# A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
## 4 Current Research Trends, Challenges, Solutions, and Future Research Directions  
### Current Research Trends  
Millimeter-wave (mmWave) hybrid beamforming is a critical technology for enabling high-data-rate communication systems such as 5G and beyond. Hybrid beamforming is an attractive approach because it balances the trade-off between the hardware complexity of digital beamforming and the performance of analog beamforming. Here are some of the current trends [126; 127; 128; 129; 130] in this area, as highlighted in Figure 12 below:  
* Energy-Efficient Solutions: With the increased power consumption associated with high-frequency operations and large antenna arrays, there is a trend toward developing power-efficient beamforming solutions. This includes both circuit-level innovations and algorithmic optimizations to minimize power usage without sacrificing  
Figure 12: Current trends in Mw-wave hybrid beamforming field.  
performance. It also includes focusing on designs that minimize power consumption without significantly compromising on performance, which is crucial for the widespread deployment of mmWave technologies in mobile devices and base stations.
* AI- and Machine Learning-Driven Optimization: There is a growing interest in utilizing artificial intelligence (AI) and machine learning (ML) algorithms to optimize hybrid beamforming, especially in dynamic environments. These techniques can help with channel estimation, beam selection, and adaptive beamforming strategies that react to changing conditions and user demands.
* AI-Driven Beam Management: AI and machine learning algorithms are being explored to dynamically manage beamforming in real time, taking into account user mobility and varying channel conditions. AI can optimize beam direction and power allocation efficiently, potentially outperforming traditional algorithms.
* Beamforming Protocols: Research into new protocols and signal processing techniques aimed at faster and more accurate beam alignment is ongoing. This is crucial for ensuring robust mmWave communication in mobile environments.
* Subarray Architectures: There is a shift toward more sophisticated subarray configurations that allow for more flexible and powerful beamforming options, including the ability to form multiple beams simultaneously and serve several users.
* Research on Propagation and Channel Modeling: Continuous research on the better understanding of mmWave propagation characteristics and channel modeling is ongoing. Accurate models are vital for the design and simulation of hybrid beamforming strategies.
* Standardization Efforts: Efforts are being made to create and refine industry standards that support the widespread adoption of mmWave technologies, including hybrid beamforming approaches.
* Integration with sub-6 GHz Technologies: To ensure wide coverage and reliable connectivity, there is a trend towards integrating mmWave beamforming technologies with sub-6 GHz systems, allowing for seamless transition and better overall performance in various use cases.
* Integration with Non-Terrestrial Networks (NTNs): As 5G evolves, there is an increased interest in the integration of mmWave hybrid beamforming with NTNs such as satellites and high-altitude platform stations (HAPS), expanding coverage and capacity.
* Advanced Antenna Designs: There has been a push for more innovative antenna designs that allow for better control of the beamwidth and direction, providing enhanced performance in mmWave systems.