… prediction method to a more realistic multi-UE setting, enabling us to deploy the ML models
into the network to study the data rate performance… We simulate the mmWave network shown …

… In this article, we focus on tracking user mobility in mobile mmWave networks to predict its
moving direction according to past observations. Learning the moving direction of a mobile …

… In the process, a network controller makes handover decisions in the mmWave networks …
We consider a mmWave network wherein multiple mmWave BSs and an STA are deployed. …

… Differently from [9]–[11], [13], we study the application to the mmWave network use case,
where it is potentially possible to predict the received power degradation due to temporary link …

… performance as in LTE networks, CHO is considered an essential technology in 5G networks…
This wrong preparation is expected to occur more frequently in 5G networks since mm-wave …

… NR millimeter wave (mmWave) high-band frequencies (eg, Verizon in US). We are particularly
interested in mmWave 5G performance … up to 20 Gbps) of mmWave 5G offers exciting new …

… downlink performance. In this work, we perform a systematic study of the uplink performance
of commercial 5G mmWave networks … (1) It reveals that 5G mmWave uplink performance is …

… learns long-term spatiotemporal features and achieves superior prediction performance to
a conventional LSTM. Therefore, the ConvLSTM is also expected to work effectively for the …

… We consider a 5G mmWave network that consists … performance of DeepIA when 6 or fewer
beams are utilized. There is a minimum number of beams that are required in order to predict …

… neural network models to learn them. For that, we prove that a large enough neural network
can predict mmWave … the performance of the proposed sub-6GHz based mmWave beam …