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.
|Journal||IEEE Transactions on Signal Processing|
|Publication status||Published - 1 Dec 2007|
- Channel estimation
- Low signal to noise ratio (SNR)
- Wavelet transforms
- waveform estimation