… average, exponential smoothing, and machine learning. The simple equal scheme assumes
… The machine learning schemes typically require training process, thus will inevitably raise …

… resource scheduling and allocation were found to be the key problems of eMBB and URLLC
… mechanisms between eMBB and URLLC traffic for resource scheduling. We followed the …

… allocation in URLLC with deep learning, where the NNs are trained either online or offline.
Simulation results showed that the proposed online learning … the resource allocation is in …

… for resource allocation of eMBB and URLLC coexisting systems. In [27], the joint eMBB and
URLLC resource allocation … His research interests include URLLC and machine learning for …

… the wideband THz resource block allocation. To solve this problem, we adopt a supervised
learning approach relying on optimization, deep learning and ensemble learning methods. …

… deep neural networks (DNN) is effective in solving numerical optimization in real time for
time-sensitive resource allocation … latent function with unsupervised deep learning, where the …

… proper dynamic resource allocations, while there is no GFBR for a Non-GBR QoS flow. To
allocate resources to a PDU session, the CN sends a PDU Session Resource Request to a …

… As far as related research in URLLC resource allocation and load … Learning (SL), Unsupervised
Learning (UL) and mainly the cutting-edge RL and Deep Reinforcement Learning (DRL), …

… their own QoS requirements but also reduces the interference to others, leading to the optimal
resource allocation solution of the vehicular network communication system. In the power …

… This relation was used to optimize resource allocation for short packet transmissions in
URLLC [7,8,24]. For most of these problems, the QoS constraints do not have closed-form …