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Millimeter-wave non-orthogonal multiple access (mm-wave-NOMA) systems exploit the power domain for multiple accesses to further enhance the spectral efficiency. User clustering and power allocation can effectively exploit the potential of NOMA in mm-wave systems. This paper investigates the sum rate maximization problem of mm-wave-NOMA systems under the constraints of the total transmission power and users’ predefined rate requirements. The formulated optimization problem is a non-linear programming problem and, thus, is non-convex and challenging to solve, especially when the number of users becomes large. Sparked by the correlation features of the users’ channels in mm-wave-NOMA systems, we develop a K-means-based machine learning algorithm for user clustering. Moreover, for a practical dynamic scenario where the new users keep arriving in a continuous fashion, we propose a K …