., and Aziz K. A., 2019, “Simulated Kalman Filter Optimization Algorithm for Maximization of Wireless Sensor Networks Coverage,” in Proceedings of the 2019 International Conference on Computer and Information Sciences (ICCIS), Sakaka, Saudi Arabia: IEEE. doi:10.1109/ICCISci.2019.8716387

Chandra A., Khatri S. K., and Simon R., 2019, “Filter-Based Attribute Selection Approach for Intrusion Detection Using K-Means Clustering and Sequential Minimal Optimization Techniq,” in Proceedings of the 2019 Amity International Conference on Artificial Intelligence (AICAI), Dubai, United Arab Emirates: IEEE. doi:10.1109/AICAI.2019.8701373

Ge X., Tu S., Mao G., Wang C.-X., and Han T., 2016, “5G Ultra-Dense Cellular Networks,” IEEE Wireless Communications, 23(1), 72-79. doi:10.1109/MWC.2016.7422408

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結合智慧5G網路的行動通訊：現況、應用與展望

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