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Application of artificial neural network models to linear and nonlinear RF circuit modeling

Typical RF and wireless circuits comprise a large number of linear and nonlinear components. The complexity of the RF portion of a wireless system continues to increase in order to support multiple standards, multiple frequency bands, the need for higher bandwidth, and stringent adjacent channel specifications. The time required to carry out a virtual prototyping of such complex circuits and their trade‐off analysis with the baseband circuitry can be unacceptably long, because both the circuit simulation and optimization procedures can be very time consuming. Typically, one divides the task into those of designing the nonlinear elements or subcircuits that can be accurately analyzed by using RF simulators, and uses circuit level analysis for simulating the circuits at module level. In this article, we will review some approaches to modeling both the linear RF elements as well as nonlinear subcircuits (amplifiers, mixers, VCOs), and will emphasize on the application of the artificial neural networks (ANNs). Furthermore, we will demonstrate the use of the ANN to the design of RF circuits and illustrate their application to wireless types of problems of practical interest. © 2001 John Wiley & Sons, Inc. Int J RF and Microwave CAE 11: 231–247, 2001.