NDLI: Reduced-Rank Linear Interference Suppression for DS-UWB Systems Based on Switched Approximations of Adaptive Basis Functions

Content Provider	IEEE Xplore Digital Library
Author	Sheng Li de Lamare, R.C. Rui Fa
Copyright Year	1967
Abstract	In this paper, we propose a novel low-complexity reduced-rank scheme and consider its application to linear interference suppression in direct-sequence ultrawideband systems (DS-UWB). First, we investigate a generic reduced-rank scheme that jointly optimizes a projection vector and a reduced-rank filter by using the minimum mean square error (MMSE) criterion. Then, a low-complexity scheme, which are denoted the switched approximation of adaptive basis functions (SAABFs), is proposed. The SAABF scheme is an extension of the generic scheme, in which the complexity reduction is achieved by using a multibranch framework to simplify the structure of the projection vector. Adaptive implementations for the SAABF scheme are developed by using least mean squares (LMS) and recursive least squares (RLS) algorithms. We also develop algorithms for selecting the branch number and the model order of the SAABF scheme. Simulations show that, in the scenarios with severe intersymbol interference (ISI) and multiple-access interference (MAI), the proposed SAABF scheme has fast convergence and remarkable interference suppression performance with low complexity.
Sponsorship	IEEE Vehicular Technology Society
Starting Page	485
Ending Page	497
Page Count	13
File Size	892912
File Format	PDF
ISSN	00189545
Volume Number	60
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Complexity theory Interference suppression Algorithm design and analysis Adaptation model Optimization Convergence ultrawideband (UWB) systems Adaptive filters interference suppression reduced-rank methods
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Automotive Engineering Computer Networks and Communications Electrical and Electronic Engineering Aerospace Engineering

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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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