Sixth-Order Statistics-Based Non-Data-Aided SNR Estimation

Signal-to-noise ratio (SNR) estimation is an important task in many digital communication systems. With nonconstant modulus constellations, the performance of the classical second- and fourth-order moments estimate is known to degrade with increasing SNR. A new non-data-aided estimate is proposed, w...

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Bibliographic Details
Published in:IEEE communications letters 2007-04, Vol.11 (4), p.351-353
Main Authors: Lopez-Valcarce, R., Mosquera, C.
Format: Article
Language:English
Subjects:
Amplitudes
Applied sciences
Communication systems
Constellations
Degradation
Detection, estimation, filtering, equalization, prediction
Digital
Digital communication
Educational programs
Equipments and installations
Estimates
Exact sciences and technology
Frequency estimation
Information, signal and communications theory
Keying
Mobile radiocommunication systems
Modulation, demodulation
Parameter estimation
Performance loss
Phase estimation
Radiocommunications
Robustness
Signal and communications theory
Signal detection
Signal to noise ratio
Signal, noise
Systems, networks and services of telecommunications
Tasks
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
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Description
Summary:Signal-to-noise ratio (SNR) estimation is an important task in many digital communication systems. With nonconstant modulus constellations, the performance of the classical second- and fourth-order moments estimate is known to degrade with increasing SNR. A new non-data-aided estimate is proposed, which makes use of the sixth-order moment of the received data, and which can be tuned for a particular constellation in order to extend the usable range of SNR values. The advantage of the new method is especially significant for constellations with two different amplitude levels, e.g. 16-amplitude-and-phase-shift keying (16-APSK)
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOM.2007.348298