# An Adaptive Scheduling Mechanism Optimized for V2N Communications over Future Cellular Networks
## 2 Scheduling Algorithms
### Proposed Schedulers for 5G and Beyond including V2X Communications
In [18], the authors suggest using vehicles' density information, channel state information, and queuing state information to allocate resources. The scheme's target is to reduce latency, improve throughput and guarantee reliability for V2V and V2N UEs. The evaluation of the results considers the key performance indicators at the UE level, not the service level. In [19], the authors evaluate the use of different 5G QoS schemes to identify how V2N scheduling for automated driving communication sessions is affected when other types of traffic, i.e., VoIP, video, and web traffic, are present concurrently. The authors consider just a single data traffic pattern for any automated driving session, which is somewhat limited in order to gain full insight into the support of various applications. They discover that the use of standardized values does not seem to be sufficient to guarantee an adequate performance for all four (VoIP, video, web and automated driving) applications, and thus, they suggest a combination of the different variants. As they also notice, the bigger the packet size of a session, the worse becomes the performance of the corresponding application. V2N scheduling is also investigated in [20], where the authors are using a maximum carrier to interference scheduler to provide priorities to V2X messages by indicating a higher priority in QoS, compared to VoIP, Video and Data traffic. As in the previous scheme, V2X sessions consider having only one type of data traffic pattern, thus providing useful yet limited insight into the effect of various types of V2X services. The above-mentioned papers present several interesting findings for developing scheduling algorithms for V2X communication and provide positive perspectives. However, not all of them focus on V2N communications. Those that offer solutions to this scheduling category evaluate their proposals either at a UE level thus, not providing service differentiation for each autonomous driving service separately, or their analysis considers only one type of V2X services which they compare with typical VoIP, Video and data traffic. However, as 5G networks support the notion of slicing [21], such non-critical services can always be supported via an eMBB slice and separately from V2X services. However, it is important to manage and support service differentiation among automated driving applications, especially those related to different safety services, as these services may have different data traffic characteristics and requirements. Our proposed solution addresses this point and overcomes the shortcomings of serving the latest 5G C-V2X UCs with stringent requirements, under traffic congestion conditions. As stated in [6], developing 5G-enabled vehicles under V2X UCs is ongoing. C-V2X connectivity presents advantages providing both direct and Non-Line-Of-Sight (NLOS) communication, higher achievable throughput, and enhanced reliability. These advantages introduce an additional motive to develop a scheduler, dedicated to C-V2X communications, which optimizes resource allocation on a V2X service-basis. All autonomous or automated driving applications that require communication through a server or between vehicles that do not have an NLOS, must be served by a base station. Thus, the development of an appropriate V2N scheduler for this category is essential. This is precisely the focus of our paper.