Analysis of Reduced Complexity Widely-Linear Adaptive Forgetting-Factor Inverse Square-Root Recursive Least Squares algorithm

Suchada Sitjongsataporn
Department of Electronic Engineering, Mahanakorn Institute of Innovation
Faculty of Engineering, Mahanakorn University of Technology
140 Cheumsamphan Rd., Nongchok, Bangkok 10530 Thailand
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Theerayod Wiangtong
Department of Electrical Engineering, Faculty of Engineering
King Mongkut’s Institute of Technology Ladkrabang
1 Chalongkrung Rd., Ladkrabang, Bangkok 10520 Thailand
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Manuscript received April 17, 2019
Revised June 15, 2019

ABSTRACT
Based on widely-linear approach, the proposed reduced complexity inverse square-root recursive least squares algorithm is presented with the methods of adaptive forgetting-factor algorithm. The proposed reduced complexity widely-linear approaches based on inverse square-root recursive least squares algorithm is introduced for a relation between widely-linear and reduced complexity mechanism. By using mean square deviation approach, the proposed optimal forgetting-factor mechanism for optimal gain sequence is presented. Adaptive forgetting-factor inverse square-root recursive least squares algorithm is considered with regard to an optimal forgetting-factor algorithm. A reduced-complexity widely-linear inverse square-root recursive least squares algorithm with the adaptive inverse square-root mechanism, called QR-decomposition for single-carrier frequency-domain equalization systems is presented. Simulation results show that the performance of proposed algorithm is shown that similar to widely-linear approach compared with the conventional algorithm.

Keywords: Widely-Linear approach, Reduced complexity scheme, adaptive inverse square-root recursive least squares algorithm, adaptive forgetting-factor algorithm.

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