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Multi Beam DOA Estimation Using Robust Convergence Adaptive Algorithm

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJHIT) 바로가기
  • 간행물
    International Journal of Hybrid Information Technology 바로가기
  • 통권
    Vol.6 No.6 (2013.11)바로가기
  • 페이지
    pp.311-320
  • 저자
    Y. Murali Krishna, N. Sayedu Khasim, M. Sreedhar
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A217430

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원문정보

초록

영어
Smart Adaptive Array antenna can automatically track the unknown interference signal in real time applications, that it requires to provide nulls towards the interference and offer gain to the required signal to ensure the required signal reception, so it leads the output SINR (signal to Interference and Noise Ratio) is improved. There is a growing need for the development of efficient algorithms for real-time optimization. Several algorithms can be applied for Digital Signal Processors (DSP), which differ in their complexity, convergence and so on In this paper, an efficient method for the DOA estimation of the linear antenna arrays with the prescribed steering and nulling lobe is presented. The proposed method is based on Least Mean Square (LMS) algorithm; provide a comprehensive and detailed treatment of the signal model used for beam forming, as well as, describing adaptive algorithms to adjust the weights of an array. In order to improve the convergence rate of LMS algorithm in smart antenna system, this paper proposes the GNGD algorithm. By taking advantage of spatial filtering, the proposed scheme promises to reduce the bandwidth required for transmitting data by improving convergence rate. The performance of the GNGD algorithm in the presence of Multi-path effects and multiple users is analyzed using MATLAB simulations. The simulations when compared to that of the LMS algorithm greater improvement in the convergence rate are observed. The results suggest that GNGD algorithm can improve the convergence rate and lead to better system efficiency.

목차

Abstract
 1. Introduction
 2. Adaptive Beam Forming
 3. Adaptive Algorithms
  3.1. The Least Mean Square (LMS) Algorithm:
  3.2. The Normalized Least Mean Square (NLMS) Algorithm
  3.3. Block Based Normalized LMS algorithm
  3.4. The Generalized Normalized Gradient Descent (GNGD) Algorithm
 4. Simulation Results
 5. Conclusion
 References

키워드

Smart antenna LMS BBNLMS GNGD Convergence Rate

저자

  • Y. Murali Krishna [ Dept. of Electronics and Communication Engineering, Narasaraopeta Engineering College, Narasaraopeta, AP, India ]
  • N. Sayedu Khasim [ Dept. of Electronics and Communication Engineering, Narasaraopeta Engineering College, Narasaraopeta, AP, India ]
  • M. Sreedhar [ Dept. of Electronics and Communication Engineering, Narasaraopeta Engineering College, Narasaraopeta, AP, India ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Hybrid Information Technology
  • 간기
    격월간
  • pISSN
    1738-9968
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

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