Symbol Detection for Faster-Than-Nyquist Signaling by Sum-of-Absolute-Values Optimization

In this letter, we propose a new symbol detection method in faster-than-Nyquist signaling for effective data transmission. Based on the frame theory, the symbol detection problem is described as underdetermined linear equations on a finite alphabet. While the problem is itself NP (nondeterministic p...

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Veröffentlicht in:IEEE signal processing letters 2016-12, Vol.23 (12), p.1853-1857
Hauptverfasser: Sasahara, Hampei, Hayashi, Kazunori, Nagahara, Masaaki
Format: Artikel
Sprache:eng
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Zusammenfassung:In this letter, we propose a new symbol detection method in faster-than-Nyquist signaling for effective data transmission. Based on the frame theory, the symbol detection problem is described as underdetermined linear equations on a finite alphabet. While the problem is itself NP (nondeterministic polynomial-time) hard, we propose convex relaxation using the sum-of-absolute-values optimization, which can be efficiently solved by proximal splitting. Simulation results are shown to illustrate the effectiveness of the proposed method compared to a recent ℓ ∞ -based (ellinfinity-based) method.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2016.2625839