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Found 6 papers, 0 papers with code
Open RAN LSTM Traffic Prediction and Slice Management using Deep Reinforcement Learning
This emphasizes the importance of using the prediction rApp and distributed actors' information jointly as part of a dynamic xApp.
Attention-based Open RAN Slice Management using Deep Reinforcement Learning
As emerging networks such as Open Radio Access Networks (O-RAN) and 5G continue to grow, the demand for various services with different requirements is increasing.
Joint Path planning and Power Allocation of a Cellular-Connected UAV using Apprenticeship Learning via Deep Inverse Reinforcement Learning
The performance of this method is compared to learning from a demonstration technique called behavioral cloning (BC) using a supervised learning approach.
Triplet Loss-less Center Loss Sampling Strategies in Facial Expression Recognition Scenarios
The triplet center loss (TCL) function is applied on all dimensions of the sample's embedding in the embedding space.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN
To solve this problem, a new solution is proposed based on evolutionary-based deep reinforcement learning (EDRL) to accelerate and optimize the slice management learning process in the radio access network's (RAN) intelligent controller (RIC) modules.
Semantic-Aware Collaborative Deep Reinforcement Learning Over Wireless Cellular Networks
To address these challenges, in this paper, a novel semantic-aware CDRL method is proposed to enable a group of heterogeneous untrained agents with semantically-linked DRL tasks to collaborate efficiently across a resource-constrained wireless cellular network.
