AUTOMATED DESIGN OF MICROWAVE DISCRETE TUNING DIFFERENTIAL CAPACITANCE CIRCUITS IN Si-INTEGRATED TECHNOLOGIES Lu´ıs Mendes, E. J. Solteiro Pires, João C. Vaz, Maria J. Rosa´rio, P. B. de Moura Oliveira, and J. A. Tenreiro Machado ABSTRACT: A genetic algorithm used to design radio-frequency binary-weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. The algorithm provides a set of circuits all having the same maximum performance. This article also describes the design, implementation, and measurements results of a 0.25 lm BiCMOS 3-bit RFDSCA. The experimental results show that the circuit presents the expected performance up to 40 GHz. The similarity between the evolutionary solutions, circuit simulations, and measured results indicates that the genetic synthesis method is a very useful tool for designing optimum performance RFDSCAs. Key words: automated circuit synthesis; genetic algorithms; RF integrated circuits; RF switched capacitor arrays; RF tuned circuits 1. INTRODUCTION The radio-frequency switched capacitor arrays (RFSCAs) have a great potential for use in reconfigurable or adaptive radio-fre- quency (RF) circuits for actual and future wireless transceivers, because they allow a large capacitance tuning range with small tuning steps, when maintaining its quality factor at acceptable values. Moreover, these circuits have no power consumption, which is an important aspect when the transceivers are powered by a battery. At present, RFSCAs can be found in multistandard low-phase-noise ultra-wide-band voltage controlled oscillators [1], in fast-settling time frequency synthesizers [2], in process dispersion compensation techniques [3] and in adaptive imped- ance matching circuits [4]. Optimization and search tools, such as, the genetic algo- rithms (GAs) [5], have been progressively used to automate the design of RF integrated circuits [6–8]. An algorithm to design optimum performance radio-frequency and microwave binary- weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. This new approach, based on e- concept [9] and maximin sorting scheme [10], provides a set of solutions well distributed along an optimal front. Each GA solution that corresponds to a distinct implementation of the desired RFDSCA meets the initial design specifications and has the same maximum performance as the others. This method has bet- ter performance than the one already reported in the scientific