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Author

R. Iltis

Bio: R. Iltis is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Spread spectrum & Filter (signal processing). The author has an hindex of 1, co-authored 1 publications receiving 127 citations.

Papers
More filters
Journal ArticleDOI
TL;DR: It is shown that the most common LLSE filter design can lead to performance inferior to that of various other filter designs, but results are also presented demonstrating that an LLSEfilter design motivated by the structure of the maximum-likelihood receiver leads to consistently superior performance.
Abstract: Linear least squares estimation (LLSE) techniques can provide an effective means of suppressing narrow-band interference in direct sequence (DS) spread-spectrum systems. In the results presented here, analytical expressions for bit error rate are derived for two DS spread-spectrum systems under the conditions of either tone or narrowband Gaussian interference. It is shown that the most common LLSE filter design can lead to performance inferior to that of various other filter designs. However, results are also presented demonstrating that an LLSE filter design motivated by the structure of the maximum-likelihood receiver leads to consistently superior performance. The performance of a system using this new design criterion is compared with that of an approximation to the maximum-likelihood (ML) receiver for the tone interference model and with that of the exact ML receiver for the Gaussian interference. Finally, it is shown that the bit error rate estimate obtained from application of a Gaussian approximation for the test statistic is overly pessimistic for the systems studied here.

132 citations


Cited by
More filters
Journal ArticleDOI
01 Jun 1988
TL;DR: In this article, two general types of narrowband interference suppression schemes are discussed and an overview is presented for several other techniques, including least-mean-square estimation and transform-domain processing.
Abstract: It is argued that the ability of a spread-spectrum system to withstand interference, both intentional and unintentional, is probably its greatest asset. Any spread spectrum receiver can only suppress a given amount of interference; if the level of interference becomes too great, the system will not function properly. Even under these latter circumstances, however, other techniques, which enhance the performance of the system over and above the performance improvement that comes automatically to systems from using spread spectrum, are available for use. These techniques typically involve some type of additional signal processing and are examined here. Two general types of narrowband interference suppression schemes are discussed and an overview is presented for several other techniques. The two classes of rejection schemes emphasized are (1) those based on least-mean-square estimation techniques, and (2) those based on transform-domain processing structures. >

566 citations

Journal ArticleDOI
TL;DR: In this article, the characteristics of spread spectrum that make it advantageous for mobile communications are described, and the parameters that determine both the performance and the total capacity are introduced, and an analysis which yields (approximately) the number of users that can simultaneously communicate, while maintaining a specified level of performance.
Abstract: The characteristics of spread spectrum that make it advantageous for mobile communications are described. The parameters that determine both the performance and the total capacity are introduced, and an analysis which yields (approximately) the number of users that can simultaneously communicate, while maintaining a specified level of performance, is presented. Spread spectrum overlay, wherein a code-division multiple-access (CDMA) network shares a frequency band with narrow-band users, is analyzed, and it is seen that excision of the narrowband signals from the CDMA receivers before despreading can improve both performance and capacity. >

532 citations

Journal ArticleDOI
TL;DR: Simulations indicate that the nonlinear filter with LMS updates performs substantially better than the linear filter for both narrowband Gaussian and single-tone interferers, whereas the gradient algorithm gives slightly better performance for Gaussian interferers but is rather ineffective in suppressing a sinusoidal interferer.
Abstract: The binary nature of direct-sequence signals is exploited to obtain nonlinear filters that outperform the linear filters hitherto used for this purpose. The case of a Gaussian interferer with known autoregressive parameters is considered. Using simulations, it is shown that an approximate conditional mean (ACM) filter of the Masreliez type performs significantly better than the optimum linear (Kalman-Bucy) filter. For the case of interferers with unknown parameters, the nature of the nonlinearity in the ACM filter is used to obtain an adaptive filtering algorithm that is identical to the linear transversal filter except that the previous prediction errors are transformed nonlinearly before being incorporated into the linear prediction. Two versions of this filter are considered: one in which the filter coefficients are updated using the Widrow LMS algorithm, and another in which the coefficients are updated using an approximate gradient algorithm. Simulations indicate that the nonlinear filter with LMS updates performs substantially better than the linear filter for both narrowband Gaussian and single-tone interferers, whereas the gradient algorithm gives slightly better performance for Gaussian interferers but is rather ineffective in suppressing a sinusoidal interferer. >

189 citations

Journal ArticleDOI
TL;DR: A self-coherence anti-jamming scheme is introduced which relies on the unique structure of the coarse/acquisition (C/A) code of theatellite signals to excise interferers that have different temporal structures from that of the satellite signals.
Abstract: This paper considers interference suppression and multipath mitigation in Global Navigation Satellite Systems (GNSSs). In particular, a self-coherence anti-jamming scheme is introduced which relies on the unique structure of the coarse/acquisition (C/A) code of the satellite signals. Because of the repetition of the C/A-code within each navigation symbol, the satellite signals exhibit strong self-coherence between chip-rate samples separated by integer multiples of the spreading gain. The proposed scheme utilizes this inherent self-coherence property to excise interferers that have different temporal structures from that of the satellite signals. Using a multiantenna navigation receiver, the proposed approach obtains the optimal set of beamforming coefficients by maximizing the cross correlation between the output signal and a reference signal, which is generated from the received data. It is demonstrated that the proposed scheme can provide high gains toward all satellites in the field of view, while suppressing strong interferers. By imposing constraints on the beamformer, the proposed method is also capable of mitigating multipath that enters the receiver from or near the horizon. No knowledge of either the transmitted navigation symbols or the satellite positions is required.

131 citations

Journal ArticleDOI
TL;DR: The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Crame/spl acute/r-Rao lower bound of the problem at hand.
Abstract: This paper addresses the estimation of the code-phase (pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code- and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Crame/spl acute/r-Rao lower bound of the problem at hand.

128 citations