# Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A Survey
## 3 Physical Layer in 5G
### Signaling Techniques for 5G
In [222], the author proposed an ANN-based novel Adaptive Modulation and Coding (AMC) scheme to estimate the signal-to-noise power ratio (SNR) to determine the optimal MCS with a low calculation complexity, and [223] proposed ML-based peak-to-average power ratio (PAPR) reduction using the optimal hyperparameter function and efficient approximation for the downlink channel of mMIMO with an OFDM signal. In addition, ref. [224] proposed a DRL-based channel and latency aware radio resource allocation scheme to optimize the uplink scheduling for service-oriented multi-user millimeter wave (mmWave) radio access networks (RAN). Furthermore, ref. [225] proposed a DRL-based channel prediction approach to reduce the signaling overhead when reporting full downlink (DL) channel state information (CSI) back to the base station. Orthogonal frequency division multiplexing (OFDM) is a mature technique in wired and wireless communication systems. In OFDM, high-order modulation schemes boost the SE of a signal and the power level for each subcarrier, enhancing the transmission performance, while digital signal processing complexity is another factor in contrast to single-carrier systems. Table 6 explains the 5G numerology from 0 to 4 and their corresponding attributes. Fifth-generation networks offer five options for different scenarios depending on the communication requirements. A high peak-to-average power (PAPR) offers vulnerability to fiber nonlinear effects, and ML-based techniques can play the best role here to control the PARP level and optimize the values for upcoming intervals [226]. Figure 3: 5G NR-LTE options. The existence of a high carrier frequency in the mmWave band generates non-ideal characteristics in the signal and extends the free space loss propagation. Researchers have also discussed the performance of radio channels by varying the RF and by analyzing the impact of propagation factors on 5G architecture, and the results show that if the wavelength is small, it is easy to build the entire structure on a single IC, but it is hard to cope with environmental factors. At low wavelengths, the chances of attenuation, shadowing objects, scattering, reflection, diffraction, and constructive and destructive interference are high because of delay, path loss, and unnecessary noises [227]. At the same time, multi-path propagation creates indirect rays to carry various duplicates of transmission side signals to receiving side signals. The authors first analyzed the performance of the signal at 28 GHz and then at 38 GHz, proving that, when using high range frequencies the radio channel behaves differently if the objects surround the environment. In addition, if the user/object is moving, the amplitude and phase of the traveling signal must be altered, and ultimately the receiver cannot decode the transmitted signal [228]. Similar efforts were performed by an authors in [229] to demonstrate the concept of vehicular positioning for 5G mmWave. Following the guidelines in [150], Figure 4 illustrates the physical layer services of 5G and functions defined by 3 GPP. Multi-path propagation and the simultaneous localization and mapping (SLAM) technique are used to determine the position of reflectors and users, respectively. Though multi-path propagation blocks GPS signals, it helps the reflectors to measure the transmitter signal scattered from objects. Furthermore, the instantaneous localization and mapping algorithm determines the user's position and constructs an atmosphere map. The author proposed a joint estimation