Application of Diversity Controlled Genetic Algorithms to the Design and Optimization of OTA-C IF Filters

IF filters find diverse practical applications in modern communication systems. In the current analog IC fabrication technologies, IF filters are usually implemented as OTA-C filters. The design of OTA-C IF filters can be achieved by employing either the existing gradient-based optimization techniques or the conventional genetic algorithms (GAs). However, the latter approach may result in relatively slower convergence speeds. This paper presents a novel application of diversity controlled (DC) GAs to the rapid optimization of OTA-C IF filters. In this application, the gains associated with the constituent OTA transconductances are used as optimization parameters. DCGA is well known to exhibit an order of magnitude improvement in the convergence speed as compared to conventional GAs. The proposed approach is illustrated through its application to the optimization of an OTA-C IF filter consisting of 39 OTAs for operation around a center frequency of 455 kHz.