Bandwidth Improvement of an Inverted-F Antenna Using Dynamic Hybrid Binary Particle Swarm Optimization
Jude Alnas, Garrett Giddings, Nathan Jeong
Abstract
This paper proposes a Dynamic Hybrid Binary Particle Swarm Optimization (DH-BPSO) algorithm to improve the bandwidth of an inverted-F antenna (IFA). The proposed algorithm improves upon the existing Artificial Immune System (AIS) algorithm by including a weighting factor that dynamically changes throughout the optimization. DH-BPSO activates or deactivates a 12 × 2 grid of parasitic patches incorporated between the IFA and ground plane. The DH-BPSO optimized and conventional IFAs are fabricated and compared while maintaining the same antenna volume. The measurement results show that the optimized IFAs have characteristics of 58.6% wider bandwidths and 5.8% higher antenna gain for various ground clearance lengths at Long Term Evolution (LTE) 700 MHz band compared to the conventional IFAs.