Deep Reinforcement Learning for Wireless 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...

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Detaylı Bibliyografya
Asıl Yazarlar: Yu, F. Richard (Yazar), He, Ying (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2019.
Imprint: Springer,
Edisyon:1st ed. 2019.
Seri Bilgileri:SpringerBriefs in Electrical and Computer Engineering,
Konular:
Wireless communication systems.
Mobile communication systems.
Artificial intelligence.
Telecommunication.
Wireless and Mobile Communication.
Artificial Intelligence.
Communications Engineering, Networks.
Online Erişim:Full-text access

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