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Proceedings Paper

Adaptive sparse-binary waveform design for all-spectrum channelization
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Paper Abstract

We introduce maximum-SINR, sparse-binary waveforms that modulate data information symbols over the entire continuum of the available/device-accessible spectrum. We present an optimal algorithm that designs the proposed waveforms by maximizing the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum- SINR linear filter at the receiver. In addition, we propose a suboptimal, computationally-efficient algorithm. Simulation studies compare the proposed sparse-binary waveforms with their conventional non-sparse binary counterparts and demonstrate their superior SINR performance. The post-filtering SINR and bit-error rate (BER) improvements attained by the proposed waveforms are also experimentally verified in a software-defined radio testbed operating in multipath laboratory environment, in the presence of colored interference.

Paper Details

Date Published: 5 May 2017
PDF: 12 pages
Proc. SPIE 10211, Compressive Sensing VI: From Diverse Modalities to Big Data Analytics, 102110B (5 May 2017); doi: 10.1117/12.2262311
Show Author Affiliations
George Sklivanitis, Univ. at Buffalo (United States)
Panos P. Markopoulos, Rochester Institute of Technology (United States)
Stella N. Batalama, Univ. at Buffalo (United States)
Dimitris A. Pados, Univ. at Buffalo (United States)

Published in SPIE Proceedings Vol. 10211:
Compressive Sensing VI: From Diverse Modalities to Big Data Analytics
Fauzia Ahmad, Editor(s)

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