BO-WQWO Algorithm for Improving the Efficiency of Uniform Linear Antenna Array

BO-WQWO Algorithm for Improving the Efficiency of Uniform Linear Antenna Array

  IJETT-book-cover           
  
© 2023 by IJETT Journal
Volume-71 Issue-3
Year of Publication : 2023
Author : Y. Sahithi, P. Siddaiah
DOI : 10.14445/22315381/IJETT-V71I3P225

How to Cite?

Y. Sahithi, P. Siddaiah, "BO-WQWO Algorithm for Improving the Efficiency of Uniform Linear Antenna Array," International Journal of Engineering Trends and Technology, vol. 71, no. 3, pp. 246-251, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I3P225

Abstract
The study explores the use of evolutionary algorithms called Biogeography Optimization – Weighed Quantum Wolf Optimization (BO-WQWO) in antenna array synthesis. Specifically, a network of Uniform Linear Antenna (ULA) using the amplitude control method is employed to investigate the effectiveness of GA using two different methods. The study deploys the novel bio-inspired algorithm, BO-WQWO, which is reviewed compared to traditional BO with the linear migration model. The study aims to minimize the lateral lobes by adjusting the excitation magnitudes of the matrix components. To form dummies in particular directions in the optimized model, a weight parameter is determined based on the cost function. Finally, the effectiveness of the proposed bioinspired algorithm is demonstrated by comparing it to other GA’s, such as ACO.

Keywords
Biogeography optimization, Weighed quantum wolf optimization, Bioinspired algorithm, Linear antenna array.

