Lattice-based subspace decomposition for DS-CDMA detection

Author

Woodward, Graeme ; Honig, Michael L. ; Vucetic, Branka S.

Author_Institution

Dept. of Electr. Eng., Sydney Univ., NSW, Australia

Volume

1

fYear

1998

fDate

2-4 Sep 1998

Firstpage

164

Abstract

Lattice filtering is applied to the MMSE (minimum mean squared error) DS-CDMA receiver. The lattice performs Cholesky decomposition on the sampled input covariance matrix. This identifies information about signal and noise subspaces, which can be exploited to decrease the complexity of the MMSE receiver using LS (least squares) adaptive algorithms. Two reduced complexity techniques are considered: (1) filter truncation and (2) linear combining of multiple truncated subfilters. In both cases, the dimension of the (sub)filters must be larger than that of the user subspace. Numerical results presented compare the performance of these techniques using LMS and LS algorithms

Keywords

code division multiple access; computational complexity; covariance matrices; lattice filters; least mean squares methods; receivers; signal detection; spread spectrum communication; Cholesky decomposition; DS-CDMA detection; MMSE DS-CDMA receiver; complexity; dimension; filter truncation; lattice filtering; lattice-based subspace decomposition; least squares adaptive algorithms; linear combining; minimum mean squared error; multiple truncated subfilters; sampled input covariance matrix; Adaptive algorithm; Lattices; Least squares approximation; Least squares methods; Matched filters; Multiaccess communication; Multiple access interference; Nonlinear filters; Resonance light scattering; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Spread Spectrum Techniques and Applications, 1998. Proceedings., 1998 IEEE 5th International Symposium on

Conference_Location

Sun City

Print_ISBN

0-7803-4281-X

Type

conf

DOI

10.1109/ISSSTA.1998.726219

Filename

726219