Journal ArticleDOI
Adaptive Reduced-Rank Processing Based on Joint and Iterative Interpolation, Decimation, and Filtering
TLDR
An iterative least squares (LS) procedure to jointly optimize the interpolation, decimation and filtering tasks for reduced-rank adaptive filtering for interference suppression in code-division multiple-access (CDMA) systems is described.Abstract:
We present an adaptive reduced-rank signal processing technique for performing dimensionality reduction in general adaptive filtering problems. The proposed method is based on the concept of joint and iterative interpolation, decimation and filtering. We describe an iterative least squares (LS) procedure to jointly optimize the interpolation, decimation and filtering tasks for reduced-rank adaptive filtering. In order to design the decimation unit, we present the optimal decimation scheme and also propose low-complexity decimation structures. We then develop low-complexity least-mean squares (LMS) and recursive least squares (RLS) algorithms for the proposed scheme along with automatic rank and branch adaptation techniques. An analysis of the convergence properties and issues of the proposed algorithms is carried out and the key features of the optimization problem such as the existence of multiple solutions are discussed. We consider the application of the proposed algorithms to interference suppression in code-division multiple-access (CDMA) systems. Simulations results show that the proposed algorithms outperform the best known reduced-rank schemes with lower complexity.read more
Citations
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Journal ArticleDOI
Set-membership constrained conjugate gradient adaptive algorithm for beamforming
Lei Wang,R.C. de Lamare +1 more
TL;DR: A constrained adaptive filtering strategy based on conjugate gradient and set-membership techniques is presented for adaptive beamforming and two time-varying bounding schemes are introduced to measure the quality of the parameters that could be included in the parameter space.
Journal ArticleDOI
Successive Interference Cancellation via Rank-Reduced Maximum A Posteriori Detection
TL;DR: Simulation results demonstrate the superiority of RR-MAP-SIC over the conventional algorithm and numerically verify the EXIT chart analysis, which examines how the probability of symbol error is changed in terms of the covariance of the residual interference as the number of iterations increases and the covariances of the error events decrease.
Journal ArticleDOI
Compression and Combining Based on Channel Shortening and Reduced-Rank Techniques for Cooperative Wireless Sensor Networks
TL;DR: This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications and proposes a preprocessing block similar to channel shortening (CS), which has a superior BER performance as compared with CS schemes when sensors employ fixed-gain amplification.
Proceedings ArticleDOI
Anomaly detection in IP networks based on randomized subspace methods
TL;DR: Novel randomized subspace methods to detect anomalies in Internet Protocol networks by performing a normal-plus-anomalous matrix decomposition aided by the randomized sampling scheme and subsequently detecting traffic anomalies in the anomalous subspace using a statistical test.
Proceedings ArticleDOI
Knowledge-aided STAP algorithm using convex combination of inverse covariance matrices for heterogenous clutter
TL;DR: This paper develops a KA-STAP algorithm to estimate the inverse interference covariance matrix rather than the covariANCE matrix itself, by combining the inverse of the covariance known a priori, R0-1, and the inverse sample covariance Matrix estimate R̂-1.
References
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Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.