Better Millimeter-wave Measurements with New Preselection Technology

Blog Post created by benz on Aug 31, 2017

  When gems turn to coal, engineers get creative

Despite their flaws, I have described YIG preselector filters as the gems in microwave signal analyzers. These preselectors solve a problem created when mixers are used to downconvert signals for analysis: The mixers produce multiple outputs from a single input frequency, including the main high-side and low-side ones, and many smaller ones. Unless removed somehow, these outputs can cause false signals to appear in the analyzer display, especially in wide frequency spans.

The preselection process removes false responses using a bandpass preselector filter that tracks the appropriate mixing mode in the analyzer, removing signals before they get measured in the final IF stage. It’s a tried-and-true approach, and a combination of automatic alignment and characterization keeps the preselectors centered while accounting for their insertion loss.

Unfortunately, these little gems rapidly lose their luster as frequencies climb into the millimeter range, becoming increasingly impractical above about 50 GHz. That’s a more serious limitation now, as designers dive into the challenges of the bands at 60 GHz and need accurate measurements of power, spurious, and harmonics. The wide bandwidth and time-varying or noise-like behavior of the signals in question only compound the challenge.

The goal, as always, is accurate and unambiguous results over wide frequency ranges with a single connection. The new N9041B UXA X-Series signal analyzer, 110 GHz, uses a conventional YIG preselector below 50 GHz, but employs two other—software-centric—methods at higher frequencies. Both techniques identify false signals and remove them from measurements, but avoid the insertion loss of the preselector filter. This loss would otherwise directly impact the sensitivity of the analyzer, a critical factor at millimeter frequencies where power is precious.

Wideband spectrum to 100 GHz showing displayed average noise level (DANL) of N9041B UXA signal analyzer. Marker shows DANL better than -147 dBm/Hz at 85 GHz

Maintaining a low noise floor is increasingly difficult—and increasingly important—at millimeter frequencies. This wideband measurement from an N9041B signal analyzer indicates an average noise floor of better than 147 dBm/Hz at 85 GHz.

One straightforward technique involves a combination of image shifting and image suppression. The analyzer makes two sweeps of the same span, with the local oscillator (LO) frequency shifted so that each of the two main mixing modes—high-side and low-side—is used to convert the frequencies in question for measurement. The two measurements are then compared.

Because of the frequency symmetry of the results, real signals appear at the same frequency while false ones shift. In theory, it’s then a simple matter to display the minimum values of each measurement point, removing the false signals and leaving the real ones.

In practice, however, this shift-and-remove technique has limitations. It usually requires a subsequent measurement with a narrower span to accurately measure signal power. Additionally, the selection of the minimum value for display of each measured point distorts the amplitude values of the noise-like signals that are so common these days.

Fortunately, adding information to the measurement process and applying creative signal processing can counter these limitations, yielding accurate measurements of wideband and dynamic signals and avoiding the need for user to take additional steps. The added information comes in two forms:

The noise floor and alternate trace information is used to create a threshold that enables removal of images from measurement data without causing a negative power bias for noise-like signals.

Of course, the goal of all these operations is to provide accuracy and ease of use over a wide range of frequencies and signal types. Ideally, measurements from 50 to 110 GHz will be as direct and reliable as those at lower frequencies, enabling the engineering of the next generation of communications and imaging solutions.

That’s it for now. Look for more information about software preselection and its application to specific signals and measurements in posts to come.