Joint Modulation Classification and Detection Using Sphere Decoding

In this letter, we propose a simple yet effective modulation classification method for maximum likelihood multiuser detection. Our method is a modification of generalized likelihood ratio test (GLRT) that approximates the optimal classifier in the Bayesian sense. We show that the proposed method can...

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Bibliographic Details
Published in:IEEE signal processing letters 2009-09, Vol.16 (9), p.778-781
Main Authors: Byonghyo Shim, Byonghyo Shim, Insung Kang, Insung Kang
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Bayesian methods
Classification
Decoding
Detectors
Gain
Generalized likelihood ratio test (GLRT)
High speed
Interference
Likelihood ratio
Maximum likelihood decoding
Maximum likelihood detection
Maximum likelihood estimation
Modulation
modulation classification
Multiuser detection
Performance gain
Signal to noise ratio
sphere decoding
Testing
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Summary:In this letter, we propose a simple yet effective modulation classification method for maximum likelihood multiuser detection. Our method is a modification of generalized likelihood ratio test (GLRT) that approximates the optimal classifier in the Bayesian sense. We show that the proposed method can be implemented by modifying the sphere decoding algorithm to support multimodulation. Simulation results in multiuser detection in high-speed downlink packet access (HSDPA) system show that the proposed method offers considerable performance gain over conventional RAKE and MMSE algorithms.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2009.2024805