# Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A Survey
## 3 Physical Layer in 5G
### Signaling Techniques for 5G
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & & **SCS** & **Supported** & **Supported** & **Cyclic** & **Cyclic** & **OFDM and** \\ \(\mu\) & **N** & \(\frac{Slots}{Sabframes}\) & **N** & \(\frac{Symbols}{Stot}\) & **\(\Delta f=2^{n}\times\)** & **Data (PDSCH, (PSS, PBCH) & **Sync Blocks** & **Prefix** & **Prefix** & **Useful Symbol** \\  & & & & **15 kHz** & **(PUSCH)** & **(PSS, PBCH)** & **Type** & **Length (\(\mu\)s)** & **Length (\(\mu\)s)** \\ \hline
0 & 14 & 1 & 15 & Yes & Yes & Normal & 4.69 & 71.35/66.67 \\
1 & 14 & 2 & 30 & Yes & Yes & Normal & 2.34 & 35.68/33.33 \\
2 & 14 & 4 & 60 & Yes & No & Normal/Extd & 1.17 & 17.84/16.67 \\
3 & 14 & 8 & 120 & Yes & Yes & Normal & 0.57 & 8.92/8.33 \\
4 & 14 & 16 & 240 & No & Yes & Normal & 0.29 & 4.46/4.17 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: 5G numerology. Figure 4: 5G physical layer functioning. scheme that depicts an automobile's location and resolves multi-path propagation projections while calculating their delays and angle deviations [230]. In [231], the author uses a single-cell multi-user millimeter wave system to achieve SE. The uniform rectangular array situated at the base station region is used for single consumers, who are present in large quantities. The authors achieved favorable results, where SE gave a logarithmic relation depending on the number of antennas using the azimuth and elevation degree for 3D model design and considered single-path propagation. Results showed that SE increased by increasing the number of antennas. Moreover, the SE is improved through the scheduling scheme of users, relying on the response obtained from the users. Table 7 shows the strengths and weaknesses of 5G waveform candidates. In [237], the authors made several efforts to boost the SE of the hybrid architectures by using discrete Fourier transform (DFT) signal processing and compared them with digital architecture. Zero-forcing pre-coding is used to perform baseband signaling, while BS contains the ideal state information. The viable SE for a hybrid architecture can be enhanced by upgrading SNR and RF chains such as the SE and DFT, which are independent of the number of antennas used at the BS. Moreover, in multi-core fiber (MCF), two or more signals carrying the same or partially the same frequency can be transmitted by using the available number of cores in the same fiber. We can experience more than one dimension of the fiber core through the MCF environment, but the transmission performance of the network is reduced [238]. So far, we have discussed crosstalk issues generated by mmWave frequencies and massive MIMO in 5G. It is essential to overcome these limitations to deploy 5G infrastructure successfully in upcoming years. Although the researchers have already suggested various proposals to overcome these issues, there are still several open research challenges [239]. Various efforts have already been shown in this regard; for example, ref. [240] proposed a DL-based hybrid precoding scheme to increase spectral efficiency in MIMO systems. In addition, ref. [241] proposed a DL-based spectrum situation prediction using RF traces collected from nine different coexistence scenarios for efficient spectrum prediction. Moreover, ref. [242] proposed an NN-based technique for detecting and decoding the SCMA codewords to optimize the Euclidean distance between constellation points and to increase spectral efficiency in enhanced mobile broadband (eMBB) use cases. The combination of 5G with the latest technologies (AI, ML, SDN, NFV, network slicing, edge computing, massive MIMO, mmWave, IoE, VR, AR, MR) will transform the data-centric future. These technologies present numerous opportunities for distributing intelligence from both life and business perspectives. In other words, 5G acts as a revolutionary tool for these technologies. The primary goal of these technologies is to connect machines and computers intuitively.