A blind equalization algorithm for biological signals transmission

Abstract

Direct transmission of biological signals such as electrocardiogram (ECG) and electroencephalogram (EEG) through mobile network provides practically unlimited movement of the patients and unlimited coverage area. However, transmission of such signals over a bandlimited channel or through a multipath propagation is subject to inter symbol interference (ISI), whereby adjacent symbols on the output of the channel smear and overlap each other causing degradation of error performance. Mitigation of such kind of distortion can be achieved through equalization filter. Recently an adaptive blind channel equalization using sinusoidally-distributed dithered signed-error constant modulus algorithm (DSE-CMA) has been proposed. In this paper we investigate the performance and the feasibility of this scheme for wireless ECG and EEG transmission. Also, this paper discusses the importance of adaptive blind equalizer for biological signals transmission over existing wireless networks such as Global System for Mobile Communications (GSM) and the Enhanced Data rates for GSM Evolution (EDGE). The geometrical-based hyperbolically distributed scatterers (GBHDS) channel model for macrocell environments was simulated with angular spreads (AS) taken from measurement data. Simulation results show that the low complexity of implementation and the fast convergence rate are the major advantages of deploying this scheme for telemedicine applications. It is also shown that the equalizer output signal is highly correlated with the original transmitted signal in time and joint time-frequency domains.