編集後記

Simulation is becoming more and more important around the world in multiple applications. A simulation model is a good base for describing the reaction of a system and its behavior, with one unexpected example coming from a PC game. Many of you might know World of Warcraft, a role-playing game from Blizzard Entertainment. In 2005, a glitch caused a virtual pandemic where characters were killed off by a very contagious spell called “corrupted blood.” This became known as the corrupted blood incident, where upon contact with one another, characters could be infected and die. The players’ reaction to this virtual pandemic was remarkable and very close to what we see nowadays. Some players stopped playing. Some were more careful when meeting other characters, while others tried to achieve immunity upfront by forcing the infection. A whole forum was founded where gamers shared tips and discussed how to prevent the infection or which character strengths were required to survive. False news and rumors also spread. Two years later in 2007, this gamer behavior was identified as a model for epidemic research to help study human reactions to real-world outbreaks like SARS and avian influenza. More recently, players were interviewed about the differences in their behaviors as gamers, compared to their real-life behavior throughout the COVID-19 pandemic.

And now, back to the Analog Dialogue articles.

Much of the promotional material presented on digital predistortion (DPD) performance is based on static quantitative data. Typically, a DPD spectrum is shown and ACLR figures are quoted. Such an approach, while addressing the fundamental needs of a design, fails to capture many of the challenges, risks, and performance trade-offs that occur in real-world deployments. The rapid transition to 5G introduces a plethora of new challenges and scenarios. Algorithm developers and equipment vendors need to pay particular attention to “what lies beneath.” You can read through the details in “How to Make a Digital Predistortion Solution Practical and Relevant.”

The article “Understanding and Using the No-OS and Platform Drivers” describes the use of no-OS (no operating system) drivers and platform drivers for building an application firmware with ADI’s precision ADCs and DACs, which offer a high level of performance in speed, power, size, and resolution. Rapidly advancing technologies need software support (firmware drivers and example code) to simplify the development process. Embedded firmware examples based on no-OS drivers are provided to support precision converters. No-OS drivers are responsible for device configuration, data capture from a converter, system calibration, etc., while firmware examples based on the no-OS drivers facilitate transfer of data to a host PC for display, storage, and further processing.

Optics plays a key role in time of flight (ToF) depth sensing cameras, and the optical design dictates the complexity and feasibility of the final system and its performance. 3D ToF cameras have certain distinct characteristics that drive special optics requirements. “ToF System Design–Part 2: Optical Design for Time of Flight Depth Sensing Cameras” presents the depth sensing optical system architecture, which consists of the imaging optics sub-assembly, the ToF sensor on the receiver, and the illumination module on the transmitter. This article discusses how to optimize each sub-module to improve the sensor and system performance.

Demand for smaller and smaller electronic devices with an increasing number of features, combined with reduced current consumption, calls for size constraints on components including multilayer ceramic capacitors (MLCCs). As a result, the effect of the voltage dependence (DC bias) is also being pushed into focus. Miniaturization of ceramic capacitors requires higher capacitance values in an increasingly smaller space. Materials with high permittivities (ε) and increasingly thin dielectric insulating layers are being implemented, making it now possible to produce high quality ceramic layers on an industrial scale. In this article, we describe “How to Use LTspice® Simulations to Account for the Effect of Voltage Dependence” (or DC bias) caused by the use of ceramic capacitors with even smaller case sizes.

A transresistance amplifier outputs a voltage proportional to its input current. The transresistance amplifier is often referred to as a transimpedance amplifier, especially by semiconductor manufacturers. An inverting transresistance amplifier can be configured from a conventional operational amplifier and a single resistor. In the “ADALM2000 Activity: The Transresistance Amplifier Input Stage” we’ll investigate an alternate differential input structure that produces an inherently low input impedance (a current input) as opposed to the relatively high input impedance of the voltage differential pair that was investigated in “ADALM2000 Activity: BJT Differential Pair” and “ADALM2000 Activity: MOS Differential Pair.”

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