## 1 Introduction
Hence, the thresholding of the values. 4G and 5G offer high data rates and low latency; thus, they make a good candidate for SHM. 5G, 5 th generation mobile network, is a new global wireless standard coming immediately after the 4G networks. In the 5G era, a large volume of data will be exchanged with low latency at a low energy cost. One key concept is to get low residual error rates with fast, flexible, and low complexity decoders. 5G enables a new kind of network that is destined to connect virtually a plethora of devices, objects, and machines. 5G wireless technology is here to accomplish higher multi-Gbps peak data speeds, ultra-low latency, more reliability, extremely large network capacity, increased availability, and a more uniform user experience to more users. The higher performance, which is promised to achieve, in conjunction with the improved effectiveness ensures new user experiences and connects new industries, the railway industry in our case. Nowadays, in the railway sector, there is the LTE-R, which is the Long-Term Evolution (LTE) for railways, which comes as a candidate against Wi-Fi connectivity. With 5G, we aim to surpass the LTE-R and accomplish even better numbers in terms of latency and connectivity, as well as throughput. In the case of the collection of data from AE sensors in monitoring infrastructure, high coverage (connectivity) and low latency is essential. Those features refer to the ultra Reliable Low Latency context. It seems interesting to evaluate the capability of the 5G network to perform to changing condition; however, the high connectivity and low latency with the increased performance make 5G suitable for SHM. An excellent method for ensuring that the message is transmitted to the basestation is network coding [23]. The simplest case is where relay nodes are utilised that transmit a linear combination of two messages, i.e., the sum. Then, the decoder essentially receives two messages, since it has one message and a combination of the two messages transmitted. Since data is transmitted in such a way, throughput is maximised. Forward Error Correction codes (FEC) is a method in which a data sender adds an Error-Correcting Code (ECC) to the original data for allowing the receiver to detect and correct a limited number of errors in a noisy channel. The FEC consists of two types, the block code, and the convolutional code. Some of the most recognised block codes include the Hamming code, Golay code,Bose-Chadhuri-Hocquenghem code and Reed-Solomon (RS) code, as we can see in [24] and references therein. These codes are quite simple and have strong features with respect to burst error. Since the assumption is for a 5G network to be deployed, a large amount of data with a short delay and we may have burst errors, block codes are mainly used. The convolutional codes offer less mathematical complexity than block codes and it offers good features in the additive Gaussian noise environment. A typical example is the turbo code [25]. The linear block codes, names POLAR codes are of great importance and proposed recently [26]. Some related work in other domains includes research that is given below. [PERSON] et al. [27], extended the upper bound of streaming codes to multi-hop relay networks, and further, the described the state-dependent scheme for the L relay scenario and provided the way it accomplishes the upper bound while requiring an overhead in the packet header. Moreover, they showed that the header size is not dependent on the field size utilised by the code. Hence, the gap from the upper bound decreases as the field size increases. [PERSON] et al. [28] investigate a network of two source nodes, one relay node and a destination node, whereby the source nodes' objective is the transmission of a sequence of messages, via the relay, to the destination. The latter needs to decode the messages with a strict delay constraint T. The paper begins with the introduction of two significant tools namely, the delay spectrum and the concatenation.