5G多媒体通信中的机器学习

D. Milovanovic, Z. Bojkovic, D. Kukolj
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引用次数: 0

摘要

机器学习(ML)已经发展到这种技术可以增强通信并实现第五代(5G)无线网络的程度。ML非常适合深入了解使用大量数据的复杂网络,以及预测和主动适应动态无线环境。机器学习已经成为移动宽带通信的一项关键技术。沉浸式媒体中的深度学习(DL)是一个特例。通过本章,我们的目标是展示机器学习的开放式研究挑战和应用。在5G主要eMBB、mMTC和uHSLLC服务的背景下,探索基于机器学习的解决方案方法的潜力,同时评估未来研究的开放式问题,包括算法和数据格式的标准化活动。
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Machine Learning in 5G Multimedia Communications
Machine learning (ML) has evolved to the point that this technique enhances communications and enables fifth-generation (5G) wireless networks. ML is great to get insights about complex networks that use large amounts of data, and for predictive and proactive adaptation to dynamic wireless environments. ML has become a crucial technology for mobile broadband communication. Special case goes to deep learning (DL) in immersive media. Through this chapter, the goal is to present open research challenges and applications of ML. An exploration of the potential of ML-based solution approaches in the context of 5G primary eMBB, mMTC, and uHSLLC services is presented, evaluating at the same time open issues for future research, including standardization activities of algorithms and data formats.
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