Abstract
This paper links the direct-sequence code-division multiple access (DS-CDMA) multiuser separation-equalization-detection problem to the parallel factor (PARAFAC) model, which is an analysis tool rooted in psychometrics and chemometrics. Exploiting this link, it derives a deterministic blind PARAFAC DS-CDMA receiver with performance close to non-blind minimum mean-squared error (MMSE). The proposed PARAFAC receiver capitalizes on code, spatial, and temporal diversity-combining, thereby supporting small sample sizes, more users than sensors, and/or less spreading than users. Interestingly, PARAFAC does not require knowledge of spreading codes, the specifics of multipath (interchip interference), DOA-calibration information, finite alphabet/constant modulus, or statistical independence/whiteness to recover the information-bearing signals. Instead, PARAFAC relies on a fundamental result regarding the uniqueness of low-rank three-way array decomposition due to Kruskal (and generalized herein to the complex-valued case) that guarantees identifiability of all relevant signals and propagation parameters. These and other issues are also demonstrated in pertinent simulation experiments.
Original language | English (US) |
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Pages (from-to) | 810-823 |
Number of pages | 14 |
Journal | IEEE Transactions on Signal Processing |
Volume | 48 |
Issue number | 3 |
DOIs | |
State | Published - 2000 |
Externally published | Yes |
Bibliographical note
Funding Information:Manuscript received December 29, 1998; revised August 17, 1999. This work was supported by NSF/CAREER CCR-9733540, NSF CCR-9805350, the Nordic Industry Foundation Project P93-149, and the F;TEK Foundation, through Prof. L. Munck. The associate editor coordinating the review of this paper and approving it for publication was Prof. Michail K. Tsatsanis.