… In this work we focus on the analysis of different machine learning algorithms (and their
potential) over a single mmWave channel, leaving multi-channel scenarios as an extension that …

… We model the mmWave propagation channel with N C = 8 clusters and each cluster involves
N P = 10 paths. The angle spread of θ k and φ k are both equal to 7.5 and each path factor …

… a mmWave throughput estimation scheme using an online machine learning algorithm and
… a testbed consisting of IEEE 802.11ad mmWave wireless local area network devices and an …

… (CE) optimization in machine learning and the relative error … as a training process in machine
learning, in which the training … For any channel vector, we adopt the geometric channel …

… mmWave MIMO channel and carrier frequency offset (CFO), this paper proposes a novel
online machine learning… thus establish a novel online machine learning-based physical layer …

… In reality, due to the sparsity and high directional nature of the mmWave channel, the LoS
path is the predominant mode of propagation [15]. As such, we assume that the LoS path …

… In this article, we leverage machine learning (ML) techniques to learn the mobility of users
… changes may cause serious channel variation in mobile mmWave communications, in this …

… For example, in [30], the authors propose a K-means-based user grouping scheme for
downlink mmWave-NOMA, which uses the normalized channel correlation as a clustering …

… CHANNEL STATE INFORMATION We consider a MIMO mmWave communications network
… The SBSs use the mmWave links to transmit data to the UE. We denote the set of UE with L …

… of deep and machine learning-based analog beam selection schemes for the uplink of a
multi-user MIMO mmWave … under mm-wave channels,’’ IEEE J. Sel. Topics Signal Process., vol. …