Selecting the Best Signal Amplitude in the Smart Antenna Output by Using Neural Networks

The concept of frequency reuse has been successfully implemented in modern cellular communications systems in order to increase the system capacity. Further improvement of capacity can be achieved by employing adaptive arrays at the base station. In order to track the desired users, direction finding algorithms are used to locate the positions of mobile users as they move within or between cells. Recently, neural networks-based direction finding algorithms have been supposed for source direction finding. The performance of neural network is evaluated by comparing their prediction, standard deviation and Mean Square Error (MSE) between their predicted and measurement values. The research depends on this context. So, it has been compared the antenna array output signals according to their amplitude, then selected the signal that has the best amplitude in the system’s final output.