Title :
Sparsity-embracing multiuser detection for CDMA systems with low activity factory
Author :
Zhu, Hao ; Giannakis, Georgios B.
Author_Institution :
Dept. of ECE, Univ. of Minnesota, Minneapolis, MN, USA
fDate :
June 28 2009-July 3 2009
Abstract :
The number of active users in code-division multiple access (CDMA) systems is often much lower than the spreading gain. The present paper exploits fruitfully this a priori information to improve performance of multiuser detectors. A low-activity factor manifests itself in a sparse symbol vector with entries drawn from a finite alphabet that is augmented by the zero symbol to capture user inactivity. The non-equiprobable symbols of the augmented alphabet motivate a sparsity-exploiting maximum a posteriori probability (S-MAP) criterion, which is shown to yield a cost comprising the lscr2 least-squares error penalized by the p-th norm of the wanted symbol vector (p = 0; 1; 2). Related optimization problems appear in variable selection (shrinkage) schemes developed for linear regression, as well as in the emerging field of compressive sampling (CS). The contribution of this work to CDMA systems is a gamut of sparsity-embracing multiuser detectors trading off performance for complexity requirements. From the vantage point of CS and the least-absolute shrinkage selection operator (Lasso) spectrum of applications, the contribution amounts to sparsity-exploiting algorithms when the entries of the wanted signal vector adhere to finite-alphabet constraints.
Keywords :
code division multiple access; least squares approximations; multiuser detection; probability; regression analysis; CDMA systems; a priori information; code division multiple access; finite alphabet; least-absolute shrinkage selection operator; least-squares error; linear regression; low activity factor; maximum a posteriori probability; sparse symbol vector; sparsity embracing multiuser detection; Collaborative work; Costs; Detectors; Input variables; Linear regression; Multiaccess communication; Multiuser detection; Production facilities; Sampling methods; Vectors; Compressive Sampling; Lasso; Multiuser Detection; Sparsity; Sphere Decoding;
Conference_Titel :
Information Theory, 2009. ISIT 2009. IEEE International Symposium on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-4312-3
Electronic_ISBN :
978-1-4244-4313-0
DOI :
10.1109/ISIT.2009.5205788