Robust Automatic Modulation Classification in Low Signal to Noise Ratio

Robust Frame Synchronization for Low Signal-to-Noise Ratio Channels Using Energy-Corrected Differential Correlation

Recent standards for wireless transmission require reliable synchronization for channels with low signal-to-noise ratio (SNR) as well as with a large amount of frequency offset, which necessitates a robust correlator structure for the initial frame synchronization process. In this paper, a new correlation strategy especially targeted for low SNR regions is proposed and its performance is analyz...

Robust phase estimation for signals with a low signal-to-noise-ratio

The estimation of time-dependent phase-shifts of distorted signals is an ubiquitous problem in signal-processing. Processing of data from plasma interferometry reveals that the standard approach based on band-pass filtering can result in misleading results already for moderate signal-to-noise ratios. An alternative phase estimation method based on a combination of direct signal matching and a d...

Signal-to-Noise Ratio Estimation

Of the many measures that characterize the performance of a communication receiver, signal-to-noise ratio (SNR) is perhaps the most fundamental in that many of the other measures directly depend on its knowledge for their evaluation. In the design of receivers for autonomous operation, it is desirable that the estimation of SNR take place with as little known information as possible regarding o...

Signal-to-noise ratio in MRI.

in RF receiving coil design. However, modern is proportional to 0 , so that their population imaging techniques often demand very high speed difference is larger at high values of 0 . Since the and spatial resolution, so that the highest possible ratio of the energy difference to thermal energy is SNR is still required to avoid poor image quality. very small, the population difference increases...

Signal Detection and Modulation Classification in Non-Gaussian Noise Environments