Reconfigurable antennas in cognitive radio that can think for themselves?

Abstract

This paper discusses the use of reconfigurable antennas in cognitive radio. Most of the emphasis on cognitive radio so far has been in the area of spectral estimation and signal classification. In this paper we show that once a cognitive device manages to learn the RF environment (cognition part), from past observations and decisions using machine learning techniques, we can use the collected data to train reconfigurable antennas to adapt to any change in the RF environment.