This paper considers the time-varying characteristic of the downlink channels, and proposes a complex-valued ResNet-based deep Q-learning (DQN) algorithm.
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Oct 19, 2024 · In this paper, we aim to maximize the sum-rate at UE side by jointly performing the active beamforming design at BS side and the passive phase ...
The results reveal that the proposed complex-valued deep reinforcement learning (DRL) approach shows stronger generalization ability in comparison with the ...
Beamforming. Conference Paper. Complex-valued Reinforcement Learning Based Dynamic Beamforming Design for IRS Aided Time-Varying Downlink Channel. June 2022.
Jun Yu's research works | Tongji University and other places
www.researchgate.net › Jun-Yu-2171152...
Jun Yu's 4 research works with 7 citations, including: Complex-valued Reinforcement Learning Based Dynamic Beamforming Design for IRS Aided Time-Varying ...
Oct 28, 2024 · We show that the DRL agent is capable of exploiting the time-domain correlations of the channels for constructing accurate TPC matrices. This is ...
Nov 7, 2020 · Our objective is to gain the maximum value of sum rate in the time-varying channel under the some constraints about cut-off signal-to-interference and noise ...
Missing: Complex- IRS Aided
Apr 16, 2024 · In addition, the algorithm has the ability to deal with fixed and dynamic channels, which gives deep reinforcement learning methods an edge over ...
Abstract—This paper studies a secure satellite-terrestrial com- munication system assisted by a hybrid intelligent reflecting surface (IRS).
Oct 31, 2023 · This paper studies a secure satellite-terrestrial communication system assisted by a hybrid intelligent reflecting surface (IRS).