Adaptive Array Design using Least Mean Square Algorithm
Vidya P. Kodgirwar1, Shankar B. Deosarkar2, Kalyani R. Joshi3, Arati J. Vyavahare4
1Vidya P. Kodgirwar*, Department of Electronics and Telecommunication Engineering, PES’s Modern College of Engineering, SPP University, Pune, India.
2Shankar B. Deosarkar, Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, India.
3Kalyani R. Joshi, Department of Electronics and Telecommunication Engineering, PES’s Modern College of Engineering, SPP University, Pune, India.
4Arati J. Vyavahare, Department of Electronics and Telecommunication Engineering, PES’s Modern College of Engineering, SPP University, Pune, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1017-1021 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6083018520/2020©BEIESP | DOI: 10.35940/ijrte.E6083.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents the designing and testing of an 8-element linear array for Adaptive Antenna applications using the Least Mean Square (LMS) algorithm towards improving the directive gain of the array. A conventional patch antenna is optimized to operate at 2.35 GHz (4G applications) and this design is extended up to 8 elements using CST Microwave Studio parameterization. The S-parameters, Return Loss, Gain and VSWR of the antenna array are studied for the 2, 4, and 8 elements adaptive array. The simulation results are validated on the hardware setup and found closely matching with the experimental results. The resulting eight-element antenna array geometry is optimized with a coaxial feeding technique. This geometry appears promising in improving the gain from 6.13 to 23.5 dBi for a single element to eight elements respectively. Further, the LMS algorithm is used to compute the optimal complex weights considering different angles for desired User (60o and 30o) and Interferer (10o and 15o) during MATLAB simulation and then these optimal weights are fed to antenna elements using CST for beam steering in a different direction. Maximas are obtained at 54o and 28o when nulls are at 10o and 15o using CST software which is closely matching with MATLAB results.
Keywords: Adaptive Antenna Array, LMS And RLS Algorithms, Beam Steering, S-Parameters, Directive Gain, Microstrip Antenna.
Scope of the Article: VLSI Algorithms.