Low-Complexity Non-Data-Aided SNR Estimation for Multilevel Constellations | IEEE Journals & Magazine | IEEE Xplore

Low-Complexity Non-Data-Aided SNR Estimation for Multilevel Constellations


Abstract:

Empirical-distribution-function (EDF)-based non-data-aided signal-to-noise ratio (SNR) estimation methods are effective for multilevel constellations but require many mat...Show More

Abstract:

Empirical-distribution-function (EDF)-based non-data-aided signal-to-noise ratio (SNR) estimation methods are effective for multilevel constellations but require many matching operations between reference cumulative distribution functions and EDF. To reduce resource consumption and improve real-time performance, we propose a low-complexity method by simplifying the matching test method. The proposed method modifies the matching operation from two-dimensions (2-D) to 1-D, reducing the number of matching operations and memory resource. Compared to the moment-based methods and the existing EDF-based reduced-complexity methods, the proposed method has the lowest complexity and provides better estimation performance in the medium-to-high SNR range.
Published in: IEEE Communications Letters ( Volume: 24, Issue: 1, January 2020)
Page(s): 113 - 116
Date of Publication: 20 November 2019

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