## 6 Simulation Analyses  
### Result Analyses  
To assess the advantage and effectiveness of the proposed algorithm, several different experiments instances were monitored and explored. In the following part, to assess the flexibility and effectiveness of the presented approach, the specific numerical results are shown and compared with some reference ways (obtainable from the literature [20; 21; 22]). In the first example, to minimize the maximum side lobes level (\(\Phi_{\text{slp}}\)) via the changing element weight was solved. As for the problem, in [22] the combining process was utilized to the linear matrix of 25 isotropic elements D = 50 \(\lambda\) in length. The power weight parameters were set to change inside the range [0.2, 2.0] and the parameter \(u_{start}\) was fixed to 0.04 to compare the performances of the results achieved via normal GA with the IGA optimization. As far as this application is concerned, we supposed that the length of this array was dispersed in \(N\) = 100(\(\lambda\)/2)-spaced steps via pushing the specific number of the elements \(M\), equals to 25. Such that, the architectures of those series of the chromosome results as below:  
\[\overline{\xi}=\{\omega_{0},\ldots,\omega_{k},\ldots,\omega_{N-1}\},\] \[b_{k}=1\ k=0,\ldots,\ N-1, \tag{26}\] \[M=25.\]  
Figure 6 shows the comparison between the element, the BP, and the position layout of such arrays. The most optimal result is the array with a side lobe peak value located at \(\Phi_{\text{slp}}=-14.77\) dB. However, to the authors' knowledge, the best threshold for the side-lobes level obtained in article [26] was just \(-14.45\) dB approximately, and \(u_{ml}=0.191\) was the width of the half-beam width. However, then as far as the main lobe width is concerned, one of the most optimal results was the specific array with a beam pattern (BP), which was characterized by a side lobe peak value being \(\Phi_{slp}=-14.67\) dB and the main-lobe width value \(u_{ml}=0.0204\). Figure 6: _Cont._In order to meet the accuracy and completeness, Figure 7 illustrated the specific collection of those best results achieved behind the running of the presented method to highlight an obtainable trade-off among the main-lobe width and the side-lobe peak value. As a reminder, it has to be pointed out that, although the side-lobe decrease of approximately 0.2 dB could be lower than the errors' number in the real phased array, these obtained results are pretty good due to the closeness to the theoretically optimal value. For the convenience to the comparison, this figure also shows the outcome with the procedure based on the SA (Simulated Annealing). In this testing part, the optimizing process of the quantity of these sensors and of the specific length of the array using a fixed beam pattern shape was thought about. The expected pattern was the same as in [11; 16] and illustrated in Table 1 below. The algorithm proposed in the paper intended to work, firstly, as every node writes the local interference power value into the HELLO message, and then broadcasts it to its neighbors. Figure 6: Optimization of the element power weights—(**a**) beam pattern (BP) with a side-lobe peak value of \(-14.77\) dB; and (**b**) positions and power weights of those array elements. Figure 7: Optimization of the element power weights—peak side-lobe value level as a specific function of the main-lobe width ((dB) units; simulated innovative genetic algorithm (IGA); O: Simulated SA). At last, the isophoric matrices [19] were also thought about as well. In this instance, the power weights of these array elements were statically set (\(w_{k}\); \(k=0,1,2,3,\ldots,N-2,N-1\)) and an optimization procedure took these array element positions into account.