An Image Rejection Mixer with AI-Based Improved Performance for WCDMA Applications(<Special Section>Analog Circuit and Device Technologies)

概要

論文の詳細を見る
This paper proposes the combination of adjustable architecture and parameter optimization software, employing a method based on artificial intelligence (AI), to realize an image rejection mixer (IRM) that can enhance its image rejection ratio within a short period of time. The main components of the IRM are 6 Gilbert-cell multipliers. The tail current of each multiplier is adjusted by the optimization software, and the gain and phase characteristics are optimized. This adjustment is conventionally extremely difficult because the 6 tail currents to be adjusted simultaneously are mutually interdependent. In order to execute this adjustment efficiently, we employed a Genetic Algorithm (GA) that is a robust search algorithm that can find optimal parameter settings in a short time. We have successfully developed an IRM chip that has a performance of 71dB and is suitable for single-chip integration with WCDMA applications.
社団法人電子情報通信学会の論文
2006-06-01