Title :
Blind Adaptive Constrained Reduced-Rank Parameter Estimation Based on Constant Modulus Design for CDMA Interference Suppression
Author :
De Lamare, Rodrigo C. ; Haardt, Martin ; Sampaio-Neto, Raimundo
Author_Institution :
Dept. of Electron., Univ. of York, York
fDate :
6/1/2008 12:00:00 AM
Abstract :
This paper proposes a multistage decomposition for blind adaptive parameter estimation in the Krylov subspace with the code-constrained constant modulus (CCM) design criterion. Based on constrained optimization of the constant modulus cost function and utilizing the Lanczos algorithm and Arnoldi-like iterations, a multistage decomposition is developed for blind parameter estimation. A family of computationally efficient blind adaptive reduced-rank stochastic gradient (SG) and recursive least squares (RLS) type algorithms along with an automatic rank selection procedure are also devised and evaluated against existing methods. An analysis of the convergence properties of the method is carried out and convergence conditions for the reduced-rank adaptive algorithms are established. Simulation results consider the application of the proposed techniques to the suppression of multiaccess and intersymbol interference in DS-CDMA systems.
Keywords :
adaptive estimation; code division multiple access; gradient methods; interference suppression; intersymbol interference; least squares approximations; optimisation; recursive estimation; spread spectrum communication; stochastic processes; Arnoldi-like iteration; DS-CDMA system; Krylov subspace; Lanczos algorithm; automatic rank selection procedure; blind adaptive constrained reduced-rank parameter estimation; code-constrained constant modulus design; multiaccess-intersymbol interference suppression; multistage decomposition; optimization; recursive least squares type algorithm; stochastic gradient method; Blind adaptive constrained algorithms; DS-code- division-multiple-access (CDMA) systems; interference suppression; reduced-rank parameter estimation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.913161