An improved LMS adaptive algorithm for narrowband interference suppression in direct sequence spread spectrum
01 Jul 1995-IEEE Transactions on Aerospace and Electronic Systems (IEEE)-Vol. 31, Iss: 3, pp 1198-1201
TL;DR: In this article, a new adaptive least mean squares (LMS) algorithm to increase the slow convergence of their nonlinear adaptive filter is described. But the main drawback of their adaptive nonlinear filter is its slow convergence rate.
Abstract: In 1990 Vijayan and Poor proposed nonlinear predictive methods for suppressing narrowband interference in spread spectrum (SS) systems with a significant increase in signal-to-noise ratio (SNR) improvement. The main drawback of their adaptive nonlinear filter is its slow convergence rate. A new adaptive least mean squares (LMS) algorithm to increase the slow convergence of their nonlinear adaptive filter is described. Computer simulation results are presented to support the advantages of the new filter. >
Citations
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TL;DR: The present bibliography represents a comprehensive list of references on nonlinear system identification and its applications in signal processing, communications, and biomedical engineering.
242 citations
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TL;DR: A progression of techniques is described, in which successively more information about the spread-spectrum signal and interference is used to make improvements on the interference suppression capability via more advanced signal processing methods.
Abstract: Communication networks involving the overlay of spread-spectrum systems an narrower band services are of increasing interest as a means of producing greater efficiencies and flexibility in the use of the radio spectrum. Although spread-spectrum systems enjoy a natural immunity to interference from narrowband sources, their performance in the presence of such interference can be significantly enhanced by active suppression techniques. The study of this problem has elicited a very rich body of methodology, which has progressed over nearly 25 years from some of the simplest signal processing paradigms to some of the most advanced. This paper provides an overview of a number of these techniques, most of which have been developed over the past decade. In particular, a progression of techniques is described, in which successively more information about the spread-spectrum signal and interference is used to make improvements on the interference suppression capability via more advanced signal processing methods. These include linear predictive methods that make use of the spectral properties of the spread-spectrum and narrowband signals, nonlinear predictive methods that make use of the spectra and first-order probability distribution of these signals, linear code-aided methods that make use of the spreading codes of the signals of interest and the second-order statistics of the narrowband interference, and finally, a maximum-likelihood code-aided technique that makes use of essentially all that is known about the useful signals and interference. Performance comparisons show that moving up this progression of improved modeling is rewarded with performance gains that can be quite significant.
73 citations
07 Aug 2002
TL;DR: A tutorial overview of the progress made in this area over the past 15 years is provided, focusing on direct-sequence CDMA (DS/CDMA) systems and on the so-called "code-aided" techniques for NBI suppression, a term coined to indicate those strategies in which knowledge of the spreading code of a SS signal of interest is explicitly exploited in suppressing NBI.
Abstract: The push toward more efficient and flexible use of the radio spectrum has led to the consideration of the overlay of spread-spectrum (SS) communication networks on preexisting narrow-band networks. Such systems are already in widespread and rapidly expanding use in the lightly regulated spectrum where personal networking is largely centered and they are of increasing interest in the more tightly regulated spectrum due to a dearth of spectrum for new services, the desire to incorporate multi-rate (e.g., multimedia) traffic in the same network and the survival of legacy systems. Even though SS signals are inherently robust to the effects of narrower bandwidth cochannel signals, it has been shown that the use of additional processing aimed at interference suppression can result in substantial performance improvement. Motivated by this consideration, the past quarter century has seen the development of a very large body of techniques for improving the performance of SS communications systems in the presence of narrow-band interference (NBI). Early techniques (up to late 1980s) have been reviewed in the survey by Milstein (1988). Since that time, more sophisticated strategies have been developed, making use of advances from the fields of beamforming, multiuser detection (MUD), and adaptive filtering. Also, the focus of interest has shifted from techniques aimed primarily at the suppression of NBI from single-user SS systems to systems in which the SS signaling is being used to implement a code-division multiple-access (CDMA) protocol. This paper provides a tutorial overview of the progress made in this area over the past 15 years. The focus of the paper is on direct-sequence CDMA (DS/CDMA) systems and on the so-called "code-aided" techniques for NBI suppression, a term coined to indicate those strategies in which knowledge of the spreading code of a SS signal of interest is explicitly exploited in suppressing NBI. Particular attention is devoted to the case in which the CDMA signals are subject to frequency-selective fading and to the issue of blind adaptive MUD in the presence of external NBI. In particular with regard to the former issue, the effects and implications of channel-state information on system design and performance are discussed. With regard to the latter issue, it is observed that the external NBI may introduce the need for a periodically time-varying detection rule, which has significant implications in the design of blind adaptive MUD algorithms for overlaid DS/CDMA systems. The performance of the techniques discussed is compared through analysis and simulation, as well as through considerations of their relative computational complexity and required prior information. Finally, the paper is concluded by a discussion of several challenging open problems in this area.
