A compact neural-network-based CDMA receiver

David C. Chen; Bing J. Sheu

doi:10.1109/82.664245

A compact neural-network-based CDMA receiver

David C. Chen^*, Bing J. Sheu

^*Corresponding author for this work

CenterUniversity of Southern CaliforniaLos

Research output: Contribution to journal › Journal Article › peer-review

10 Scopus citations

Abstract

A compact neural-network receiver for code-division multiple-access (CDMA) communication is presented. In the CDMA schemethe near-far problem is a major impediment for the performance of a conventional detector (CD). By using a compact neural network with hardware annealing function and gradient-descent optimization techniquean optimal multiuser receiver can be implemented. The algorithm and simulation results of the compact neural-network-based CDMA receiver are described in this brief.

Original language	English
Pages (from-to)	384-387
Number of pages	4
Journal	IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Volume	45
Issue number	3
DOIs	https://doi.org/10.1109/82.664245
State	Published - 1998
Externally published	Yes

Keywords

Optimizationmultimedianeural networkreceiverspread spectrumwireless communication

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10.1109/82.664245

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AB - A compact neural-network receiver for code-division multiple-access (CDMA) communication is presented. In the CDMA schemethe near-far problem is a major impediment for the performance of a conventional detector (CD). By using a compact neural network with hardware annealing function and gradient-descent optimization techniquean optimal multiuser receiver can be implemented. The algorithm and simulation results of the compact neural-network-based CDMA receiver are described in this brief.

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M3 - 文章

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A compact neural-network-based CDMA receiver

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Keywords

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