The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Blind equalization and multiuser detection in dispersive CDMA channels
Abstract
The problem of blind demodulation of multiuser information symbols in a high-rate code-division multiple-access (CDMA) network in the presence of both multiple-access interference (MAI) and intersymbol interference (ISI) is considered. The dispersive CDMA channel is first cast into a multiple-input multiple-output (MIMO) signal model framework. By applying the theory of blind MIMO channel identification and equalization, it is then shown that under certain conditions the multiuser information symbols can be recovered without any prior knowledge of the channel or the users' signature waveforms (including the desired user's signature waveform), although the algorithmic complexity of such an approach is prohibitively high. However, in practice, the signature waveform of the user of interest is always available at the receiver. It is shown that by incorporating this knowledge, the impulse response of each user's dispersive channel can be identified using a subspace method. It is further shown that based on the identified signal subspace parameters and the channel response, two linear detectors that are capable of suppressing both MAI and ISI, i.e., a zero-forcing detector and a minimum-mean-square-error (MMSE) detector, can be constructed in closed form, at almost no extra computational cost. Data detection can then be furnished by applying these linear detectors (obtained blindly) to the received signal. The major contribution of this paper is the development of these subspace-based blind techniques for joint suppression of MAI and ISI in the dispersive CDMA channels.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Detection of signals by information theoretic criteria
Wax, M., & Kailath, T. (1985) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1985.1164557 · Cited by 3,426
The Differentiation of Pseudo-Inverses and Nonlinear Least Squares Problems Whose Variables Separate
Golub, G. H., & Pereyra, V. (1973) · SIAM Journal on Numerical Analysis · doi:10.1137/0710036 · Cited by 1,430
Projection approximation subspace tracking
Yang, B. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.365290 · Cited by 1,273
Tracking a few extreme singular values and vectors in signal processing
Comon, P., & Golub, G. H. (1990) · Proceedings of the IEEE · doi:10.1109/5.58320 · Cited by 489
Subspace-based channel estimation for code division multiple access communication systems
Bensley, S. E., & Aazhang, B. (1996) · IEEE Transactions on Communications · doi:10.1109/26.535441 · Cited by 485
An updating algorithm for subspace tracking
Stewart, G. W. (1992) · IEEE Transactions on Signal Processing · doi:10.1109/78.139256 · Cited by 326
Nonlinear adaptive prediction of nonstationary signals
Haykin, S., & Li, L. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.348134 · Cited by 228
Cited by
Nonconvex Demixing From Bilinear Measurements
Dong, J., & Shi, Y. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2864660 · Cited by 37
Metadata
- Authors
- Wang, X., & Poor, H. V.
- Venue
- IEEE Transactions on Communications
- Published
- 1998
- Volume
- 46
- Issue
- 1
- Pages
- 91-103
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W2159187245
- Cited by
- 391
- References
- 7
- FWCI
- 40.80
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Blind equalization and multiuser detection in dispersive CDMA channels. https://app.cochat.ai/papers/10.1109/26.655407
- The paper
- Wang, X., & Poor, H. V. (1998). Blind equalization and multiuser detection in dispersive CDMA channels. IEEE Transactions on Communications. https://doi.org/10.1109/26.655407
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.