## 2 Related Work  
Beamforming is the process of creating an energy beam using phased arrays, which involves adjusting the antenna spacing and signal phase of each element in the array. This allows for control over the size and direction of the signal beam from multiple antennas [17]. Beamforming involves interference and pattern construction, and beam steering is an advanced technique that dynamically modifies the beam pattern by altering the signal phase in real time without changing the hardware [18]. Beam steering is commonly used in 5G and Wi-Fi to direct the radiation or reception beam to a specific station, maximizing gain for that station and minimizing interference with others. These concepts are fundamental for vehicle communications [19]. The increasing demand for voice-over-internet protocols, on-demand bandwidth, and multimedia applications, especially in connected cars, necessitates small, portable antennas with high-speed and low-latency wireless connections. This study evaluates various 5G beamforming techniques, such as analog, digital, hybrid, switching, and adaptive systems, as well as their types, working algorithms, antenna design, gain, and substrate characteristics [20]. These techniques generate different beam widths for specified directions. As wireless and telecommunication protocols for vehicle-to-vehicle (V2V) communication advance, artificial intelligence, machine learning, and deep learning are playing a significant role. A study [21] proposes an optimal Minimum Mean Squared Error (MMSE) receiver-based heuristic solution structure for downlink beamforming. This study focuses on power allocation and virtual uplink beamforming (VUB) using the Beamforming Prediction Network (BPNet). The proposed method achieves efficient performance in high-speed environments for intelligent transportation systems (ITSs) [22]. Another study [23] investigates the benefits and drawbacks of using beamforming for beaconing in V2V communication. Simulation results show that while beamforming increases collisions, it also enables reaching a higher number of vehicles in the network, leading to more reliable communications. However, the study does not consider the effect of increased power usage on channel loading. As part of the related work, the utilization of physical layer security techniques, such as friendly jamming (FJ), has been explored to enhance the confidentiality of data uploading in mobile edge computing (MEC) services. FJ has shown promising results in degrading attackers' wiretap channel capacities and effectively protecting users from potential threats [24]. In this paper, the authors propose a comprehensive security scheme that incorporates FJ as a physical layer security mechanism. This scheme involves the coordinated use of FJ from both the base station (BS) and nearby mobile users to cover the upload transmission, thereby ensuring enhanced confidentiality in MEC services. One drawback of this FJ-based physical layer security mechanism is the potential increase in resource utilization and communication overhead due to the additional coordination and signaling required for implementing FJ. The emerging concept of the Internet of Vehicles (IoV) in the 5G era has gained significant attention. One study [25] focused on multicast beamforming and multimedia content caching in IoV-based vehicle edge networks. The authors addressed the optimization of clustering, caching, and multicasting with V2V assistance to meet Quality of Service (QoS) requirements. However, the study did not test the power cost in high-speed environments. Enhancing V2V communication effectiveness is explored in [26] through beamforming and scalable transmission. Beamforming increases the bandwidth by establishing clear and reliable beam connections between vehicles. Scalable transmission reduces data volumes by transmitting only relevant information. However, the study acknowledges potential problems in high-speed scenarios if power management and intelligent algorithms are not considered.