… Machine-to-Machine (M2M) communications. Our goal is to maximize the sum-rate of
UAVs-served M2M communications … Memory (LSTM) with Generative Adversarial Networks …

… Therefore, we used the dataset to experiment whether the massive M2M communications
affected real H2H communications and the performance indicators seriously. There are above …

… networks allow communication over both short and long distances. Data collection, M2M
communication… predicting delays in M2M networks using DL and an LSTM network is discussed …

… In our modified LSTM network, we set the condition for an … LSTM network. It can be noted
that there must be neurons without edge connection in the randomly connected LSTM network, …

… self-adaptive industrial M2M communications are deployed underlaying cellular networks to
… In our proposed LSTM network, we set the condition for an edge exists between neurons 𝑖 …

… We show that LSTM outperforms all of the other models significantly for devices in the VBP
class in our simulations. Furthermore, we show that LSTM has almost the same performance …

… communications for monitoring. To meet the goal, this work suggests device-to-device (D2D)
communications, operated in cognitive radio network (… A long short term memory (LSTM) …

… Memory (LSTM) network to solve the problem, but LSTM involves … graph-based sparse LSTM
network to solve the problem … -M2M communications underlaying multiple cellular network, …

… Machine-to-Machine (M2M) communications. Our goal is to maximize the sum-rate of
UAVs-served M2M communications … Memory (LSTM) with Generative Adversarial Networks …

… network is promising to enable a plethora of new applications, including M2M communications…
require a boost in the performance of the network in terms of latency, capacity and context …