NDA waveform estimation in the low-SNR regime

Jóse A. López-Salcedo, Gregori Vázquez

Research output: Contribution to journalArticleResearchpeer-review


This correspondence addresses the problem of nondata-aided waveform estimation for digital communications. Based on the unconditional maximum likelihood criterion, the main contribution of this correspondence is the derivation of a closed-form solution to the waveform estimation problem in the low signal-to-noise ratio regime. The proposed estimation method is based on the second-order statistics of the received signal and a clear link is established between maximum likelihood estimation and correlation matching techniques. Compression with the signal-subspace is also proposed to improve the robustness against the noise and to mitigate the impact of abnormals or outliers. © 2007 IEEE.
Original languageEnglish
Pages (from-to)5864-5868
JournalIEEE Transactions on Signal Processing
Publication statusPublished - 1 Dec 2007


  • Channel estimation
  • Low signal to noise ratio (SNR)
  • Nondata-aided
  • Wavelet transforms
  • waveform estimation


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