# 3 GPP 5G V2X Error Correction Coding for Various Propagation Environments: A QoS Approach
## 1 Introduction and Literature Review
In [38], the authors presented a QoS-aware decentralized resource allocation for V2X communication based on a deep reinforcement learning framework and proposed a scheme to maximize the throughput of all V2I links while meeting the latency constraints of V2V links associated with the respective priority. [PERSON] et al. [39] investigated QoS in order to improve the service availability and stability for safety-critical applications, specifically targeting safety-critical V2X services. [PERSON] et al. [40] used turbo coding in V2V doubly-dispersive channels and studied the impact of delay spread and Doppler spread, i.e., vehicle speed, on the V2V system as well as the gain in terms of BER performance by using turbo coding on the V2V communication system. In [41], the authors analyzed the link reliability and they observed that larger-sized resources are preferred when the vehicle density decreases, the message size increases or the communication range decreases. In [42], the authors built and simulated a system in several V2V channel environments, using FER and throughput as the performance measures. In [43], the authors measured the performance of a V2V communication system that consists of high-density truck platooning in terms of latency and reliability. [PERSON] et al. [44] investigated BER, FER and throughput as performance and QoS features under several waveform candidates and coding schemes for various ultra-reliable and low-latency V2X use cases. [PERSON] et al. [45] proposed an LDPC-based model that improves reliability by reducing the BER compared to the existing physical layer framework, and in [46], the authors examined the effect of LDPC and multiple input multiple output (MIMO) in a V2X system model, supported by dedicated short-range communication. In [47], the authors emphasized the BER evaluation and analysis of turbo and polar codes over AWGN channels. [PERSON] et al. [48] analyzed the influence that turbo, polar and LDPC codes have on 5G massive-machine-type communications over AWGN channels by examining the BER performance. In [49], the authors compared polar and LDPC for the AWGN channel. Based on the discussion above, a lot of work has been conducted investigating individual QoS parameters in V2X communication systems as well as analyzing the performance of 4G and 5G coding schemes, but no one, to our knowledge, has addressed the impact of all 4G and 5G coding schemes on the overall QoS requirements as defined in [13; 14]. Therefore, in this work, we examine and compare the FER performance of turbo codes, LDPC and polar codes for 128-bit frames in 3 GPP 5G V2X Release 16 scenarios and analyze the 3 GPP and 5 GAA QoS parameters for each scenario. Our goal is to draw conclusions about the overall QoS behavior of coding schemes in each possible V2X communication scenario and evaluate each coding scheme for its QoS efficiency. The main contributions of this paper are:  
* We examined 3 GPP 5G V2X Release 16 system model simulation scenarios for both turbo-based and 5G-NR coding schemes and 128-bit frames, as a representative for small-frame V2X communications. In our simulation scenarios, different traffic propagation models and channel states are considered, targeting a comprehensive FER analysis for all the coding schemes. * QoS simulations scenarios are also examined, where reliability, power, vehicle velocity, maximum range, throughput, end-to-end latency, vehicle density and number of vehicles, as well as the impact of channel state change and traffic model change, are considered and optimized for each coding scheme and system simulation scenario. * Finally, a simulation-based selection of the most effective QoS coding scheme was conducted for small-frame 5G V2X propagation environments among all the 4G and 5G coding candidates, which is the main objective of this article. Such an analysis is missing in the current literature as can be seen in Section 5.13.