Toward intelligent wireless communications: Deep learning - based physical layer technologies

• DOI: 10.1016/j.dcan.2021.09.014
• Publication Date: 2021-10-06T13:14:16Z
• Authors: Siqi Liu; Tianyu Wang; Shaowei Wang
• Keywords: Physical layer; 0203 mechanical engineering; Wireless communications; 0202 electrical engineering, electronic engineering, information engineering; Deep learning; Information technology; 02 engineering and technology; Data-driven; T58.5-58.64

Advanced technologies are required in future mobile wireless networks to support services with highly diverse requirements terms of high data rate and reliability, low latency, massive access. Deep Learning (DL), one the most exciting developments machine learning big data, has recently shown great potential study communications. In this article, we provide a literature review on applications DL physical layer. First, analyze limitations existing signal processing techniques model accuracy, global optimality, computational scalability. Next, brief classical frameworks. Subsequently, discuss recent DL-based layer technologies, including both modules end-to-end systems. neural used replace single or several conventional functional modules, whereas objective latter is entire transceiver structure. Lastly, open issues research directions complexity, quality, representation, algorithm reliability.