## 3 Cooperative Perception Information-Sharing
### Cooperative Perception Information-Sharing Network
#### 3.1.3 Hybrid Architecture  
At present, there are obvious limitations for a single V2X technology to achieve efficient and reliable cooperative perception in the IoV environment, such as the insufficient penetration rate of smart devices, network switching caused by vehicle mobility, and limited network bandwidth. To this end, some researchers have proposed that a hybrid solution using DSRC and C-V2X technology is more feasible for actual deployment at this stage, as shown in Figure 7[72]. This hybrid architecture enables the cellular network to back up vehicle data when the V2V multi-hop connection in the sparse network is interrupted. Meanwhile, it can choose the communication mode independently according to the driving scene requirements and performance requirements, which is more in line with economic development and accelerates the commercial application of autonomous driving. [PERSON] et al. [73] conducted an in-depth analysis of the potential of DSRC and cellular network hybrid architecture [74; 75], which fully considered the limitations of the two current mainstream V2X communication technologies in supporting V2X applications and the challenges brought by vehicle mobility to wireless communication. It concluded that the hybrid architecture of DSRC and cellular networks is promising for realizing V2X applications with low latency and high-reliability requirements. In practical application scenarios, to solve the problems of high network transmission latency and reduced reliability in cases of highspeed vehicle driving, [PERSON] et al. [76] proposed a 5G C-V2X intelligent fusion network technology based on MEC, and they discussed and summarized the network architecture, deployment schemes, and application scenarios. As shown in Figure 8, according to the needs of vehicle-infrastructure collaboration, the application scenarios of the intelligent fusion network are divided into four categories: interaction between a single vehicle and the MEC; interaction between multiple vehicles and the MEC; interaction between a single vehicle and the MEC or roadside intelligent facilities; and multivehicle interaction with the MEC or roadside smart facilities. In addition, the integrated network architecture of MEC and C-V2X effectively shortens the transmission path of data services in the IoV environment with localized services and realizes the information exchange delay to meet the service requirements of ultra-high reliability and low latency in the C-V2X scenario. In addition, the differences in the driving speeds of autonomous vehicles also require different performance requirements for network communication. When the vehicle speed is too high, it will pose higher challenges to edge node sensing data, computing resource allocation, and task scheduling. [PERSON] et al. [77] pointed out the importance of using millimeter-wave communication in cooperative perception in combination with the requirements of autonomous vehicles for network data transmission at different driving speeds. As the speed of the vehicle increases,  
Figure 7: V2X communication in a DSRC–cellular hybrid urban scenario. the data rate generated by the sensor increases exponentially, and they pointed out that, when using V2V millimeter wave communication on the 60 GHz band, the cooperative perception of overtaking scenarios can still be achieved when the speed exceeds 51 km/h. [PERSON] et al. [78] studied the sensor rate required for cooperative perception to achieve specific application functions for urban road scenes, and they found that millimeter-wave communication showed better performance in realizing the cooperative perception of edge nodes. It was verified that, when vehicle speeds are 56 km/h and 47 km/h, the required data rates are 12 GHz and 6 GHz, respectively. At present, the penetration rate of intelligent networked vehicles is low, and the deployment of intelligent equipment and infrastructure construction still need continuous efforts.