## 3 The Proposal
### Determining Grids Based on 17 Indicators
& **BHP** frequency, _BIn public facilities such as village government centres, economic activity centres (markets), industrial centres, health facilities, and educational places, locals can utilize the availability/coverage of telecoms access services using 4G technology. In addition, according to the results of a pro bono consultation with OpenSignal's international crowdsourcing, there are three aspects that influence the network experience:  
* The number of cells/sites will provide information on the network capacity (Mbps). * Quantity of subscribers if two networks share the same spectrum, but only one has a large subscriber base, in which case the network with the larger subscriber base will often have a poorer network experience due to the increased network load. * Type of transportation network: networks with enough spectrum but inadequate transport networks will provide a bad user experience. If the perspectives of these 5G actors are reduced to empirical datasets, then the data gathering requirements can be categorized into two major groups: telecommunications' network dimensions and socioeconomic potential dimensions. Telecommunication networks include optical distribution points (ODPs), signal coverage (SigCov), traffic, and the number of sites as operator considerations for network optimization or new network construction. Socioeconomic potential, comprising electricity, community activity centres, business fields, residential conditions, regional finances, and population, as a factor for commercial service providers to provide profitable services. Since the objective is to develop a telecommunications access infrastructure, we determined that the four variables comprising the telecommunications network (\(4\times 20\%=80\%\)) have a contribution or weight equivalent to the socioeconomic potential (\(1\times 20\%=20\%\)), as depicted in Figure 8.  
In the dendogram shown in Figure 8, 17 indicators are merged with the percentage of contribution. After acquiring the values of telecommunications network dimensions and socioeconomic potential dimensions, the following correlation matrix is applied to the data. On the basis of these indicators, a multi-stage statistical modelling approach assists in determining whether a district falls into the grid-reference index, the so-called G1, G2,  
Figure 8: Dendogram. G3, and G4. The correlation of these indexes ultimately determines the corresponding grid. Table 7 shows the correlation matrix between these indicators. For example, if a district has a grid-reference index G1 for a telecommunications network and G2 for socioeconomics, then it is categorized as Grid #2. Table S3 in Supplementary Material File S7 shows an abbreviation or variable definition for Table 7 (Correlation Matrix) and its explanation. Matrix mathematical functions can also be used to demonstrate the process. If \"G(i)\" is socioeconomic and \"G(j)\" is the telecommunication network, then  
\[G(x) = G(i).\ G(j)\] \[= \begin{bmatrix}I_{1}\\ I_{2}\\ I_{3}\\ I_{4}\end{bmatrix} .\left[\begin{array}{ccccc}I_{1}&I_{2}&I_{3}&I_{4}\\ I_{2}&  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Indicator** & **Indicator Name** & **Postulate to Determine the Grid-Reference** & **Explanation** \\  & & **Index G1, G2, G3, G4** & \\ \hline
2 & Telecommunications Network: & Mean aggregates: & G1 when there is no signal for communication. G2 when the average signal coverage reaches \\  & Coverage (SigCov) & & If the data column & grid region. G3 when the average signal coverage reaches \\  & & & \\  & & \(\mathrm{O}\)= \(\mathrm{[3G Coverage]}\), & & one-third and two-thirds of the signal coverage reaches between one-third and two-thirds of the signal region. G4 when the average signal coverage reaches between two-thirds and the entire grid.