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Journals / International Journal of Applied Mathematics Electronics and Computers / 2016 / Special Issue (2016)

Reduction of In-Band Interferences’ Effect Using Subspace Algorithms in Radio Channel Data

Seda ÜSTÜN ERCAN
Hülya GÖKALP
Pages
30–32
Publication Date
2016-12-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results show that MUSIC and EV methods have similar results for time delay estimation, and perform better than the FFT method.

📌 3 Key Takeaways

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Objective & Hypothesis:In-band interference increases the noise floor of delay profiles estimated from frequency modulated continuous wave (FMCW) sounder channel data and prevents weak multipath components from being detected.
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Key Findings & Data:In this study two of the subspace methods named MUltiple SIgnal Classification (MUSIC) and EigenVector (EV) algorithm were used to reduce the effect of interference in delay profiles obtained from an FMCW channel data, and the results are compared with those from conventional FFT method.
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Conclusion & Impact:Results show that MUSIC and EV methods have similar results for time delay estimation, and perform better than the FFT method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:In-band interference · RF interference · Music

Abstract

In-band interference increases the noise floor of delay profiles estimated from frequency modulated continuous wave (FMCW) sounder channel data and prevents weak multipath components from being detected. In this study two of the subspace methods named MUltiple SIgnal Classification (MUSIC) and EigenVector (EV) algorithm were used to reduce the effect of interference in delay profiles obtained from an FMCW channel data, and the results are compared with those from conventional FFT method. Results show that MUSIC and EV methods have similar results for time delay estimation, and perform better than the FFT method.

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Cite This Article

ERCAN, S. Ü., GÖKALP, H. (2016). Reduction of In-Band Interferences’ Effect Using Subspace Algorithms in Radio Channel Data. International Journal of Applied Mathematics Electronics and Computers, Special Issue (2016), 30–32. https://ajindex.com/articles/258147

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