Adaptive antenna applications by brain emotional learning based on intelligent controller

This study presents a uniform linear array (ULA) adaptive antenna which uses a theoretical analysis of an on-line autonomous intelligent adaptive tracking controller based on the emotional learning model in mammalian brains. This optimisation approach, called the brain emotional learning based on intelligent controller (BELBIC), demonstrates superior performance in estimating the arrival direction of the incoming signals and performing adaptive beamforming, which is aimed at the receiving end. The most important advantages of this algorithm are its robustness in adaptation and on-line learning ability, which make it suitable for dynamic and real-time applications. In order to investigate the performance of adaptive antenna technology applied in mobile terminals, an appropriate channel model considering the effects of wireless channels is presented. Performance of the BELBIC algorithm is compared with Capon and least mean square (LMS) schemes considering a channel model from the static and dynamic points of view. Simulation results reveal superior performance of the BELBIC approach in almost all the cases. Moreover, the proposed approach demonstrates higher precision and lower computational time in comparison to other classical techniques.