Clustered Random Beamforming and Hierarchical Modulation for Large Multi-User MIMO Downlinks

We propose a novel clustered random beamforming (RBF) scheme for multi-user multiple-input multiple-output (MIMO) downlink systems. The objective of this scheme is to maximize the number of served users while ensuring that each user meets a minimum quality of service (QoS) requirement. The system model comprises a base station (BS) equipped with multiple transmit antennas, serving multiple users. Hierarchical modulation (HM) is employed for each beam to improve spectral efficiency. To analyze the performance of the proposed scheme, we develop an analytical model by mapping the symbols of all users within a cluster onto different layers of a HM constellation. We demonstrate that the proposed scheme not only increases the number of served users but also enhances the sum-rate capacity of the system. Additionally, we discuss the selection of the optimal HM parameter based on predefined performance requirements, illustrated through a sample case. Simulation results indicate that the proposed hierarchical random beamforming (HRBF) scheme is highly promising for multi-user massive MIMO downlink systems, particularly in the context of 5G New Radio (NR) and future 6G networks and beyond.