Fading Channel Coding Based on Entropy and Compressive Sensing
| Autor: | Kostas E. Psannis, Theofanis Xifilidis |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Noise measurement
020206 networking & telecommunications Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Inverse problem Computer Science::Performance symbols.namesake Compressed sensing Rician fading 0202 electrical engineering electronic engineering information engineering symbols Fading Statistical physics Rayleigh scattering Computer Science::Information Theory Central limit theorem Mathematics Coding (social sciences) |
| Zdroj: | 2020 3rd World Symposium on Communication Engineering (WSCE). |
| DOI: | 10.1109/wsce51339.2020.9275582 |
| Popis: | In this paper, channel code length is investigated under Rayleigh and Rician fading assumptions along with additive noise consideration. Fading distributions means and variances are known. Rayleigh and Rician fading along with Central Limit Theorem are used in entropy calculations. Compressive Sensing reduced number of samples for distributions reconstruction are also derived. Finally, the inverse problem of identifying the corresponding distributions from the derived channel code lengths and Compressive Sensing based number of samples is addressed with promising results for distribution channel knowledge and estimation. |
| Databáze: | OpenAIRE |
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