# A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
## 3 An In-Depth Analysis of the mmWave Hybrid Beamforming Landscape
### Applications
There is no need for extra signals, such as synchronization signals, since the angular information is approximated from regular pilot signals that are then used for tracking channels [108]. * **Security** Prior studies focused on various performance metrics, such as power minimization. Conversely, methods exist for optimizing the secret rate. To ensure secure downlink transmission, the base station (BS) employs a uniform planar array (UPA) configuration to regulate the beams' azimuth and elevation angles, as well as to provide sufficient bandwidth and gain across the coverage region. Improved system performance is possible with the UPA configuration by use of three-dimensional beamforming techniques. Beamforming makes use of three distinct hybrid subarray designs: interlaced, fully connected, and partially connected. In the absence of perfect information about the wiretap channel's angle of departure (AoD), a limited optimization problem is utilized to determine the optimal spectrum efficiency and energy efficiency that satisfy the demands of cellular users for a specific SNR value [109]. An inactive reflector system based on a RIS improves performance against jamming and eavesdropping. The reconfigurable intelligent surface (RIS) may greatly reduce power consumption and improve data security. A multi-user cellular network's spectrum efficiency and security may be enhanced with the use of RIS-assisted wireless transmitters. The design of the user-side receive decoder, the digital precoder and artificial noise (AN) at the base station (BS), and the analog precoder at the RIS are all taken into account concurrently in order to solve the worst-case sum rate maximization issue. Finding a good response that meets the least attainable rate restriction, the maximum wiretap rate need, and the maximum power limitation is conducted using an alternative optimization (AO) approach. To facilitate the generation of a closed-form solution for the receiver encoder, a heuristic approach is used to strengthen weak angular CSI. After this, the majorization-minimization (MM) approach may be used to reframe the initial issue into a more manageable form [110]. * **Satellite**Optimizing resource allocation in an integrated terrestrial satellite network (ITSN) based on frequency forward transmission and hybrid beamforming user scheduling are necessary to improve the system sum rate and energy economy. Using a combination of beamforming and user scheduling, we can reduce the sum rate maximization issue to a power allocation problem. To enhance power sharing for each user terminal (UT), logarithmic linearization and the minimal mean square error (MMSE) criteria are used [111]. * **UAV** The need of the present age is NOMA-enabled mobile edge computing networks helped by UAVs. An unmanned aerial vehicle (UAV) carrying a wirelessly powered mobile edge computing (MEC) system may improve transmission efficiency in a few ways: NOMA hybrid beamforming and non-orthogonal multiple access (NOMA). The UAV offers mobility, while the MEC platform supplies computing services and electricity to IoT devices. There has to be massive coverage, little power usage, and lightning-fast computations from the IoT devices [112]. For unmanned aerial vehicle (UAV) deployment and optimal hybrid beamformer design, the polyhedral annexation method and the deep deterministic policy gradient (DDPG) algorithm are useful tools. For line-of-sight (LoS) channels, a hybrid beamforming design is used to obtain a power allocation plan and a near-closed-form depiction of the rate. Antenna density has an inverse relationship with total transmitted power for UAVs [113].