64 citations
TL;DR: An adaptive nonlinear predictor that consists of an (N+1)-level quantizer, four adders, and two adaptive linear filters that achieves almost the same performance even at very low signal-to-noise ratio but involves much less complexity.
Abstract: This paper presents a new nonlinear approach for narrowband interference (NBI) suppression in code-division multiple-access (CDMA) systems. The proposed scheme is an adaptive nonlinear predictor that consists of an (N+1)-level quantizer, four adders, and two adaptive linear filters, where N is the number of users in the CDMA system. Both adaptive filters have the same coefficients at each iteration: one for feedforward estimation of NBI and the other for feedback compensation for the estimated result. It could be regarded as an improved version of the nonlinear predictor with offset outputs presented recently by Wang et al. (1996). Computer simulation results support that the improved offset predictor performs much better than the original one under the same complexity. As compared with the nearly optimal approximate conditional mean filter, it achieves almost the same performance even at very low signal-to-noise ratio but involves much less complexity.
25 citations
TL;DR: The proposed adaptive techniques for narrowband interference (NBI) suppression in DS-CDMA system are blind and provide faster convergence speed than the pure code-aided approach (without using a predictor and subtractor), but also give better BER performance.
Abstract: When overlaying spread spectrum (SS) transmission over a narrowband system, the performance of the spread spectrum system will be significantly degraded due to the interference from the narrowband signal. This paper proposes two computationally attractive and efficient adaptive techniques for narrowband interference (NBI) suppression in DS-CDMA system: adaptive linear predictor algorithm and adaptive NBI re-estimation algorithm. Unlike existing techniques in literature which use either estimator/subtracter approach or code-aided approach, the proposed methods combine these two approaches together and show that a much better performance can be achieved. In addition, the proposed algorithms are blind and do not require any training symbols and interference characteristics. The proposed methods not only provide faster convergence speed than the pure code-aided approach (without using a predictor and subtractor), but also give better BER performance
24 citations
References
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TL;DR: It is shown here that the output samples of the adaptive filter possess approximately Gaussian statistics under the conditions of slow convergence and a large number of filter taps.
Abstract: The Widrow LMS algorithm is considered for the implementation of an adaptive prewhitening filter in a direct-sequence (DS) spread-spectrum receiver. Exact expressions for the steady-state tapweight covariance matrix and resulting average excess mean square error are developed for the real LMS algorithm when the input contains a random binary sequence (used to model a pseudonoise spreading sequence). It is shown here that the output samples of the adaptive filter possess approximately Gaussian statistics under the conditions of slow convergence and a large number of filter taps. Using this approximation, expressions for the resulting bit error rate (BER) when the adaptive algorithm is used to suppress a fading gone jammer are developed, and numerical results obtained from these expressions are compared to simulation results for the DS receiver.
76 citations
TL;DR: In this article, a nonlinear filter is proposed to produce predictions of the interfering signals that are then subtracted from the received signal to suppress the interference, and the independence of the filtering procedures from the noise distribution shape, given constant second-order statistics, is shown.
Abstract: Suppression algorithms are developed first for a channel containing only impulsive background noise and then for a channel containing a spread-spectrum signal as well. These algorithms are based on nonlinear filters that produce predictions of the interfering signals that are then subtracted from the received signal to suppress the interference. Several such filters, including both fixed and adaptive ones, are proposed and compared using extensive computer simulations. The independence of the filtering procedures from the noise distribution shape, given constant second-order statistics, is shown. >
56 citations