208 天前 - … in such an orthogonal architecture and good system-level … for downlink 5G based
on deep learning CoMP. Unlike in [… optimal power allocation or distribution. The proposed …

214 天前 - … We introduce an intelligent architectural concept design that leverages key zerotrust …
detection system based on distributed Q-learning. Q-learning is a machine learning …

214 天前 - … Toward this end, we present a deep learning-based IDS … of the LSTM network and
the VAE in this architecture, the … [6] proposed a distributed Machine Learning (ML) scheme …

214 天前 - … ZTA and Deep Sarsa reinforcement learning algorithms. … can be used as the base
architecture for our study. Then, … • Distributed Unit (DU): The DU is in charge of radio signals…

214 天前 - … to optimization in mmWave systems, and Machine Learning (ML)-based methods
… distributed nature of learning in SL allows our approach to be suitable for O-RAN architecture…

214 天前 - … algorithms, we adopt deep reinforcement learning algorithms (DRL… in next-generation
wireless communication systems. … On the other hand, the two distributed architectures we …

214 天前 - … a promising technique for wireless transmission schemes … learn the data flow
distribution from the multimodal RTBC … MDP in our reinforcement learning architecture, expound …

214 天前 - … agent reinforcement learning (MARL) is a promising solution for many large-scale
multi-agent system (… We adopt a single RSU network architecture. Table I gives the simulation …

214 天前 - … We firstly construct the network architecture and define … of deep reinforcement
learning training. Fig. 3 and Fig. … and distributed architectures to safeguard data and user privacy. …

214 天前 - … networking paradigm is a distributed architecture, in which individual networking
devices will take control of the network … techniques and machine learning techniques are …