Optimization of End-Fire Realized Gain and Side Lobe Levels in Active and Parasitic Antenna Arrays

This work presents a comprehensive optimization strategy for both active and parasitic antenna arrays, focusing on maximizing the overall efficiency and realized gain (RG). Using a differential evolution (DE) algorithm, we optimize key parameters such as element spacing, excitation currents, and load values. By removing predefined constraints on excitation vectors, this approach achieves greater flexibility and higher RG for all the array configurations, which is validated through full-wave simulations. Using the proposed DE-based optimization technique, we show a five-element parasitic array, achieving a maximum RG of 11.42 dB. Then, the optimization is extended to include side lobe level (SLL) minimization, balancing RG and low SLLs to improve the end-fire radiation performance. The parasitic five-element array achieves a RG of 10.32 dB with a SLL of −20 dB. This approach offers promising results for 5G and beyond wireless communication systems requiring compact, high-efficiency arrays with controlled interference.