DS/CDMA linear receiver based on Krylov-proportionate adaptive filtering technique—an extension to complex-valued signals

This paper presents a novel training-based adaptive linear receiver to suppress the multiple access interference, which has been one of the central issues in DS/CDMA wireless communication systems. The proposed receiver is derived by extending the Krylov-proportionate normalized least-mean-square (KPNLMS) algorithm to complex-valued signals. The key idea of KPNLMS is (a) sparse representation of the minimum mean square error (MMSE) receiver based on a certain Krylov subspace, (b) use of the dasiasparsitypsila for fast convergence, and (c) simplification to keep linear complexity per iteration. To clarify the convergence properties of the proposed receiver, its derivation from the variable-metric version of the adaptive projected subgradient method (V-APSM) is presented. The simulation results demonstrate the efficacy of the proposed receiver.

[1]  Sergio Verdú,et al.  Linear multiuser detectors for synchronous code-division multiple-access channels , 1989, IEEE Trans. Inf. Theory.

[2]  W. Y. Chen,et al.  A variable step size LMS algorithm , 1990, Proceedings of the 33rd Midwest Symposium on Circuits and Systems.

[3]  M. Yukawa.  On whitening for Krylov-proportionate normalized least-mean-square algorithm , 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.

[4]  B. Vucetic,et al.  Adaptive detection for DS-CDMA , 1998, Proc. IEEE.

[5]  Isao Yamada,et al.  Adaptive Parallel Quadratic-Metric Projection Algorithms , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[6]  Isao Yamada,et al.  Adaptive Parallel Variable-Metric Projection Algorithm -An Application to Acoustic Echo Cancellation , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[7]  D. Luenberger.  Optimization by Vector Space Methods , 1968 .

[8]  Isao Yamada,et al.  Multiaccess Interference Suppression in Orthogonal Space–Time Block Coded MIMO Systems by Adaptive Projected Subgradient Method , 2008, IEEE Transactions on Signal Processing.

[9]  S.L. Gay,et al.  An efficient, fast converging adaptive filter for network echo cancellation , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).

[10]  I. Yamada,et al.  Adaptive Projected Subgradient Method for Asymptotic Minimization of Sequence of Nonnegative Convex Functions , 2005 .

[11]  Behnaam Aazhang,et al.  Multistage detection in asynchronous code-division multiple-access communications , 1990, IEEE Trans. Commun..

[12]  Masahiro Yukawa.  Krylov-proportionate NLMS algorithm based on multistage Wiener filter representation , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[14]  Sergios Theodoridis,et al.  Online Kernel-Based Classification Using Adaptive Projection Algorithms , 2008, IEEE Transactions on Signal Processing.

[15]  I. Yamada,et al.  The Adaptive Projected Subgradient Method over the Fixed Point Set of Strongly Attracting Nonexpansive Mappings , 2006 .

[16]  Kazuhiko Ozeki,et al.  An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties , 1984 .

[17]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[18]  Isao Yamada,et al.  An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques , 2002, IEEE Trans. Signal Process..

[19]  Donald L. Duttweiler,et al.  Proportionate normalized least-mean-squares adaptation in echo cancelers , 2000, IEEE Trans. Speech Audio Process..

[20]  Masahiro Yukawa,et al.  Krylov-Proportionate Adaptive Filtering Techniques Not Limited to Sparse Systems , 2009, IEEE Transactions on Signal Processing.

[21]  V. John Mathews,et al.  A stochastic gradient adaptive filter with gradient adaptive step size , 1993, IEEE Trans. Signal Process..

[22]  Tyseer Aboulnasr,et al.  A robust variable step-size LMS-type algorithm: analysis and simulations , 1997, IEEE Trans. Signal Process..

[23]  Shin'ichi Koike,et al.  A class of adaptive step-size control algorithms for adaptive filters , 2002, IEEE Trans. Signal Process..

[24]  John G. Proakis,et al.  Digital Communications , 1983 .

[25]  T. Hinamoto,et al.  Extended theory of learning identification , 1975 .

[26]  Upamanyu Madhow,et al.  MMSE interference suppression for direct-sequence spread-spectrum CDMA , 1994, IEEE Trans. Commun..