# Intelligent Transmission Control Scheme for 5G mmWave Networks Employing Hybrid Beamforming
## 4 Proposed Work
### Hybrid Beamforming for Multi-User mmWave Networks
#### 4.3.1 Multi-User Beamforming Strategies for mmWave Networks  
Millimeter-wave (mmWave) systems can support many antennas based on half-wavelengths in a small size. Consistently, high-gain beamformers are recommended to offset their significant path loss. HB consists of a direct arrangement of antenna elements. In the RF domain, phase modulators are typically employed in conjunction with digital beamforming for millimeter-wave communications. The hybrid transmits and receives beamforming, which was optimized iteratively using the \"minimum mean-square-error\" criterion. Analog beamformers are optimized using nonlinear manifold optimization techniques. The authors have created multiple methods for constructing analog beamformers to advance multi-user uplink mmWave communication. Recently, various HB algorithms have been presented for multi-user downstream mmWave communications. They suggest hybrid beamforming algorithms that are based on \"zero-forcing (ZF)\". Assuming the number of users equals the number of RF chains, the resulting ZF beamforming problem might not be well-posed. To produce an established difficulty, the number of users was reduced to the number of transmitting antennas. Hybrid beamforming based on \"regularized zero-forcing (RZF)\" was examined; channel statistics were used to define the analog and baseband beamformer design, and equal-power-constructed RZF beamforming was used to decide the beamforming technique. The impact of combining HB and \"non-orthogonal multiple access (NOMA)\" on the total data rate achievable when dealing with beam misalignment was investigated in a scenario where each \"radio frequency (RF)\" chain serves multiple users. Additionally, the issue of maximizing energy efficiency in both concerns has also been raised regarding the multi-user mmWave networks' uplink and downlink. They first discussed the NOMA concept to match two users per RF chain. After that, they used a variation of the convex function programming approach to handle the interconnected optimization of power distribution. For both single-cell and twin-cell applications, they provide a time-fraction oriented mmWave transmission method that enables an unparalleled max-min user rate to be achieved using an integrated beamforming. There are the following three noteworthy advancements in the present investigation:  
* In the greatest common scenario where the user count is the highest, the paper demonstrates that the number of RF chains should not exceed a certain amount in a basic HB configuration, which corresponds to the RZF baseband beamforming being used by the analog beamforming to adapt to the channel's stage efficient transmission quality. It can achieve performance close to the ideal fully digital ZF beamforming in terms of the channel maximum and minimum rates of users. The best fully digital ZF system uses beamforming that can also achieve the capacity of massive MIMO channels according to an important finding about a constrained quantity of RF chains that does not appreciably reduce the amount of mmWave channels, provided the total RF quantity is more than the number of user links. * In cases where the number of users doubles, we design a time fraction based on the quantity of RF chains. HB is enabled by a mmWave scheme created to attain an unmatched maximum-minimum user rate. * In the case of a twin-cell mmWave communication system experiencing an introduced time-sharing scheme to mitigate strong interference between cells, an mmWave-based system can achieve high performance and ensure that the highest possible user rating is achieved while maintaining a minimum user rate; with consideration for the number of workers, the cell value is less than or equivalent to double the RF value chains that are employed at the primary position. We calculate the best power distribution to exploit the minimum rate of the employers. In conclusion, simple path-following algorithms with fast convergence are created to calculate the optimal power.