… reuse, and it is capable of achieving concurrent transmissions from multiple other VUEs …
In this paper, we propose a machine learning (ML) approach to achieve an efficient and fast …

… beams, and it is capable of achieving concurrent transmissions from multiple other UAV
BSs … Fortunately, machine learning (ML) is suitable for decreasing complexity in codeword …

… To sum up, LiM inherits the benefits from concurrent transmissions and a machine learning
scheme, outperforming our baseline protocol Glossy in the light of energy efficiency while …

… In this work, we aim to propose a novel method for concurrent transmission in mmWave … of
UserE under concurrent transmission. Then, we establish a machine learning training dataset …

… transmission scheduling with the QoS support along with the issues involved in short data
packet transmission… for the applications of emerging machine learning (ML) techniques in ultra-…

… LTE transmissions, multiple Wi-Fi transmissions, or concurrent LTE and Wi-Fi transmissions.
… We consider machine learning models that take time-series data of width w as input, giving …

… In this case study, the consistency of UAVs with blockchain and machine learning
techniques is restrained by the number of data points. Since UAVs travel a limited distance, it is …

… , called edge learning, has emerged, which crosses and revolutionizes two disciplines:
wireless communication and machine learning. A major theme in edge learning is to overcome …

… To this end, we propose Less is More (LiM), a machine learning-based data dissemination
protocol for low-power multi-hop WSNs. In designing LiM, we utilize a reinforcement …

… [18] introduced a multi-hop based concurrent transmission technique in order to mitigate
the probability of simultaneous packets transmissions of LoRa nodes. In addition, Zhu et al. [19] …