# 5G V2X Performance Comparison for Different Channel Coding Schemes and Propagation Models
## 1 Introduction and Literature Review
In [36], several waveform candidates and coding schemes under a common framework were investigated for V2X use cases, requiring ultra-reliable and low-latency communications under harsh channel conditions. [PERSON] et al. [37] proposed a model featuring an LDPC code that can improve reliability by reducing the bit error rate compared to the existing physical layer framework. In [38], they investigated the impact of LDPC and multiple input multiple output (MIMO) in a V2X environment, supported by Dedicated Short-Range Communication. The performance of different coding schemes attracted the research community in various communication systems. In [39], the authors evaluated different channel coding techniques potentially applicable in IEEE 802.11 be. [PERSON] et al. [40] focused on the BER evaluation and analysis of turbo and polar codes over AWGN channels for varying block lengths and code rates and, [PERSON] et al. [41] analysed the impact of turbo, polar and LDPC codes for 5G massive-machine-type communications over the AWGN channel. In [42], the authors compared the 5G channel coding techniques, e.g., polar and LDPC for the AWGN channel. Thorough research has been conducted in Worldwide Interoperability for Microwave Access (WiMAX) as well. In [43], the performance of the WiMAX system using LDPC, turbo coding, MIMO and Rayleigh channel was simulated and analysed. Based on the discussion above, a lot of work has been carried out in path loss analysis and modelling for V2V communications as well as the channel coding/decoding schemes in various wireless channel conditions. Moreover, V2X use cases require ultra-reliable and low-latency communications (URLLCs) under harsh channel conditions. To select a codingscheme for such use cases represents a key challenge. For this reason, in the published literature, no one has addressed the V2X channel modelling and coding issues combined in realistic road environments with the aim of designing a future adaptive model that will dynamically select the appropriate encoding/decoding scheme with the corresponding parameters providing a high quality of service (QoS) in driving experience. Therefore, in this work, we investigate and compare the performance of turbo codes, LDPC and polar codes for V2V traffic information for small frames in 3 GPP 5G V2X Release 16 practical scenarios. Bearing in mind these V2V scenarios, we investigate which can be implemented and are more efficient. The idea is to use the derived experimental results in a future system of dynamic data rate selection based on the conditions of the external environment (e.g., traffic density, wireless interference, safety level) to achieve the optimal BER among all the possible coding schemes and combine them in a reconfigurable and adaptive coding scheme. The main contributions of this paper are:  
* Simulation scenarios are investigated and are based on release 16 of the 3 GPP 5G V2X technical report, incorporating the use of both turbo-based and 5G-NR coding schemes. Aiming at an extensive analysis of the behaviour of coding schemes, different traffic propagation models, channel states and frame sizes are considered. * Analysis of the simulation results focusing on comparing the BER performance versus the SNR for the BCJR, logBCJR, maxlogBCJR, SOVA, LDPC and polar decoding algorithms in the implemented scenarios. The main objective is to document BER efficiency in small data frames and extract the optimal decoding scheme in the case of small-frame 5G V2X environments. * The simulation results are used to study the impact of QoS parameters on the system performance and on the decision of the optimal decoding scheme. Finally, the additional knowledge resulting from this work can be used to build a coding scheme, exploiting machine learning (ML) techniques, where the ML coding scheme will learn using data from the best coding/decoding technique for a given SNR and frame size.