We have witnessed an exponential growth in commercial data services, which has led to the so-called big data era. Machine learning, one of the most promising artificial intelligence (AI) tools for analyzing this deluge of data, has been called upon in many industry and academic research areas. In this article, we briefly review big data analysis and machine learning, along with their potential applications in next-generation (NG) wireless networks. Next, we invoke big data analysis to predict the requirements of mobile users and exploit such analysis to improve the performance of "social network-aware wireless." In particular, a unified, big data-aided machinelearning framework is proposed that consists of feature extraction, data modeling, and prediction/online refinement. The main benefits of this proposed framework are that, by relying on big data that reflects both the spectral and other challenging requirements of users, we can refine the motivation, problem formulations, and methodology of powerful machine-learning algorithms in the context of wireless networks.

中文翻译：

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当机器学习遇到大数据：无线通信视角

我们见证了商业数据服务的指数级增长，这导致了所谓的大数据时代。机器学习是用于分析大量数据的最有前途的人工智能 (AI) 工具之一，已被许多行业和学术研究领域所采用。在本文中，我们简要回顾了大数据分析和机器学习，以及它们在下一代 (NG) 无线网络中的潜在应用。接下来，我们调用大数据分析来预测移动用户的需求，并利用这种分析来提高“社交网络感知无线”的性能。特别是，提出了一个统一的、大数据辅助的机器学习框架，包括特征提取、数据建模和预测/在线细化。这个提议的框架的主要好处是，