A maximum entropy approach for blind deconvolution
Signal Processing - Fractional calculus applications in signals and systems
Multi-user pdf estimation based criteria for adaptive blind separation of discrete sources
Signal Processing - Special issue: Information theoretic signal processing
Some Equivalences between Kernel Methods and Information Theoretic Methods
Journal of VLSI Signal Processing Systems
Adaptive blind multiuser equalizer based on pdf matching
ICT'09 Proceedings of the 16th international conference on Telecommunications
Low complexity blind equalization based on parzen window method
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Blind adaptive equalizer for broadband MIMO time reversal STBC based on PDF fitting
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Estimating the information potential with the fast gauss transform
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
| Hi-index | 35.68 |
This work presents a new blind equalization approach that aims to force the probability density function (pdf) at the equalizer output to match the known constellation pdf. Quadratic distance between pdf's is used as the cost function to be minimized. The proposed method relies on the Parzen window method to estimate the data pdf and is implemented by a stochastic gradient descent algorithm. The kernel size of the Parzen estimator allows a dual mode switch or a soft switch between blind and decision-directed equalization. The proposed method converges faster than the constant modulus algorithm (CMA) working at the symbol rate, with a similar computational burden, and reduces the residual error of the CMA in multilevel modulations at the same time. A comparison with the most common blind techniques is presented.