Signals and Telecommunication Journal Yao-Liang Chung 15 1 2026 https://doi.org/10.6025/stj/2026/15/1/1-14 https://www.dline.info/stj/fulltext/v15n1/stjv15n1_1.pdf This study presents a fractal inspired ultra wideband (UWB) multiple input multiple output (MIMO) antenna design framework integrated with multi objective optimization for next generation 5G, IoT, and wireless communication systems. Addressing critical challenges of mutual coupling, limited isolation, and excessive hardware complexity in dense array deployments, we employ Pareto front analysis to systematically characterize fundamental trade offs in sparse array synthesis. Using the MOPET optimized dataset comprising 3,350 non-dominated solutions derived from aperture sizes spanning 196-2,025 elements, we reconstruct performance envelopes mapping hardware cost against electromagnetic metrics including sidelobe level (- 27.95 to 3.38 dB), directivity (18.36-34.01 dB), and sparsity ratios (26.7%-62.0%). Our analysis reveals four key insights: (i) sidelobe suppression exhibits diminishing returns beyond a critical "knee point" in element count; (ii) beamwidth degradation stems primarily from effective aperture contraction rather than sparsity alone; (iii) high directivity is preserved in sparse layouts through intelligent peripheral element placement; and (iv) Pareto optimal configurations achieve performance within a few decibels of dense arrays while reducing element count by 30-70% [Lorincz, J., 2019, 2022]. These findings validate multiobjective optimization as a physics grounded methodology for sustainable antenna design, directly addressing escalating energy consumption in 5G/6G infrastructure [Uluslu, A., 2025; Haxhiraj, E., 2023]. The reconstructed Pareto fronts serve as quantitative design maps enabling informed selection of array configurations that optimally balance spectral efficiency, interference suppression, angular resolution, and implementation cost for resource constrained wireless deployments.