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Multiuser detection in flat fading non-Gaussian channels
H. Vincent Poor
, Mario Tanda
Electrical and Computer Engineering
High Meadows Environmental Institute
Center for Statistics & Machine Learning
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Contribution to journal
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Article
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peer-review
54
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Dive into the research topics of 'Multiuser detection in flat fading non-Gaussian channels'. Together they form a unique fingerprint.
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Keyphrases
Multiuser Detection
100%
Flat Fading
100%
Non-Gaussian Channel
100%
Impulsive Noise
100%
Numerical Results
33%
M-estimator
33%
Attendants
33%
Analytical Results
33%
Phase Shift
33%
Code Division multiple Access
33%
Man-made
33%
Multiuser Detector
33%
Flat Fading Channel
33%
Decorrelating Detector
33%
Channel Noise
33%
Algorithmic Complexity
33%
Noncoherent Demodulation
33%
Multiple-access Fading Channels
33%
Realistic Wireless Channel
33%
Performance Gains
33%
Direct-sequence Code-division multiple Access
33%
Phase-shift Keyed Signals
33%
Impulsive Source
33%
Computer Science
Gaussian Channel
100%
Fading Channel
100%
Multiuser Detection
100%
Flat Fading
100%
Code Division Multiple Access
100%
Performance Gain
50%
Transmitted Signal
50%
Wireless Channel
50%
Algorithmic Complexity
50%
Engineering
Multiuser
100%
Gaussians
100%
Code Division Multiple Access
66%
Phase Shift
66%
Fading Channel
33%
Demodulation
33%
Flat Fading Channel
33%