… and improving a 5G/6G wireless network. In this research work, a hybrid deeplearning method is … improvement in the wireless sensors of 5G/6G IoT networks. This proposed model is …
… requests efficiently, perform load balancing, optimum utilization of resources, and restrict network slice failure, a hybrid deeplearning-based model is proposed in this research work …
… network) according to the operators’ use case (eg, energy saving enabled by deeplearning)… Simulators are, therefore, envisioned to validate the performance of ML methods in 5G/6G …
… networks with machinelearning-enabled industrial plants to build a step towards developing this sixth sense technology, ie… network with sensors and actuators to enable the sixth sense …
… deeplearning has extended the ANN applicability and capabilities with Deep Neural Networks (DNN… that are applied for unsupervised learning or other ANN structures that are used for …
… We discuss the primary aims, vision, and trends for 6G network dimensions that include our vision of 6G and IoT and machinelearning applications for autonomous networks and …
… processes the machinelearning algorithm to address the global network optimization based … and computing overhead especially in the 5G/6G large-scaled network. Furthermore, the …
J Du, C Jiang, J Wang, Y Ren… - … Vehicular Technology …, 2020 - ieeexplore.ieee.org
… of legacy network operation routines. In response, artificial intelligence (AI), especially machinelearning (ML), is emerging as a fundamental solution to realize fully intelligent network …
… network performance, and build new revenue streams. Replacing traditional algorithms with deeplearning … Further, implementation of ML algorithms also enables the wireless network …