The combination of non-orthogonal multiple access in millimeter-wave communication called as mmWave-NOMA is capable of supporting more data streams with a larger number of users to cope up with the increasing traffic demand. In this paper, an energy-efficient scheme for downlink mmWave-NOMA systems with joint user grouping, scheduling, and optimal power allocation with the objective of energy efficiency maximization is proposed.Enhanced k-means clustering for user grouping which can handle the possible simultaneous access of network to enhance the sum throughput is proposed. Weighted sum algorithm-based scheduling where weights are calculated based on the service requirement of the users to maximize the sum rate and a proportional-based scheme of power allocation modeled as a resource allocation problem considering the beam gain and discrimination weight of each user for energy-efficient power allocation is discussed. The simulation results show that the proposed scheme is energy efficient than the conventional mmWave orthogonal multiple access systems.

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Summary Beam space multiple‐input multiple‐output (B‐MIMO) systems operating at mmWave frequency in downlink uses different beam selection techniques for reducing the required number of radio frequency chains without apparent performance loss. In this paper, a joint beam selection and user association scheme with the objective of sum rate maximization is proposed. The proposed work on beam selection is based on a norm and uncorrrelation based approach, which considers channel correlation among the users so as to avoid inter‐user interference. Two different methods for beam user association with one modelled as a balanced assignment problem based on average sum assignment method and the other method that associates an optimal beam to every user by considering their channel gain values are also proposed along with beam selection. The proposed beam assignment methods are less complex and efficient in finding a suitable beam to every user within the cell. Simulation results show that the proposed method accomplish comparable performance in terms of sum rate and energy efficiency with appreciably low computational complexity relative to the existing methods in a correlated environment.