Pareto Optimal Characterization of a Microwave Transistor

Abstract

Herein, noise, gain and port mismatchings of a microwave small-signal transistor are expressed as all the set of acceptable Pareto optimal solutions and trade-off relations within the device operation (V DS , I DS , f) domain without any need of expert knowledge of microwave device. In this multi-objective optimization problem, non-dominated sorting genetic algorithm (NSGA)-III is applied to an ultra-low noise amplifier (LNA) transistor NE3511S02 (HJ-FET) where the noise F req ≥ F min and output mismatching V outreq ≥ 1 are preferred as the reference points, while the input mismatching V inopt ≥ 1 and gain G Tmax are optimized with respect to source Z S and load Z L within the unconditionally stable working area. Thus, diverse set of the Pareto optimal (the required noise F req , the optimum input V inopt , the required output V outreq , the maximum transducer gain G Tmax) quadruples are resulted from a fast search of the solution space. Furthermore, the optimum bias condition (V DS , I DS) and sensitivities of the terminations to fabrication tolerances are also determined using the cost analysis in the operation domain for the required P max , I DSmax and performance quadruple. Finally, this work is expected to enable a designer to provide the feasible design target space (FDTS) consisting of all trade-off relations among all the transistor's performance ingredients to be used in the challenging LNA designs. INDEX TERMS Non-dominated sorting genetic algorithm, Pareto optimal solutions, optimization, impedance mismatching, transducer gain, noise figure.

Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management

“…Numerically rigorous design closure requires a definition of the quality metric, which, in practice, needs to accommodate two or more objectives, such as the operating bandwidth, power split ratio, port isolation, or the phase relationships between the input and output signals. This works addresses singleobjective optimization (as opposed to genuine multi-objective design, e.g., [27], [52]). Handling of several figures of merit is tackled by the assignment of a primary objective and controlling the remaining ones through appropriately defined constraints.…”

Novel neural network optimization approach for modeling scattering and noise parameters of microwave transistor

“…where, the error value of the jth neuron in the output layer is expressed by e j . The LMSE value of the jth neuron is given in Equation (6).…”

“…Therefore, transistor modeling studies continue to stay current as an active research field. [1][2][3][4][5][6][7] Scattering (S) parameters are used for linear behavioral modeling of two-port components. 8 The linear behaviors of transistors, which are some of the major components of active microwave circuit design, are determined by S parameters.…”

“…For power amplifiers, low-noise amplifiers and other active microwave circuits including transistors, it is highly important to model the S and N parameters through all operational ranges of the transistors. 6,12 Many studies in the literature have used the Artificial Neural Network (ANN) approach in modeling S and N parameters which provides information on the linear behavior or microwave transistors. 5,7,10,[13][14][15][16][17][18][19] In the literature, the ANN approach has not only been used in linear behavior modeling for microwave transistors.…”

Pareto Effect of LMI for Ship Propulsion

“…Interesting research is presented in [9] where a multi-criteria optimization problem is formulated for a low-noise amplifier (LNA) of an NE3511S02 (H J − FET) transistor. For this purpose, the authors use the multi-criteria evolutionary algorithm NSGA-III (Nondominated Sorting Genetic Algorithm III) to obtain Pareto characteristics of the optimal solutions for transistor performance.…”