Jialin Cai

Padé-Approximation-Based Behavioral Modeling

A new, nonlinear, frequency-domain behavioral model, based on Pade approximation theory, is presented in this paper. The new Pade model is similar in concept to the X-parameter method, but it uses a rational function instead of the X-parameter models polynomial expression. The basic theory of the proposed Pade model and the model extraction methodology are provided. The proposed Pade approach increases the available modeling space beyond that available to the X-parameter method, and the performance of a selection of this family of models under various loading conditions is described in this paper. Along with the examples displaying the ability of the new model to predict fundamental frequency behavior, a second-harmonic example is also provided, with simulation results presented in both the frequency domain and the time domain. Based on the simulation studies and experimentally measured results, the new Pade model shows good accuracy and a high level of stability. All of these characteristics show that the proposed Pade model has high potential in RF design.

Nonlinear Behavioral Modeling Dependent on Load Reflection Coefficient Magnitude

A new frequency-domain nonlinear behavioral modeling technique is presented and validated in this paper. This technique extends existing Padé and poly-harmonic distortion models by including the load reflection magnitude, |ΓL|, as a parameter. Although a rigorous approach requires a full 2-D load-pull model to cover the entire Smith chart, simulation and experimental evidence have shown that such a 1-D model-that retains only amplitude information of the load reflection coefficient-can give accuracy close to that of a full 2-D load-pull model. Consequently, neglecting the phase constitutes an approximation that provides large benefits without appearing to lead to a severe compromise in accuracy. Furthermore, compared with traditional load-independent models, the new |ΓL|-dependent models provide a major improvement in model accuracy. After a discussion of the model extraction methodology, examples are provided comparing traditional load-pull X-parameter models with the model presented in this paper. The new model not only provides consistently good accuracy, but also has a much smaller model file size. Along with the examples that display the ability of the new modeling technique to predict fundamental frequency behavioral, a second harmonic example is also provided. The modeling approach is also validated using measurements results.

Reduced-Complexity Polynomial Based Nonlinear Behavioral Modeling

A new, nonlinear, frequency-domain behavioral model, based on a reduced two-dimensional polynomial equation, is presented in this letter. The Reduced Polynomial (RP) model is similar in concept to the Poly-Harmonic Distortion (PHD) method but has advantages in terms of needing a smaller number of model parameters for comparable accuracy. The basic theory of the proposed RP model and the model extraction methodology are provided. In addition to the first-order RP model, a quadratic RP (QRP) model is also presented. Based on simulation studies and experimentally measured results, the new model shows high accuracy and good stability.

An improved quadratic poly-harmonic distortion behavioral model

In this paper, the basic quadratic form of the poly-harmonic distortion model is first presented and this is then extended to provide a new, modified quadratic poly-harmonic distortion model. Comparisons between the X-parameter model, the basic quadratic poly-harmonic distortion model, and the modified version are provided. Both simulation and experimental test results show that the new modified model provides significant improvements in accuracy, not only for the fundamental frequency, but also for DC. Work on the optimization of the model is also presented, providing further improvements in both the model extraction time and the file size.

Padé behavioral model dependent on load reflection magnitude

A new Padé behavioral model dependent on the magnitude of the load reflection coefficient is presented. With this model, we need only sweep the magnitude of reflection coefficient, |ΓL|, to cover the whole Smith chart, instead of sweeping both phase and magnitude when performing model extraction. This greatly simplifies the model extraction process from a 2D-load-pull sweep to a 1D sweep. Both simulation and measured results are given, demonstrating good accuracy with the proposed model.

Padé-approximation-based behavioral modeling

A new, nonlinear, frequency-domain behavioral model, based on Padé approximation theory, is presented in this paper. The new Padé model is similar in concept to the X-parameter method, but it uses a rational function instead of the X-parameter models polynomial expression. The basic theory of the proposed Padé model and the model extraction methodology are provided. The proposed Padé approach increases the available modeling space beyond that available to the X-parameter method, and the performance of a selection of this family of models under various loading conditions is described in this paper. Along with the examples displaying the ability of the new model to predict fundamental frequency behavior, a second-harmonic example is also provided, with simulation results presented in both the frequency domain and the time domain. Based on the simulation studies and experimentally measured results, the new Padé model shows good accuracy and a high level of stability. All of these characteristics show that the proposed Padé model has high potential in RF design.

A new nonlinear behavioral modeling technique for RF power transistors based on Bayesian inference

A novel nonlinear behavioral modeling technique, for transistor behavioral modeling, is presented in this paper. Compared with existing modeling techniques, the new approach is based on a fundamentally different theory, Bayesian inference (one of the core methods of machine learning). The new technique not only good at handling multidimensional modeling problem, it could also greatly alleviated the notorious overfitting issue through corresponded model extraction method. Both simulation and experimental test examples for a 10W Cree GaN transistor are provided. The new model provides accurate prediction throughout the Smith chart at different input power levels.

|Γ; L |-dependent polynomial behavioral model for RF power transistors

A new, load reflection magnitude (|ΓL|)-dependent, Reduced-complexity Polynomial (RP) behavioral model is introduced in this paper. The presented model provides good accuracy while only requiring a small number of parameters. The potential of this model to help design a nonlinear circuit is demonstrated through the design of a broadband power amplifier (PA) with drain efficiency between 65-79% from 1.5 GHz to 2.5 GHz.

Application of a load-independent Padé model in Power Amplifier design

The ability of a load-independent Padé nonlinear behavioural model to help design the output matching network of a Power Amplifier (PA) is shown for the first time. 50Ω Padé models are extracted at the frequencies of interest, and then the extracted models are used to perform load-pull simulations. The purpose is to find the Smith chart regions for maximum power delivery and drain efficiency in order to obtain the best fundamental load points across the bandwidth. After the load trajectory has been obtained, the Simplified Real Frequency Technique (SRFT) can be used to calculate the load output matching circuit. Measured results are compared with the behavioural simulation results for a PA with output matching only. The measured drain efficiency for the realized amplifier is between 60-70% between 1.6 GHz and 2.4 GHz, providing a 40% bandwidth with a centre frequency of 2.0 GHz. The input matching network of this PA is also realised, and measurement results are given.

Compact behavioral description for generalized loads using a modified DC X-parameter model

A modified DC X-parameter model is presented. The model gives much better accuracy than a basic 50 Ω DC X-model. Compared with a full load-pull DC X-model, the presented model not only greatly decreases the models file-size, but also provides comparably good accuracy. The optimization of the model is also presented, and based on this method both the model extraction time and the file-size are further improved.