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The new concept of Beamspace Multiple Input Multiple Output system (BS-MIMO) was developed to address the issue of reduced Energy Efficiency (EE) of the traditional MIMO in millimeter-Wave (mm-Wave) wireless communication systems by decreases the large number of radio frequency chains (RF-chains) while maintaining the same number of antennas in those systems. On the other hand, a fewer RF-Chains leads to a smaller number of users that the system can serve as a result of the number of users that can be served must be equal to/or less than the RF-chains’ number. To overcome the above issue, the BS-MIMO is proposed to be integrated with Non-Orthogonal Multiple-Access (NOMA) scheme to produce the novel approach of BS-MIMO-NOMA. As a result, the novel scheme is capable of serving a group of users with correlated channels via a single RF-chain. In this paper, we will address the issue of EE of the above-mentioned communication systems. Specifically, we propose and develop an iterative algorithm with a low complexity that achieves near-perfect performance. The proposed scheme, named MSE-DPA (for Mean-Square-Error-Based Dynamic Power Allocation Algorithm), is checked to ensure this validity of Figure-of-Merit. The simulation results indicate that the EE is approximately 85% greater than that of traditional (fully-digital) MIMO systems for a certain fair system and environment scenario.

<p><span lang="EN-US">Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity.</span></p>

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