Slotted Monopole Antenna for Ultra-wide Band (UWB) Microwave Imaging Applications
The design and implementation of monopole antennas for microwave imaging is challenging due to the following reasons:
Compact design to ensure proper physical placement and integration of antennas (as sensors) with compact components on the same printed circuit board (PCB).
Large bandwidth in both free space and close to the human body to ensure greater accuracy in body-centric wireless communications.
AI-driven Design with SADEA-III
The optimization problem is stated as follows:
- Minimize maximum reflection coefficient (S11) (3.1 GHz to 10.6 GHz)
- subject to
- 1 dBi < |Gain (bore-sight)| < 4.8 dBi
Synthesis and Measurement Results
The design obtained by SADEA-III  is verified through a physical implementation.
For this case:
- The synthesized antenna by SADEA-III obtains a maximum return loss of -10.6 dB over the bandwidth with gain (bore-sight) values ranging from 2 dBi to 4 dBi in two and a half days.
- The measured results are in close agreement with the simulation results.
- The size of the fabricated antenna is 33.12 mm × 14.90 mm × 0.03 mm, which is compact.
- This shows 1.6 times size reduction compared to a similar state-of-the-art design .
Comparison with Other Methods
The performances of SADEA-III  and SADEA-I  are compared with the following methods:
- 2019 Computer Simulation Technology-Microwave Studio: Particle Swarm Optimization (2019 CST-MWS: PSO)
- 2019 Computer Simulation Technology-Microwave Studio: Trust Region Framework (2019 CST-MWS: TRF)
- A sigma value of unity is used to direct the search towards global optimum and all initial designs for each run are randomly generated using Latin hypercube sampling.
Note that results from designs with geometric constraint violation are not included and are designated as not applicable (N/A) because in practice, such designs cannot be used due to geometric incongruities.
- B. Liu, M. O. Akinsolu, N. Ali and R. Abd-Alhameed, “Efficient Global Optimisation of Microwave Antennas Based on a Parallel Surrogate Model-Assisted Evolutionary Algorithm“, IET Microwaves, Antennas and Propagation, vol. 13, no. 2, pp. 149 – 155, 2019.
- B. Liu, H. Aliakbarian, Z. Ma, G. A. Vandenbosch, G. Gielen and P. Excell, “An Efficient Method for Antenna Design Optimization based on Evolutionary Computation and Machine Learning Techniques.“, IEEE Transactions on Antennas and Propagation, vol. 62, no. 1, pp. 7 – 18, 2014.
- B. Yeboah-Akowuah, P. Kosmas, and Y. Chen, “A Q-Slot Monopole for UWB Body-Centric Wireless Communications.” IEEE Transactions on Antennas and Propagation, vol. 65, no. 10, pp. 5069 – 5075, 2017.