Adaptive Demodulation in Symmetric Alpha-Stable Impulse Noise Channels
| Autor: | Kristoffer Hagglund, Erik Axell |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Estimation theory Monte Carlo method 020206 networking & telecommunications 020302 automobile design & engineering 02 engineering and technology Interference (wave propagation) Impulse noise Noise 0203 mechanical engineering Interference (communication) 0202 electrical engineering electronic engineering information engineering Demodulation Limit (mathematics) Algorithm Decoding methods Computer Science::Information Theory |
| Zdroj: | VTC Spring |
| DOI: | 10.1109/vtc2020-spring48590.2020.9129383 |
| Popis: | In this work, we propose a novel algorithm for adaptive demodulation in impulse noise channels. The proposed method computes appropriate log-likelihood ratios (LLR) based on four previously established parameter estimation techniques of Symmetric $\alpha -$Stable noise. The methods are evaluated with Monte Carlo simulations and shown to outperform the compared demodulators. Simulations show that the methods perform close to the theoretical limit in different proportions of impulse noise and in pure, randomized $\alpha -$Stable interference. The proposed adaptive demodulation technique can be used to improve decoding or demodulation performance in many real-world situations where non-Gaussian interference commonly occurs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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