中文标题#
移动边缘计算和开放无线接入网的进步：利用人工智能和机器学习为无线系统赋能
英文标题#
Advancements in Mobile Edge Computing and Open RAN: Leveraging Artificial Intelligence and Machine Learning for Wireless Systems
中文摘要#
移动边缘计算（MEC）和开放无线接入网（ORAN）是下一代无线通信系统发展中的变革性技术。 MEC 将计算资源推向终端用户，实现低延迟和高效处理，而 ORAN 促进了无线网络的互操作性和开放性，从而推动了创新。 本文探讨了这两个领域的最新进展，特别关注人工智能（AI）和机器学习（ML）技术如何被用于解决复杂的无线挑战。 在 MEC 中，深度强化学习（DRL）被用于优化计算卸载，确保节能解决方案并满足服务质量（QoS）要求。 在 ORAN 中，AI/ML 被用于开发用于网络切片、调度和在线训练的智能 xApps，以提高网络适应性。 本阅读报告对多篇关键论文进行了深入分析，讨论了所采用的方法，并突出了这些技术在提高网络效率和可扩展性方面的影响。
英文摘要#
Mobile Edge Computing (MEC) and Open Radio Access Networks (ORAN) are transformative technologies in the development of next-generation wireless communication systems. MEC pushes computational resources closer to end-users, enabling low latency and efficient processing, while ORAN promotes interoperability and openness in radio networks, thereby fostering innovation. This paper explores recent advancements in these two domains, with a particular focus on how Artificial Intelligence (AI) and Machine Learning (ML) techniques are being utilized to solve complex wireless challenges. In MEC, Deep Reinforcement Learning (DRL) is leveraged for optimizing computation offloading, ensuring energy-efficient solutions, and meeting Quality of Service (QoS) requirements. In ORAN, AI/ML is used to develop intelligent xApps for network slicing, scheduling, and online training to enhance network adaptability. This reading report provides an in-depth analysis of multiple key papers, discusses the methodologies employed, and highlights the impact of these technologies in improving network efficiency and scalability.
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