Improving QoS for streaming data transmission over 6G networks using reconfigurable intelligent surfaces (RIS). [PDF]
Sci RepIbrahim HM +3 more
europepmc +1 more source
Deep reinforcement learning for resource allocation and scalable numerology in NR-U enabled multi-RAT HetNets. [PDF]
Sci RepElmosilhy NA +3 more
europepmc +1 more source
Multi-agent reinforcement learning driven resource game optimization for network slicing in MEC-enabled HetNets. [PDF]
Sci RepMao K.
europepmc +1 more source
Quantum inspired wavelet and Fourier feature fusion for EEG based epilepsy and seizure detection. [PDF]
Sci RepJayanthi V, Sivakumar S.
europepmc +1 more source
Polar Coding and Early SIC Decoding for Uplink Heterogeneous NOMA. [PDF]
Entropy (Basel)Wu CJ, Lin CY, Huang YC.
europepmc +1 more source
Constrained risk-sensitive deep reinforcement learning for eMBB-URLLC joint scheduling [PDF]
In this work, we employ a constrained risk-sensitive deep reinforcement learning (CRS-DRL) approach for joint scheduling in a dynamic multiplexing scenario involving enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC ...
Gan Zheng (2546086) +3 more
core
5G/6G Networks for Wireless Communication and IoT. [PDF]
Sensors (Basel)Suraci C, Araniti G.
europepmc +1 more source
Evaluation of the QoS policy model of an ordinary 5G smart city cluster with predominant URLLC and eMBB traffic. [PDF]
PLoS One, 2023 Kovtun V +3 more
europepmc +1 more source
Optimizing 5G NR link layer parameters for eMBB and URLLC applications under dynamic channel and transmission configurations. [PDF]
Sci RepPateriya S +3 more
europepmc +1 more source
Sparse Matrix Coding for URLLC
Sparse Vector Coding (SVC) has long been considered an encoding method that meets the URLLC QOS requirements. This encoding method has been widely studied and applied due to its low encoding and decoding complexity, no pilot transmission, resistance to inter-carrier interference, and low power consumption.
openaire +2 more sources