Mathematical Modelling of Low-Frequency BiCMOS Near-Infrared Detector

Abstract

Bipolar complementary metal-oxide semiconductor (BiCMOS) technology is the platform of choice for near-Infrared (IR) detector research because of low power consumption, increased operating speed and a high fill-factor. The drawback is poor noise performance which can be attributed to the readout circuitry of the detector. Conventional near-IR detector design is an iterative process. While recognising the value of this approach, rapid prototyping can be achieved by using mathematical modelling that would ensure design repeatability.

Heterojunction bipolar transistor (HBT) and metal-oxide field-effect transistors (MOSFET) models for SiGe process technologies have been documented extensively. However, mathematical modelling of BiCMOS near-IR detectors has not been implemented in a complete working system before. This proposed model can be used to determine the output voltage as well as the noise performance of near-IR detectors. The focus of this research is to determine how process independent parameters and detector performance can be mathematically modelled. Secondly, and associated to this, is determining how the model can be extended to accommodate multiple feature sizes including short-channel MOSFETs.

An implementation of this model on the three-transistor pixel structure, using reverse-biased diode-connected HBTs as pixels, was done as part of the experimental verification process of this research. The implementation was done in a 2 × 2 gated array detector configuration. The validity of the proposed modelling procedure was verified through comparison of simulations and measured results. The simulations were done in an iterative fashion to show how a deviation in one process independent parameter affects the noise performance, while the other process independent parameters are kept constant. The detector design with optimal noise performance can be achieved in this manner, thereby minimising design time and developing optimised detectors without the need for extensive prototyping.

The main contribution of this research is that a designer can use this mathematical model to tune a detector to achieve desired performance. By changing the temperature, biasing voltage and biasing current and choosing the aspect ratio, noise performance changes. An iterative process in the mathematical model development can achieve optimised parameters for noise performance. Two approaches, namely DC analysis and y-parameter representation, were used to develop the mathematical model. Feedback was taken into account using the y-parameter representation.

The measured results show that the output voltage behaviour follows the mathematical model developed. The output voltage behaviour also shows that the mathematical model parameters can determine noise performance. As an extension to this work, the same modelling process can be used to develop mathematical models for other detecting structures such as the four-transistor pixel structure.