Adaptive control network for an intelligent RF front-end amplifier

This paper describes a novel approach for adjusting the matching networks of an RF front-end amplifier to maintain system performance using an adaptive control network (ACN). To maintain system performance, the matching networks of the amplifier are dynamically adjusted as a function of frequency. The ACN consists of a back-propagation neural network that was trained for gain as a function of frequency. As a result, the ACN adapts the system performance by controlling a tunable impedance transmission line (TITL) as a function of frequency. In addition, the ACN is able to re-configure the system for different system requirements without changing the matching network topologies. Simulation results demonstrate the ability to control the TITL matching network, adapt the performance across the frequency band, and reconfigure for different specifications. The first-generation hardware prototype was demonstrated in support of the Intelligent RF Front-End Project awarded to Northrop Grumman Space Technology by DARPA.