PyTorch replication of Wang et al. (2018) "Deep Reinforcement Learning for Dynamic Multichannel Access." DQN vs. the analytical optimal policy on the round-robin switching case
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Updated
Sep 19, 2026 - Python
PyTorch replication of Wang et al. (2018) "Deep Reinforcement Learning for Dynamic Multichannel Access." DQN vs. the analytical optimal policy on the round-robin switching case
Cognitive radio simulation in C++: dynamic common control channel with Markov PU prediction, underlay/interweave access, and backoff-based displacement recovery (with a verified spectrum-sensing baseline)
ICC 2027 manuscript and reproducibility package for accelerated minimax policy learning in queue-aware adversarial dynamic spectrum access
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