rical parameters for antenna design and their representation in [0, 1]. Moreover, L feed parameter is equal to (Wg/2)-(Wp/2). If we need to construct a new design, we merely need to calculate the bounds of the first two optimization variables for the new frequencies. Setting the boundaries of an optimization variable inside the range of [0, 1] reduces the search space, making it easier for an evolutionary algorithm to provide results. 10.5 Numerical Results In this section, we present the antenna design for future 6G mobile networks. As it is reported in [1], the low THz band for WPAN use defines the frequencies from 252 to 325 GHz. In this book chapter, we will use the 300 GHz as the design frequency of our work. It must be pointed out that a similar design case is reported in [12], where the optimization method is a hybrid Jaya-GWO and the design frequency is 26 GHz. Figures 10.2 and 10.3 show the antenna geometry for this case. The antenna is made from a single layer of dielectric, and the feeding is done via a 50ohm feed line. We have selected for this design the dielectric Rogers RT/duroid 5880 laminate (Er = 2.21) with 0.127 mm thickness. This kind of material and thickness is suitable for operation in 300 GHz. S. K. Goudos and M. A. Matin 0.6 (mm) Fig. 10.3 Antenna geometry in 3D view Table 10.3 Parameter values Parameter Value (mm) Parameter Value (mm) of the best achieved antenna design at 300 GHz Wfeed -0.10 As it is described in the previous section, there are 12 geometrical parameters to be fine-tuned in order to design this antenna. We used the SSA as the main optimization method to design this antenna. Due to computationally intensive operation while running the HFSS, we need to set the population size to a small value like 20. Moreover, the maximum number of generations is preset at 2000. We, then, run the SSA for ten independent trials and obtain the best result. SSA does not need any setting of other control parameters, which is an additional advantage of the algorithm. Table 10.3 lists all the d