Authors: Y. Li and S-M Yu
Affilation: National Chaio Tung University, Taiwan
Pages: 181 - 184
Keywords: simulation-based optimization, hybrid optimization technique, circuit design automation, low noise amplifier, numerical method, evolutionary algorithm
In this paper we propose an intelligent simulation-based optimization technique for designing low noise amplifier (LNA) integrated circuits (ICs). Based on a genetic algorithm (GA), the Levenberg–Marquardt (LM) method, and a circuit simulator, the hybrid optimization methodology is developed for automatic design of LNA ICs. For a given LNA circuit, the hybrid optimization methodology simultaneously considers the electrical specification such as S11, S12, S21, S22, K factor, the noise figure, and the input third-order intercept point in the optimization process. First of all, the necessary parameters of the LNA IC for circuit simulation are loaded. A circuit simulator will then be performed for the circuit simulation and specification evaluation. Once the specification meets the aforementioned seven constraints, we output the optimized parameters. Otherwise, we activate the GA for the global optimization; in the meanwhile, the LM method searches the local optima according to the results of the GA. We then call circuit simulator to compute and evaluate newer results until the specification is matched. Along with the proposed methodology, a corresponding prototype of the electronic computer-aided design is successfully implemented and used for optimal design of LNA ICs. Organizing some testing experiments, more than fifteen parameters of the LNA IC including device sizes, capacitance, inductance, resistance, and biasing conditions are optimized with respect to the aforementioned seven constraints. The design of LNA circuit is with 0.18 um metal-oxide-silicon filed effect transistors. Benchmark results also computationally confirm the robustness and efficiency of the proposed intelligent simulation-based optimization technique. This approach in general can be applied to optimal design of other analog and radio frequency circuits. We believe that this hybrid optimization methodology will benefit advanced designs of wireless communication system-on-a-chip.