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I/Q Imbalance Compensation Algorithm based on Neural Networks

Kirei B. S., Topa M., Neag M., Onet R. C.

Journal of Automation Mobile Robotics and Intelligent Systems

2009

Vol. 3, No. 2

66-71

This paper proposed an I/Q imbalance compensation algorithm based on neural networks, suitable for low-IF receivers. First, the low-IF receiver architecture and the phenomena of I/Q imbalance (also referred as image interference) are described. The standard solution - using a complex LMS adaptive filter, which separates the desired, and image signals - is limited in that the recovered signal remains affected by the I/Q imbalance; the filter proposed here corrects this drawback. The functionality, convergence and stability of the neural network based filter are demonstrated through extensive computer simulations. A sizing example is also given - deduction of the number of sample necessary in order to achieve a -60 dB image rejection - along with the time domain behaviour of the resulting neural network.