… Apart from the non-scheduled URLLC traffic, we also need to serve scheduled URLLC traffic,
which is not necessarily of short payload size [3, 10]. The resource allocation to this traffic …

… allocation, where the reward feedback is based … resource sharing in NOMA-URLLC networks:
1) user clustering; 2) Instantaneous feedback system; and 3) Optimal resource allocation. …

… We propose a two-phase-framework, including eMBB resource allocation and URLLC … we
discuss the convergence of the URLLC outage probability during the learning process in Fig. 9…

… a heuristic resource allocation policy presented in Algorithm 1. Therein, RSUs orthogonally
allocate RBs among VUEs with the priority towards URLLC and the remaining resources are …

… In this paper, we address the coexistence problem of URLLC … URLLC users’ latency and
reliability by designing a multi-agent Q-learning algorithm for joint power and resource allocation…

… In this paper, we optimize the resource allocation and scheduling process of URLLC … coding
of the URLLC traffic. In addition, we propose a deep supervised learning approach to predict …

… for the resource allocation performed by the schedulers. … deep learning framework to
support eMBB and URLLC … the eMBB and URLLC schedulers to allocate radio resources to …

… resource management framework for meeting the strict latency and reliability requirement
of URLLC … In particular, a semi-supervised learning and deep reinforcement learning (DRL) …

… uses a reinforcement learning-… resource allocation to multiplex URLLC and eMBB
traffic on a 5G-NR time-frequency grid. The proposed algorithm is based on a multi-agent Q-learning …

… The authors model such resource allocation problem as a non-cooperative stochastic … a
deep learning approach based on double deep Q-network to approximate the optimal allocation …