# A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
## 3 An In-Depth Analysis of the mmWave Hybrid Beamforming Landscape
### User
#### 3.1.2 Muti-User
* **Energy-Efficient Beamforming** The signal processing of each link of the analog precoding matrix determines the overall power usage. This non-convex energy maximization issue is a challenging task. To solve this, there is a need to first reduce the issue to its most basic components: the ratio of the feasible rate to the power dissipation. Then, the digital and analog precoding matrices address the achievable rate issue and are updated in a cyclical fashion. This method facilitates the transformation of the issue into a convex one, for which a solution is readily solvable [32]. * **Non-iterative Processing Beamforming** Low complexity in mm-wave channels is achieved by using a simple hybrid beamforming method based on non-iterative processing for multi-user downlink. In order to merge analog (RF component only) and digital (baseband) precoding, this design employs the hybrid regularized channel diagonalization (HRCD) technique [33]. * **Co-ordinated Beamforming** The hybrid block-diagonalization (BD) precoder uses feedback for a multi-user MIMO architecture and is designed for both base stations and users. In order to achieve array gain using beamforming principles, it employs the Equal Gain Transmission (EGT) method. On mm-wave multi-user MIMO downlink systems, coordinated beamforming in hybrid schemes may send several transmission streams simultaneously. The design takes into account both the base station and the users. Also, the Modified Generalized Low-Rank Approximation of Matrices (MGLRAM) provides a viable and effective basis for this beamforming. The coordinated beamforming approach is competitive with or even surpasses the completely digital technique in terms of performance [34]. * **Efficient Array Gain Beamforming** The greedy truncated power technique is used for downstream multi-user MIMO communication in order to achieve efficient array gain based on hybrid beamforming. This method may increase the effective array gain at mm-wave frequencies by sending several streams to each user. In terms of throughput, this method surpasses equal-gain-transmission (EGT) with different numbers of phase shifters [35]. * **Reduced-Interference Beamforming** To minimize interference, multi-user MIMO employs a downlink method based on successive interference cancelation (SIC). Even with channel estimate inaccuracy and low-resolution (2-bit) phase shifters, this method outperforms zero-forcing in terms of complexity and spectral efficiency when dealing with interference and noise power [36]. * **Full-Stack Beamforming** Using hybrid beamforming, the network capacity may be increased by sending numerous data streams concurrently to different users. If just analog beamforming is used, the SINR drops dramatically. When it comes to MMSE flat-frequency beamforming, less feedback means less capacity to minimize interference, while more feedback means more interference. The scheduler of multi-user MIMO, the beamforming architecture, and retransmissions work together to overcome this obstacle in full-stack hybrid beamforming [37].