Neural Networks for RF and Microwave Design

Chapter 1: Introduction and Overview

1.1 RF and Microwave Design

The rapid development of commercial markets for wireless communication products over the past decade has led to an explosion of interest in improved circuit design approaches in the radio frequencies (RF) and microwave areas. This new market for high frequency expertise is replacing the older discipline of Department of Defense (DOD)-oriented RF/microwave electronics with its emphasis on performance at any price after the defense build-down in the late 1980s and early 1990s. Modern wireless communication systems require a thorough understanding of RF and microwave circuit design techniques in addition to a background in digital communication techniques and familiarity with existing and emerging wireless communication protocol standards. The wireless industry's emphases on time-to-market and low cost, resulting from first-pass-design, are placing enhanced demands on computer-aided design (CAD) tools for RF/microwave circuits, antennas, and systems.

RF and microwave circuit design has progressed considerably and has achieved a certain level of maturity in recent years. Electromagnetic (EM) simulation techniques for high frequency structures developed over the past decade have helped to bring the CAD for hybrid RF/microwave circuits and monolithic RF/microwave integrated circuits (MMIC) to its current state of the art. The key contribution of EM simulation techniques to RF/microwave CAD has been in the domain of accurate models for microwave components [1]. As a result, the microstripline-based RF/microwave-circuit design has been brought to almost a first-pass success level. Modeling still remains a major bottleneck for CAD of certain classes of RF/microwave circuits (such as coplanar waveguide (CPW) circuits, multiple-layered circuits;

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