## 2 Related Works  
Over the past few years, several low frequency models have been developed for path loss prediction [11]. Concerning the related models, the Okumura model [4] is the classical empirical model, while most of the other models are derived from [PERSON]'s model. Figure 1: Different path loss sensor (signal strength). Moreover, the wireless industry is moving to its fifth generation of cellular technology. This technology will bring mobility to millimeter waves (mmWave) communications. Fifth generation cellular networks (5G) offer unprecedented bandwidth and faster network speeds by tapping into a high band spectrum in the mmWave frequency range, typically from 30 to 300 GHz [12; 13]. Propagation is more lossy in the mmWave bands when compared to today's microwave bands, thus the solution is to modify the standard path loss models (with a frequency between 28 and 38 GHz) to fit the real world measured propagation data for reliable mmWave channel planning [14; 15]. However, the previous models (Okumura, COST-Hata) do not work with frequencies between 28 and 38 GHz, and thus they are not compatible with the 5G [16; 17]. Of all the literature studies, the [PERSON] model [18] is the foundation of today's propagation prediction models. This prediction model is based on data extensive measurements which enable the telecommunication providers to compute the received signal power in a given propagation medium. However, when making network planning in practice, it is required to fit the parameters that was best used in the Okumura model, instead of a direct usage. In this regard, an empirical formulation for propagation prediction called a COST-HATA model [19] is derived from [PERSON]'s model. This model offers straightforward techniques to verify path loss in an expandable frequency range. On the other hand, our working frequency of 5 GHz is different from the estimation extent, as its effortlessness and modified variables still allow us to estimate the path loss at a higher frequency. Furthermore, it provides a good approximation in urban areas and it is a well-suited model over roughly the same range of Okumura converge frequencies, as the model for urban areas was built first and used as the base for other models. By using the Okumura model, we have the ability to calculate path loss in urban areas up to less than 3 GHz [20]. The path loss model by [PERSON] is given according to Equation (2). \[PL=lf+A_{mu}(f,d)-G_{(lte)}-G_{(ltre)}-G_{area} \tag{2}\]  
**Definition 2**. :  
_PL: is Path loss. \(lf\): is the free space propagation loss. \(A_{mu}(f,d)\): is the median attenuation relative to free space. \(G_{(lte)}\): is the gain base station antenna. \(G_{(ltre)}\): is the gain mobile antenna. \(G_{area}\): is the gain due to the type of environment._  
The COST-Hata models have more parameters that allow frequency and height to be adjusted. The Okumura and COST-Hata models are more generalized and well-known. The Hata path loss model is represented in Equation (3). \[PL=46.3+33.9\ \log 10(f)-13.82\log 10-ahm+(44.9-6.55\log 10(hb))\log 10(d)+cm \tag{3}\]  
**Definition 3**. : \(d\) _is for distance, \(hb\) is the height of the transmitter antenna, \(ahm\) is the Height of mobile station antenna, and \(cm\) is the height correction factor; \(ahm\) and \(cm\) have two values depending on the area being tested, as listed below:_  
_Urban area: \(ahm\) = 3.2(log\({}_{10}\) 11.75)) 2 - 4.79. \(Urban\) area: \(cm\) = 3 \(dB\)._  
The classical Okumura and COST-Hata models are also examined [8]. Fuzzy logic was applied as a set of rules to characterize precisely the unknown propagation environment from a set of known propagation environments. As a result, more cost-effective cellular network designs are expected using the path method. Other path loss prediction models created by [PERSON] et al. [8] made use of the sum of three propagation losses: propagation loss, wall penetration loss, and indoor propagation loss.