A general neuro-space mapping technique for microwave device modeling

Lin Zhu,Lei Pan,Deliang Liu,Haifeng Wu,Jian Zhao,Zhuo Li,Wenyuan Liu

doi:10.1186/s13638-018-1034-4

Abstract

Accurate modeling of nonlinear microwave devices is critical for reliable design of microwave circuit and system. In this paper, a more general neuro-space mapping (Neuro-SM) method is proposed to fulfill the needs of the increased modeling complexity. The proposed technique retains the capability of the existing dynamic Neuro-SM in modifying the dynamic voltage relationship between the coarse model and the desired model. The proposed Neuro-SM also considers dynamic current mapping besides voltage mappings. In this way, the proposed Neuro-SM generalizes the previously published Neuro-SM methods and has the potential to produce a more accurate model of microwave devices with more dynamics and nonlinearity. A new formulation and new sensitivity analysis technique are derived to train the general Neuro-SM with dc, small-, and large-signal data. A new gradient-based training algorithm is also proposed to speed up the training. The validity and efficiency of the general Neuro-SM method are demonstrated through a real 2 × 50 μm GaAs pseudomorphic high-electron mobility transistor (pHEMT) modeling example. The proposed general Neuro-SM model can be implemented into circuit simulators conveniently.

Highlights

Microwave transistors are key components in the generation wireless communication systems [1–4], such as cognitive multiple-input multiple-output (MIMO) systems [5–7], and cognitive relay network [8, 9]
We propose a more generalized Neuro-SM approach including static mapping and dynamic mapping, and considering both voltage mapping and current mapping for the first time
We obtain further improvement in model accuracy using general Neuro-SM technique because additional and useful degrees of freedom provided by the new dynamic current mappings at the gate and the drain in the general model

Summary

Introduction

Microwave transistors are key components in the generation wireless communication systems [1–4], such as cognitive multiple-input multiple-output (MIMO) systems [5–7], and cognitive relay network [8, 9]. With the increasing complexity of communication circuit and system structure, designers rely more heavily on computer-aided design (CAD) software to achieve efficient design. Microwave device models are essential to CAD software. The accuracy of these models can even decide whether the communication circuit and system design is successful or not. Due to rapid technology development in semiconductor industry, new microwave devices constantly arrive. Models suitable for previous devices may not fit new devices well. There is an ongoing need for new accurate models

Results

Discussion

Conclusion