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13 ta ish

Ish: RF-CVN: Recurrent Reinforcement Learning Framework for Cognitive Vehicular Ad-Hoc Networks Routing

  1. Energy-Efficient Channel Switching in Cognitive Radio Networks: A Reinforcement Learning Approach

    Haichuan Ding, Xuanheng Li, Ying Ma +1

    Maqola20202 iqtibos
    ABI

  2. Q-Learning-Based Spectrum Access for Multimedia Transmission Over Cognitive Radio Networks

    Xin‐Lin Huang, Yuxuan Li, Yu Gao +1

    Maqola20202 iqtibos
    ABI

  3. A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): case study, cognitive radio vehicular networks with drivers

    Somayeh Bahramnejad, Naser Movahhedinia

    Maqola20212 iqtibos
    ABI

  4. Availability-Aware Channel Allocation for Multi-Cell Cognitive Radio 5G Networks

    Rami Halloush, Rana Salaimeh, Roa'a Al-Dalqamoni

    Maqola20222 iqtibos
    ABI

  5. Channel assignment and users mobility influence on primary users QoE in Cognitive Radio Network

    Shavbo Salehi, Vahid Solouk

    Maqola20222 iqtibos
    ABI

  6. A Deep Reinforcement Learning-Based QoS Routing Protocol Exploiting Cross-Layer Design in Cognitive Radio Mobile Ad Hoc Networks

    Thong‐Nhat Tran, Toan-Van Nguyen, Kyusung Shim +2

    Maqola20222 iqtibos
    ABI

  7. Distributed robust channel allocation for clustered cognitive radio-based IoT networks using graph theory

    Syed Maaz Shahid, Sungoh Kwon

    Maqola20222 iqtibos
    ABI

  8. Deep learning-based selective spectrum sensing and allocation in cognitive vehicular radio networks

    Anal Paul, Kwonhue Choi

    Maqola20232 iqtibos
    ABI

  9. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  10. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  11. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  12. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  13. Sarlavhasiz

    Boshqa1 iqtibos
    ABI