## 2 Fundamental Concepts
### Generic System Model  
The typical network is where problems with PLS arise, which consists of a transmitter, a legitimate (intended) receiver and a malicious eavesdropper, represented by [PERSON], [PERSON] and [PERSON], respectively. Figure 1 shows the general Alice-Bob-Eve model of a PLS system, in which the transmitter and receiver communicate through the legitimate channel and the eavesdropper makes a limited set of observations through a wiretap channel [37]. In this setup, the eavesdropper aims to decode or obtain sensitive information from historical observations of received signals. In other words, the objective of [PERSON] is to use a secure transmission strategy that can send a confidential message to [PERSON] while making sure that the eavesdropper is kept ignorant and is not able to glean any useful information from the transmitted signals. In order to achieve security in this case, PLS techniques are appropriately designed by exploiting the channel characteristics, such as noise, dispersion, fading, interference, etc., along with efficient secure transmission strategies, such that the  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Acronyms** & **Full-Form Definition** \\ \hline DF & decode-and-forward \\ DL & Deep learning \\ DNN & Deep neural networks \\ FDD & Frequency division duplexing \\ IoT & Internet of Things \\ ILDP & Interactive learning design paradigm \\ LDPC & Low-density parity-check \\ LOS & Line of sight \\ MISO & Multiple-input single-output \\ MIMO & Multiple-input multiple-output \\ ML & Machine learning \\ mmWave & Millimeter wave \\ NOMA & Non-orthogonal multiple access \\ NDP & Non-deterministic polynomial \\ QoS & Quality of service \\ PLS & PHY security/Physical layer security \\ PER & Packet error rate \\ OFDM & Orthogonal frequency division multiplexing \\ SDP & Semi-definite programming \\ SOP & Secrecy outage probability \\ SIMO & Single-input multiple-output \\ SISO & Single-input single-output \\ SDP & Semi-definite programming \\ SNR & Signal-to-noise ratio \\ SIPNR & Signal-to-interference-plus-noise ratio \\ ReLU & Rectified linear units \\ ZF & Zero forcing \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._information being sent from source to receiver is kept confidential from both active and passive eavesdroppers.  
As illustrated in Figure 1, the transmitted message signal M is encoded into \(X\) with a length \(n\) and transmitted via a wireless medium. The signals that are received by [PERSON] and [PERSON] are designated by \(R_{E}\) and \(R_{B}\), respectively. The entropy function of the transmitting signal is denoted by \(H(M)\), while the residual uncertainty of [PERSON]'s observations is given by \(H(M/R_{E})\). Taking the environment and scenarios into consideration, the availability of CSI at [PERSON], [PERSON] and [PERSON] varies from full or partial channel knowledge to zero information. The a priori knowledge that is available to [PERSON] regarding the channel information of the legitimate and eavesdropper channels is crucial for the determination of the corresponding secrecy optimization scheme and PLS design. Nevertheless, in practical scenarios, it is logical to assume that the [PERSON] is aware of the statistical information of the eavesdropper but not of its instantaneous realizations. Such information includes the type of channel distribution, the average gain of the received signal, the spatial direction and the line-of-sight (LOS) component.