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Aug. 2022
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  Journal Paper


Paper Title :
Comparative Analysis of Adaptive Beam Forming (ABF) Algorithms for Smart Antenna System (SAS)

Author :Prathviraj Khande, Yogesh K. B, Manu M. M, Ravikiran G. N, Devasis Pradhan

Article Citation :Prathviraj Khande ,Yogesh K. B ,Manu M. M ,Ravikiran G. N ,Devasis Pradhan , (2021 ) " Comparative Analysis of Adaptive Beam Forming (ABF) Algorithms for Smart Antenna System (SAS) " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 13-21, Volume-9,Issue-7

Abstract : Abstract - Due to the latest big development in the subject of cellular communication, there is a need to maximize spectral efficiency so that the sizeable boom in visitors can be accommodated efficiently. The smart antenna gadget is a major supply to maximize the spectral efficiency and capacity of wi-fi networks. It consists of an adaptive antenna array that continuously adjusts its radiation characteristics (beam-width of the primary lobe, side-lobe degrees, and function of nulls) to supply narrow beam in the course of arrival (DOA) of the favored sign and to vicinity nulls inside the DOA of interferer signals in order that maximum SINR (signal to Interference and Noise Ratio) is received. Smart antennas are getting more popular now a days because of massive advancement inside the area of virtual sign processing and real-time implementation of adaptive signal processing strategies. These adaptive beam forming algorithms use extraordinary standards to adapt the system for higher overall performance and steer the principle beam toward the signal of hobby. Basically, adaptive beam forming is a technique in which an array of antennas is exploited to obtain most reception in a selected path. A set of rules with small complexity, low computation fee, correct convergence fee typically desired. In this paper we analyze various adaptive beam forming algorithms including LMS (Least Mean Squares), NLMS, CMA (Constant Modulus Algorithm), and RLS (Recursive Least Squares) through simulating different parameters like radiation pattern, amplitude response, mean square error and absolute weights of an N-element array for a certain number of iterations. The obtained simulation results are very helpful to evaluate performance and quality of adaptive beam forming algorithms. Keywords – LMS, NLMS, RLS, CMA, SINR, ABF, Smart Antenna, Signal Processing

Type : Research paper

Published : Volume-9,Issue-7


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-18092   View Here

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