TY - GEN

T1 - DS/CDMA linear receiver based on Krylov-proportionate adaptive filtering technique - An extension to complex-valued signals

AU - Yukawa, Masahiro

PY - 2008/12/1

Y1 - 2008/12/1

N2 - 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 'sparsity' 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.

AB - 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 'sparsity' 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.

KW - Adaptive filter

KW - CDMA

KW - Krylov subspace

KW - Linear receiver

UR - http://www.scopus.com/inward/record.url?scp=58049149857&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=58049149857&partnerID=8YFLogxK

U2 - 10.1109/MLSP.2008.4685474

DO - 10.1109/MLSP.2008.4685474

M3 - Conference contribution

AN - SCOPUS:58049149857

SN - 9781424423767

T3 - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

SP - 169

EP - 174

BT - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

T2 - 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Y2 - 16 October 2008 through 19 October 2008

ER -