Blind Channel Identification Based on Eigenvalue Decomposition Using Constrained LMS Algorithm

• AHN Kyung Seung

  Department of Electronic Engineering, Chonbuk National University

• BYUN Eul Chool

  Department of Electronic Engineering, Chonbuk National University

• BAIK Heung Ki

  Division of Electronics & Information Engineering, Electronics & Information Advanced Technology Research Center, Chonbuk National University

抄録

Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. Adaptive blind channel identification techniques based on a off-line least-squares approach have been, proposed but this method assumes noise-free case. The method resorts to an adaptive filter with a linear constraint. This paper proposes a new approach based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.

収録刊行物

• IEICE transactions on communications

  IEICE transactions on communications 85 (5), 961-966, 2002-05-01

  一般社団法人電子情報通信学会

キーワード

• blind channel estimation
• constrained LMS
• eigenvalue decomposition

詳細情報

• CRID: 1571135652465786624
• NII論文ID: 110003219418
• NII書誌ID: AA10826261
• ISSN: 09168516
• 本文言語コード: en
• データソース種別:
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