NDLI: Stable adaptive sparse filtering algorithms for estimating multiple-input

Content Provider	IET Digital Library
Author	Gui, Guan Adachi, Fumiyuki
Abstract	Channel estimation problem is one of the key technical issues for broadband multiple-input–multiple-output (MIMO) signal transmission. To estimate the MIMO channel, a standard least mean square (LMS) algorithm was often applied to adaptive channel estimation because of its low complexity and stability. The sparsity of the broadband MIMO channel can be exploited to further improve the estimation performance. This observation motivates us to consider adaptive sparse channel estimation (ASCE) methods using sparse LMS (ASCE-LMS) algorithms. However, conventional ASCE methods have two main drawbacks: (i) sensitivity to random scaling of training signal and (ii) poor estimation performance in low signal-to-noise ratio (SNR) regime. The former drawback is tackled by proposing novel ASCE-NLMS algorithms. ASCE-NLMS mitigates interference of random scale of training signal and therefore it improves its algorithm stability. It is well-known that stable sparse normalised least-mean fourth (NLMF) algorithms can achieve better estimation performance than sparse NLMS algorithms. Therefore the authors propose an improved ASCE method using sparse NLMF algorithms (ASCE-NLMF) to improve the estimation performance in low SNR regime. Simulation results show that the proposed ASCE methods are shown to achieve better performance than conventional methods, that is, ASCE-LMS by computer simulations. Also, the stability of the proposed methods is confirmed by theoretical analysis.
Starting Page	1032
Ending Page	1040
Page Count	9
ISSN	17518628
Volume Number	8
e-ISSN	17518636
Issue Number	Issue 7, May (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/8/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2013.0665
Journal	IET Communications
Publisher Date	2014-03-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Sparse Channel Estimation Algorithm Stability ASCE-NLMS Algorithm Broadband MIMO Channel Broadband Multiple-input-multiple-output Signal Transmission Channel Estimation Communication Channel Equalisation And Identification Filtering Method in Signal Processing Filtering Theory Interpolation And Function Approximation Least Mean Square Least Mean Squares Method MIMO Communication MIMO Signal Transmission Multiple-input-multiple-output Channel Estimation NLMF Algorithm Normalised Least-mean Fourth Numerical Analysis Radio Link And Equipment Signal Processing Stable Adaptive Sparse Filtering Algorithm Training Signal Wireless Channel
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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