References
[1] Lingling Liu et al., “An Improved Biogeography‐Based Optimization Approach for Beam Pattern Optimizations of Linear and Circular Antenna Arrays,” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, vol. 34, no. 6, p. E2910, 2021. Google Scholar | CrossRef | Publisher Link
[2] Jiaze Tu, “Evolutionary Biogeography-Based Whale Optimization Methods with Communication Structure: Towards Measuring the Balance,” Knowledge-Based Systems, vol. 212, p. 106642, 2021. Google Scholar | CrossRef | Publisher Link
[3] Vanita Garg, Anjali Singh, and Divesh Garg, “Biogeography-Based Optimization Algorithm for Solving Emergency Vehicle Routing Problem in Sudden Disaster,” Proceedings of International Conference on Scientific and Natural Computing, pp. 101-110, 2021. Google Scholar | CrossRef | Publisher Link
[4] Jingzheng Chong, Xiaohan Qi, and Zhihua Yang, “Bat-Inspired Biogeography-Based Optimization Algorithm for Smoothly UAV Track Planning Using Bezier Function,” Wireless and Satellite Systems: 11th EAI International Conference, vol. 357, P. 96, 2020. Google Scholar | CrossRef | Publisher Link
[5] T.P. Latchoumim, “Particle Swarm Optimization Approach for Waterjet Cavitation Peening,” Measurement, vol. 141, pp. 184-189, 2019. Google Scholar | CrossRef | Publisher Link
[6] Bin Yang et al., "Robust Adaptive Beamforming Based on Automatic Variable Loading in Array Antenna," Applied Computational Electromagnetics Society Journal, vol. 36, no. 7, 2021. Google Scholar | Publisher Link
[7] Hamid Farrokh Ghatte, “A Hybrid of Firefly and Biogeography-Based Optimization Algorithms for Optimal Design of Steel Frames,” Arabian Journal for Science and Engineering, vol. 46. no. 5, pp. 4703-4717, 2021. Google Scholar | CrossRef | Publisher Link
[8] E. G. Zahran et al., “A Self-Learned Invasive Weed-Mixed Biogeography-Based Optimization Algorithm for RFID Network Planning,” Wireless Networks, vol. 26, no. 6, pp. 4109-4127, 2020. Google Scholar | CrossRef | Publisher Link
[9] T. P. Ezhilarasi et al., “UIP—A Smart Web Application to Manage Network Environments,” Proceedings of the Third International Conference on Computational Intelligence and Informatics, pp. 97-108, 2020. Google Scholar | CrossRef | Publisher Link
[10] Giovanni Chiarion, and Luca Mesin, “Resolution of Spike Overlapping by Biogeography-Based Optimization,” Electronics, vol. 10, no. 12, p. 1469, 2021. Google Scholar | CrossRef | Publisher Link
[11] Sotirios K. Goudos, Application of Biogeography-Based Optimization to Antennas and Wireless Communications, Encyclopedia of Information Science and Technology, Fifth Edition , IGI Global, pp. 950-966, 2021.
CrossRef | Publisher Link
[12] Thota Vidhyavathi, "Amplitude and Phase Synthesis of Linear Array for Sector Beams Using Modified Harmony Search Differential Evolution Algorithm," SSRG International Journal of Electronics and Communication Engineering, vol. 3, no. 8, pp. 20-27, 2016. Google Scholar | CrossRef | Publisher Link
[13] Ali Durmus, Rifat Kurban, and Ercan Karakose, “A Comparison of Swarm-Based Optimization Algorithms in Linear Antenna Array Synthesis,” Journal of Computational Electronics, vol. 20, pp. 1520–1531, 2021. Google Scholar | CrossRef | Publisher Link
[14] Jaya Lakshmi Ravipudi, “Synthesis of Linear, Planar, and Concentric Circular Antenna Arrays Using Rao Algorithms,” International Journal of Applied Evolutionary Computation (IJAEC), vol. 11, no. 3, pp. 31-49, 2020. Google Scholar | CrossRef | Publisher Link
[15] S. Sakthivel Padaiyatchi, and S. Jaya, "Hybrid Bat Optimization Algorithm Applied to Optimal Reactive Power Dispatch Problems," SSRG International Journal of Electrical and Electronics Engineering, vol. 9, no. 1, pp. 1-5, 2022.
CrossRef | Publisher Link
[16] Rohit Salgotra et al., “Improved Flower Pollination Algorithm for Linear Antenna Design Problems,” Soft Computing for Problem Solving, pp. 79-89, 2020. Google Scholar | CrossRef | Publisher Link
[17] T.P. Latchoumi Manoj Sahit Reddy, and K. Balamurugan, “Applied Machine Learning Predictive Analytics to SQL Injection Attack Detection and Prevention,” European Journal of Molecular & Clinical Medicine, vol. 7, no. 2, pp. 3543-3553, 2020. Google Scholar | Publisher Link
[18] Yogita Wadhwa, Parvinder Kaur, and Baljeet Kaur, "Golomb Ruler Sequence Generation and Optimization using Modified Firefly Algorithm," SSRG International Journal of Electronics and Communication Engineering, vol. 1, no. 5, pp. 1-8, 2014. Google Scholar | CrossRef | Publisher Link
[19] Pruthviraju Garikapat et al., “A Cluster-Profile Comparative Study on Machining Alsi 7/63% of Sic Hybrid Composite Using Agglomerative Hierarchical Clustering and K-Means,” Silicon, vol. 13, pp. 961-972, 2021. Google Scholar | CrossRef | Publisher Link
[20] Jake Shearwood et al., “Localization and Tracking Bees Using A Battery-Less Transmitter and an Autonomous Unmanned Aerial Vehicle,” IEEE/MTT-S International Microwave Symposium (IMS), pp. 1263-1266, 2020. Google Scholar | CrossRef | Publisher Link
[21] E. Kenane et al., “A Dynamic Invasive Weeds Optimization Applied to Null Control of Linear Antenna Arrays with Constrained DRR,” Advanced Electromagnetics, vol. 10, no. 1, pp. 52-61, 2021. Google Scholar | CrossRef | Publisher Link
[22] Vijo M Joy, Joseph John, and S Krishnakumar, "Optimal Model for Effective Power Scheduling Using Levenberg-Marquardt Optimization Algorithm," SSRG International Journal of Electrical and Electronics Engineering, vol. 9, no. 10, pp. 1-6, 2022. Google Scholar | CrossRef | Publisher Link
[23] Yasser Albagory, and Fahad Alraddady, “An Efficient Approach for Sidelobe Level Reduction Based on Recursive Sequential Damping,” Symmetry, vol. 13, no. 3, p. 480, 2021. Google Scholar | CrossRef | Publisher Link
[24] Yau-Ren Shiau, Edwin M. Lau, and Wei-Cheng Chang, “Optimal Control Management for Aerial Vehicle Payload by Taguchi Method,” 2021 IEEE International Conference on Social Sciences and Intelligent Management (SSIM), pp. 1-6, 2021. Google Scholar | CrossRef | Publisher Link
[25] Anitha Suresh, C. Puttamadappa, and Manoj Kumar Singh, "Thinning Approach Based on Sides Lobe Level Reduction in the Linear Array Antenna Using Dynamic Differential Evolution," SSRG International Journal of Electrical and Electronics Engineering, vol. 10, no. 2, pp. 61-74, 2023.
CrossRef | Publisher Link
[26] Anupama Senapati., “Performance of Smart Antenna Under Different Fading Conditions,” Wireless Personal Communications, vol. 124, pp. 1-17, 2021. Google Scholar | CrossRef | Publisher Link
[27] Eda Sezen et al., “Heritable Cognitive Phenotypes Influence Appetitive Learning But Not Extinction in Honey Bees,” Annals of the Entomological Society of America, vol. 114, no. 5, pp. 606-613, 2021. Google Scholar | CrossRef | Publisher Link
[28] Y. Sahithi, and P. Siddaiah, “Weighed Quadratic Wolf Optimization Techniques to Enhance the Reliability and Accuracy on Beam Forming,” International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 401-407, 2022.
CrossRef | Publisher Link