… intelligence (AI) and machine learning (ML) technologies in … optimization for downlink channels
rather than learning from scratch, … Deep reinforcement learning for scheduling in cellular …

… downlink scenario, a wireless resource allocation algorithm based on Deep Reinforcement
Learning (… the complexity of scheduling problem, the DRL algorithm uses neural network as …

… the access throughput and access delay performance of … most traffic is in the downlink direction,
in M2M communications, the … metering report but may rarely receive downlink messages. …

… delay and energy efficiency of vehicular networks using … 3GPP LTE downlink scheduling
strategies in vehicle-to-… computing in vehicle networks: A deep reinforcement learning[J]. IEEE …

… Aiming at the asymmetry of uplink and downlink coverage … 是深度强化学习(DRL, deep
reinforcement learning) 可以克服高维… , user grouping and simplified downlink scheduling[J]. IEEE …

… 描述, 对应URLLC 的主要是delay critical GBR 所对应 的行. … Reinforcement learning based
scheduling algorithm for … MCS selection for throughput improvement in downlink LTE systems[C…

… It is also one of the four uplink and downlink license holders … programs may face a demand
schedule which is much flatter … For the last couple of years, TVB experienced slow growth to …

… LI Sen, LI Baokui, GENG Qingbo 71 Tensor Product Model Transformation Based
Integral Sliding Mode Control with Reinforcement Learning Strategy .............................................. …

: 近年来, 基于云控制技术的天空地异构多运动体系统的研究得到学界的关注, 天空地跨域多运动
体通过互联, 互通, 互操作, 能够实现信息共享与融合, 行为交互与协调, 任务协同与合作, 促进…

… An efficient downlink radio resource allocation with carrier … Blockchain and deep
reinforcement learning empowered … Delay-minimization routing for heterogeneous VANETs with …