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Measurement Techniques and Strategies for the Interference of Things

Blog Post created by benz on Aug 20, 2017

  Bring your best engineering game, and use all the measurement tools available

The term Internet of Things (IoT) has been around a few years, and sometimes it feels over-hyped. When some folks start musing breathlessly about a near future in which virtually everything will be connected, it feels like they’ve taken the concept a little too far.

Consider cybersecurity problems with Internet-connected devices, from cameras to doorbells to toys. These glitches highlight just one of the ways we aren’t quite ready for universal connectivity. In addition, the questionable utility and uneven functionality of some devices have left many potential users with feelings that range from guardedly cautious to overtly skeptical.

Long before we approach universal connectivity, we will have to contend with another factor that often seems universal: RF interference. The combination of complex radio systems, dense environments, and high user expectations guarantees that interference will be a persistent issue.

The Interference of Things is a newer term that may not be hyped enough. While we don’t need to get overly dramatic about interference problems, much of the growth of wireless applications will depend on solving or avoiding these problems.

One application likely to lead the way is IoT in medical or healthcare settings. A recent blog post by Keysight’s Chris Kelly was my first exposure to the term interference of things, and it’s a good example of the potential seriousness of RF interference. Chris suggests a forward-looking approach, focusing on early debugging and a thoughtful combination of design, simulation, emulation, test and analysis.

He is certainly right about the benefits of anticipating problems, but sometimes you’re plunged into an existing situation like the example he describes: nearly a thousand Wi-Fi devices and expectations that problems will be solved quickly.

As an RF engineer, you’ll draw on your tools, techniques, experience, creativity and insight. While the lab environment and its benchtop equipment provide powerful advantages, the faster path to success may mean going to where the thorny problems are. In her recent post describing an elusive example of RF interference, Jennifer Stark explained how a portable signal analyzer and the reasoning power of a wireless engineer were key. The actual interference offender was a simple device and a simple signal, but it wasn’t going to be found in the lab.

Fortunately, portable signal analyzers are expanding their capabilities and frequency range at a rapid pace. Keysight’s FieldFox, for example, provides measurement and display capabilities that can help you find and troubleshoot RF interference problems away from the lab.

Two example displays from Keysight FieldFox handheld analyze, including channel scanner and real-time spectrum analysis

The automatic channel scanner (left) speeds measurement of spurious and intermodulation products, while optional real-time spectrum analysis (RTSA; right) can uncover short-duration events.

In a crowded RF environment, the dynamics of time-varying signals pose many challenges, and transient interactions can be hard to understand. Perhaps the most powerful analysis tool is the wideband, gap-free signal capture and playback post-processing that is available in VSA software for signal analyzers. Signal captures can be free-run, time-qualified, or triggered by matching an RTSA frequency mask.

With a complete, gap-free signal in memory—including pre-trigger data—you can perform any type of signal analysis in post-processing: adjust span and center frequencies, apply demodulation, and more. For time-dependent interactions, a spectrogram display can be enlightening.

Gap-free spectrogram (spectrum vs time) display from vector signal analyzer (VSA) of 2.4 GHz ISM band, including WLAN, cordless phone and Bluetooth signals

A spectrogram shows how a signal spectrum (each horizontal line) varies with time (vertical axis) and power (color). This gap-free spectrogram with very fine time resolution was generated by post-processing a signal captured in memory.

The analysis and troubleshooting power of this display comes from its ability to represent everything that happened across a range of frequencies over a known time interval. This clear, comprehensive view is powerful information to mix in with your own knowledge of the system, signal and environment.

 

One note: If you’re interested in the medical environment, or in using it as guide to other demanding situations, check out Brad Jolly’s webcast Smart Testing to Limit Your Risk Exposure in Wireless Medical Devices. He’ll explain what to do when life and health depend on reliable radio links.

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