A dual-deconvolution algorithm for radar and communication black-space spectrum sharing

Masoud Farshchian, Ivan Selesnick

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce a dual-deconvolution algorithm for the purpose of black-space spectrum sharing. We consider the case of spectrum sharing between radio-frequency (RF) devices whose data source/scatterers are modeled as a convolution with a pulse-shaping filter. This model encompasses both single-carrier communications as well as pulse-Doppler radars. Preliminary results including the mean-square error (MSE) for the radar system and bit error rate (BER) are provided for a scenario of communications and radar spectrum sharing. These results demonstrate significant improvement in uncoordinated spectrum sharing of radar and wireless communication signals overlapping in time and frequency. The algorithm is implemented using the fast Fourier transform and an iterative procedure that requires no matrix inverse computations. The algorithm also generalizes straightforwardly to multiple-deconvolution scenarios.

Original languageEnglish (US)
Title of host publication2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6-10
Number of pages5
ISBN (Electronic)9781509029204
DOIs
Publication statusPublished - Nov 15 2016
Event4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016 - Aachen, Germany
Duration: Sep 19 2016Sep 23 2016

Other

Other4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
CountryGermany
CityAachen
Period9/19/169/23/16

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ASJC Scopus subject areas

  • Instrumentation
  • Signal Processing

Cite this

Farshchian, M., & Selesnick, I. (2016). A dual-deconvolution algorithm for radar and communication black-space spectrum sharing. In 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016 (pp. 6-10). [7745688] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CoSeRa.2016.7745688