Open AccessImproved singular value decomposition‐based de‐noising algorithm in digital receiver front‐end
Author(s) -
Hu Lin,
Ma Hong,
Zhang Hua,
Zhao Wen
Publication year - 2017
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2016.0501
Subject(s) - algorithm , singular value decomposition , lagrange multiplier , computer science , noise (video) , singular value , multiplier (economics) , filter (signal processing) , mathematics , mathematical optimization , artificial intelligence , eigenvalues and eigenvectors , physics , quantum mechanics , economics , image (mathematics) , computer vision , macroeconomics
It is commonly acknowledged that most of the output signals of digital receiver front‐end are noisy and cannot be directly delivered to post‐processing subject to the working condition and the limitations of devices. This study presents an improved singular value decomposition‐based de‐noising algorithm by the adoption of time‐domain constrained optimisation. The improved algorithm contains a filter factor which plays a role in distributing information contributions of each retained singular value component to the de‐noised signal, according to the relative contribution of noise in each singular value. The selection methods for several critical factors of the algorithm are discussed, including the noisy matrix, de‐noising order, noise power and Lagrange multiplier. In particular, the effects of de‐noising order and Lagrange multiplier on de‐noising performance are studied. The results of the verification tests of extensive simulations and actual measurements from receiver front‐end show that the proposed algorithm can significantly reduce the background noise and guarantee the integrity of the information contained in the de‐noised signal.