Deep Reinforcement Learning for Wireless Networks

• Main Authors: Yu, F. Richard (Author, http://id.loc.gov/vocabulary/relators/aut), He, Ying (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: SpringerBriefs in Electrical and Computer Engineering,
• Subjects: Wireless communication systems.; Mobile communication systems.; Artificial intelligence.; Electrical engineering.; Wireless and Mobile Communication.; Artificial Intelligence.; Communications Engineering, Networks.

This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with...