… We are witnessing phenomenal growth in global data traffic, accelerated by the increasing
popularity of edge devices. According to the International Data Corporation, there will be 80 …

… networks. In Section VI, we introduce some typical deep learning algorithms and their
applications in wireless networks. Some future research ideas and our conclusions are provided in …

… Experimental Setup We consider a wireless federated learning system with one base station
and N = 10 devices. The total bandwidth B is set as 20 MHz, and it is equally allocated to all …

… learning in this paper to obtain the optimal IA user selection policy in cache-enabled opportunistic
IA wireless networks. … enabled opportunistic IA networks in terms of the network’s sum …

… area spanning: wireless networks and communications, machine learning, statistics, … for
the wireless networking community and empower wireless networking researchers to create …

… This paper presents an efficient accelerated learning … wireless sensor networks. The algorithm
only assumes that the signal is spatially correlated, and that the wireless sensor network is …

… Specifically, we also summarize the recent works for the wireless communication environment,
which is of great importance for training models in an IoT environment. In this survey, we …

… and military communication networks. … wireless network applications. This article aims
to provide an in-depth and comprehensive survey on TL applications in wireless networks. …

… wireless networks in which different radio nodes transmit packets to an access point (AP) via
a shared wireless … Section III-E of this paper shows that applying DRL to DLMA accelerates …

… In this paper, a heuristically accelerated reinforcement learning approach for channel
assignment (HARL CA) in WSNs is proposed to reduce the learning iterations. The proposal …