RIS-aided proactive mobile network downlink interference suppression: A deep reinforcement learning approach
… reinforcement learning (DRL), we propose an asynchronous advantage actor–critic (A3C)-based
method … a region can significantly facilitate interference suppression. The proposed A3C…
method … a region can significantly facilitate interference suppression. The proposed A3C…
Reinforcement learning-based downlink interference control for ultra-dense small cells
… a reinforcement learning based power control scheme to suppress downlink inter-cell interference
and … Altman, “A cooperative reinforcement learning approach for inter-cell interference …
and … Altman, “A cooperative reinforcement learning approach for inter-cell interference …
Reinforcement learning based inter-user-interference suppression in full-duplex networks
D Korpi, MA Uusitalo - 2021 IEEE 93rd Vehicular Technology …, 2021 - ieeexplore.ieee.org
… training, it is shown that the RL algorithm can identify groups where the interference from
the uplink UEs to the downlink … In addition to such methods, also interference alignment [8]–[10] …
the uplink UEs to the downlink … In addition to such methods, also interference alignment [8]–[10] …
The Reinforcement Learning based Interference Whitening Scheme for 5G
K Park, H Kim, D Kwon, H Kim, H Kang… - 2021 IEEE 93rd …, 2021 - ieeexplore.ieee.org
… complexity linear method to suppress colored interference in a … interference suppression
scheme called as Reinforcement … on Reinforcement Learning in order to maximize the downlink …
scheme called as Reinforcement … on Reinforcement Learning in order to maximize the downlink …
Toward interference suppression: RIS-aided high-speed railway networks via deep reinforcement learning
… RIS-aided multiuser downlink MISO … interference suppression. Last but not least, the
performance gain of the random phase shift approach is evidently lower than other three approaches…
performance gain of the random phase shift approach is evidently lower than other three approaches…
Downlink transmit power control in ultra-dense UAV network based on mean field game and deep reinforcement learning
… reinforcement learning-based MFG (DRL-MFG) algorithm is proposed to suppress the
interference … include wireless communications, game theory, and machine learning. He was the …
interference … include wireless communications, game theory, and machine learning. He was the …
Deep Reinforcement Learning for Interference Management in UAV-based 3D Networks: Potentials and Challenges Mojtaba
… We then discuss novel approaches to scale the algorithms … alleviate the interference to
neighboring cells by suppressing the … that interference issues exist in both uplink and downlink …
neighboring cells by suppressing the … that interference issues exist in both uplink and downlink …
A reinforcement learning approach to energy efficiency and QoS in 5G wireless networks
… downlink traffic on account of its predominance in LTE/eLTE networks and the fact that in such
networks, there is no interference between downlink … well” and suppressing strategies with …
networks, there is no interference between downlink … well” and suppressing strategies with …
Joint interference alignment and power control for dense networks via deep reinforcement learning
… approaches to solve the interference problem is interference … In this letter, we investigate
the interference suppression in … SYSTEM MODEL We consider a downlink two-tier HetNet in …
the interference suppression in … SYSTEM MODEL We consider a downlink two-tier HetNet in …
Multiple access in cell-free networks: Outage performance, dynamic clustering, and deep reinforcement learning-based design
… be used to suppress some of the in-band interfering signals [28]–[30]. In [28], downlink UEs
… In this paper, we adopt this approach for a cell-free network architecture, propose a dynamic …
… In this paper, we adopt this approach for a cell-free network architecture, propose a dynamic …
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