In radar receivers, the low noise amplifier (LNA) must provide very low noise figure and high gain to successfully receive very low signals reflected off of illuminated targets. Obtaining low noise figure and high gain, unfortunately, is a well-known trade-off that has been carefully negotiated by design engineers for years. This paper presents a fundamental solution method for the source reflection coefficient providing the maximum available gain under a given noise figure constraint, and also for the lowest possible noise figure under a gain constraint. The design approach is based solely on the small-signal S-parameters and noise parameters of the device; no additional measurements or information are required. This method is demonstrated through examples. The results are expected to find application in design of LNAs and in real-time reconfigurable amplifiers for microwave communication and radar receivers.

In this paper, we propose a population-based evolutionary multiobjective optimization approach to design combinational circuits. Our results indicate that the proposed approach can significantly reduce the computational effort required by a genetic algorithm (GA) to design circuits at a gate level while generating equivalent or even better solutions (i.e., circuits with a lower number of gates) than a human designer or even other GAs. Several examples taken from the literature are used to evaluate the performance of the proposed approach.