Design and Development of Additive Manufactured 5G IoT Antenna for High Performance Wireless Sensor Application
DOI:
https://doi.org/10.15662/IJEETR.2026.0802220Keywords:
Additive Manufacturing, 3D Printing Technology, 5G Communication Systems, Internet of Things (IoT), Wireless Sensor Networks (WSN),, Dielectric Resonator Antenna (DRA), Sub-6 GHz Frequency Band, Antenna Design and Optimization, High-Gain Antenna, Wideband Antenna, Electromagnetic Simulation, Rapid Prototyping, Smart Agriculture Applications, Industrial IoT, Low-Power Communication SystemsAbstract
In this work, the inverted micro-Stereolithography (SLA) is used to show the potential of such additive manufacturing (AM) technology at prototyping super-shaped dielectric resonator antennas (S-DRAs) rapidly and accurately. The S-DRAs, which exhibit 3D complex geometries, were designed to operate at 3.5 GHz, suitable for the assessment of 5G communications in the mid band. Initially, a cross-starred-shaped S-DRA was designed and manufactured via the inverted micro-SLA by means of a photopolymer resin as material. As no information about the used material was available from literature and supplier, the dielectric properties of the photopolymer resin were characterized. Moreover, in the view of challenging further the SLA capability, several prototypes, based on the cross star shaped geometry but exhibiting a twist of variable angles along the longitudinal axis, were fabricated and tested.In order to compare the antennas performance in relation to the material volume and sizes, rectangular and cylindrical DRAs were also realized using same material and technology. Scattering parameter S11, gain, bandwidth (BW), efficiency and co- and cross-polarization of all antennas were measured. The experimental results showed that twisted S-DRAs exhibit same performance of the basic cross-starred-shaped antenna, due to the invariance to symmetry of the basic Gielis geometry. The measured gain is about 2.5 dB over a range of 1 GHz in the frequency range of interest; the BW measured for all S-DRAs is about 10%, whereas the efficiency is about 80% at 3.5 GHz. Finally, better performance in terms of bandwidth is shown by the S-DRAs, considering their dramatic volume reduction (85%) compared to classic rectangular and cylindrical DRAs and other DRA examples already reported in the state of the art.
References
Applications,” Sensors, vol. 21, no. 10, 2021.
2. Á. F. Vaquero, A. Rebollo, and M. Arrebola, “Additive Manufacturing of Compact High-Gain Wideband Antennas for Millimeter-Wave Systems,” Scientific Reports, 2023.
3. T. H. Lin, J. G. D. Hester, A. Eid, and M. M. Tentzeris, “Additive Manufacturing Enabled 5G Wireless Modules,” IEEE Future Networks, 2019.
4. H. Giddens and Y. Hao, “3D Printed Antennas for 5G Communication Systems: A Review,” IEEE Future Networks, 2020.
5. M. Pant and L. Malviya, “Design and Applications of 5G Antennas for Modern Communication Systems,” International Journal of Microwave and Wireless Technologies, 2022.
6. W. Hong, Z. H. Jiang, C. Yu, et al., “Millimeter-Wave Technologies for 5G and Future Wireless Networks,” IEEE Journal of Microwaves, 2021.
7. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
8. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
9. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
10. S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
11. S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
12. S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
13. C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
14. C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
15. C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
16. C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
17. Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
18. M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
19. M. S. Sharawi, Printed MIMO Antenna Engineering, Artech House, 2014.
20. P. Kulkarni, Antennas for IoT Systems and Applications, Artech House, 2023.
21. N. O. Parchin, Advanced Antenna Design for 5G and Beyond, MDPI, 2022.
22. M. Ghasemi, “Machine Learning-Based Optimization of MIMO Antennas for 5G Applications,” Discover Electronics, 2025.
23. Jagadeesh, S., & Sugumar, R. (2017). A Comparative study on Artificial Bee Colony with modified ABC algorithm. European Journal of Applied Sciences, 9(5), 243-248.
24. Rajasekar, M. (2024). Real-Time Predictive DevOps Intelligence for Risk-Aware Digital Business Processes in Cloud and SAP Ecosystems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(4), 10713-10718.





