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Randomly overlap subarray feeding network to reduce number of phase shifter in 28GHz
Maryam Shadi1, Zahra Atlasbaf1
1Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.
Plos One
|December 8, 2022
Summary
This study introduces a new algorithm for designing 5G base station antenna arrays, reducing component count and improving performance for efficient wireless communication.
Area of Science:
- Electromagnetics
- Antenna Theory
- Wireless Communication Systems
Background:
- Designing 5G antenna arrays presents significant challenges in the electromagnetic industry.
- Existing methods often struggle with achieving wide scan angles, compact size, and cost-effectiveness.
Purpose of the Study:
- To develop a comprehensive algorithm for a high-gain 5G base station antenna array.
- To minimize grating lobes while maintaining a wide scan angle and compact design.
- To simplify fabrication, particularly for the array feeding network.
Main Methods:
- Algorithm development comparing various subarray combinations to minimize grating lobes.
- Incorporation of subarray symmetry, complex weighting, minimal element overlap, and optimal microstrip layers.
- Hybrid genetic algorithm and particle swarm optimization for excitation coefficients.
Main Results:
- Designed a 49-element linear array for 5G base stations operating at 28 GHz.
- Reduced the number of phase shifters by over 53% compared to previous designs.
- Achieved a gain of 28 dB, beam scanning up to ±25°, and side lobe level below -24 dB.
Conclusions:
- The proposed algorithm efficiently designs 5G antenna array topologies.
- The method offers significant improvements in performance and component reduction.
- Validated through full-wave simulation of a 16-element array with a random overlap subarray structure.
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