Blind adaptive equalizer for broadband MIMO time reversal STBC based on PDF fitting

Authors:
Adel Daas;Samir Bendoukha;Stephan Weiss
Affiliations:
Centre for Excellence in Signal & Image Processing, Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, Scotland, UK;Centre for Excellence in Signal & Image Processing, Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, Scotland, UK;Centre for Excellence in Signal & Image Processing, Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, Scotland, UK
Venue:
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Year:
2009

Citing 8
Cited 1

Adaptive signal processing

Adaptive signal processing
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas

Wireless Personal Communications: An International Journal
Adaptive blind multiuser equalizer based on pdf matching

ICT'09 Proceedings of the 16th international conference on Telecommunications
Stochastic blind equalization based on PDF fitting using Parzen estimator

IEEE Transactions on Signal Processing
Overview and comparison of equalization schemes for space-time-coded signals with application to EDGE

IEEE Transactions on Signal Processing
Statistical reference criteria for adaptive signal processing indigital communications

IEEE Transactions on Signal Processing
Unsupervised receiver processing techniques for linear space-time equalization of wideband multiple input / multiple output channels

IEEE Transactions on Signal Processing
A simple transmit diversity technique for wireless communications

IEEE Journal on Selected Areas in Communications

Exploitation of the redundancy induced by Alamouti coding for MIMO signals' blind demodulation

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This work presents a new blind multiuser equalization strategy for Time Reversal Space Time Block Coding (TRSTBC) signals transmitted over a dispersive MIMO channel. The adaptation is based on forcing the probability density function (PDF) of the equalizer output to match the desired PDF of corresponding source symbols. In the proposed approach, the PDFs are estimated by means of the Parzen window method using Gaussian Kernels. The cost function combines this PDF fitting with an orthogonality criterion derived from the TR-STBC structure. The performance is demonstrated in a number of simulations and benchmarked against other blind schemes. The proposed algorithm has a moderate computational complexity and can perform with higher adaptation rate.