TY - GEN

T1 - Sparsity-embracing multiuser detection for CDMA systems with low activity factort

AU - Zhu, Hao

AU - Giannakis, Georgios B

PY - 2009/11/19

Y1 - 2009/11/19

N2 - 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 lowactivity 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 l2 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.

AB - 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 lowactivity 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 l2 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.

KW - Compressive sampling

KW - Lasso

KW - Multiuser detection

KW - Sparsity

KW - Sphere decoding

UR - http://www.scopus.com/inward/record.url?scp=70449478520&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70449478520&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2009.5205788

DO - 10.1109/ISIT.2009.5205788

M3 - Conference contribution

AN - SCOPUS:70449478520

SN - 9781424443130

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 164

EP - 168

BT - 2009 IEEE International Symposium on Information Theory, ISIT 2009

T2 - 2009 IEEE International Symposium on Information Theory, ISIT 2009

Y2 - 28 June 2009 through 3 July 2009

ER -