A Sparse Approach for Identification of Signal Constellations Over Additive Noise Channels

DÜLEK B.

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, cilt.56, sa.1, ss.817-822, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Editöre Mektup
  • Cilt numarası: 56 Sayı: 1
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/taes.2019.2909726
  • Dergi Adı: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.817-822
  • Hacettepe Üniversitesi Adresli: Evet

Özet

Identification of unknown linear modulations over arbitrary additive noise channels is addressed within the framework of sparse linear regression. A regularized least squares problem with a sparsity inducing penalty is formulated to estimate the distribution of the transmitted symbols, which complete characterizes the underlying signal constellation. Separable and iterative algorithms that deliver reduced computational complexity are obtained based on the majorization-minimization framework. The proposed method can be employed to construct a modulation dictionary tailored to the target communications system before performing hypothesis testing-based classification.