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All Places > Keysight Blogs > Better Measurements: The RF Test Blog > Blog > 2017 > June

  Coherence can make a big difference

Sometimes The Fates of Measurement smile upon you, and sometimes they conspire against you. In many cases, however, it’s hard to tell which—if either—is happening.

More often, I think, they set little traps or tests for us. These are often subtle, but nonetheless important, especially when you’re trying to make the best measurements possible, close to the limits of your test equipment.

In this post I’m focusing on coherence as a factor in ACPR/ACLR measurements. These ratios are a fundamental measurement for RF engineering, quantifying the ability of transmitters to properly share the RF spectrum.

To make the best measurements, it’s essential to understand the analyzer’s contribution to ACP and keep it to a minimum. As we’ve discussed previously, the analyzer itself will contribute power to measurements, and this can be a significant addition when measuring anywhere near its noise or distortion floor.

We might expect this straightforward power contribution to also apply to ACPR measurements, where the signals appear to be a kind of band-limited noise that may slope with frequency. However, it’s important to remember that these are actually distortion measurements, and that the assumption of non-coherence between the signal and the analyzer is no longer a given.

Indeed, an intuitive look at the nonlinearity mechanisms in transmitters and analyzers suggests that coherence of some kind is to be expected. This moves us from power addition (a range of 0 dB to +3dB) to voltage addition and the larger apparent power differences this can cause.

Diagram of error in ACPR/ACLR measurements vs. analyzer mixer level/attenuation. Diagram specifically calls out the case where DUT and analyzer ACPR are same, and how this can cause large ACPR errors due to coherent signal addition or cancellation.

This diagram shows how analyzer mixer level affects ACPR measurement error when the analyzer and DUT distortion are coherent. The largest errors occur when the ACP of the DUT and analyzer are the same, indicated by the vertical dashed red line.

Interestingly, the widest potential error band occurs not where the analyzer ACP is largest but when it is the same as the DUT ACP. Consequently, adjusting the mixer level to minimize total measured ACP may lead you to a false minimum.

There are a number of challenges in optimizing an ACPR measurement:

  •  Noise power subtraction cannot be used due to analyzer/DUT coherence.
  •  Narrow RBWs are no help because they have an equal effect on the apparent power from the analyzer and DUT.
  • Low mixer levels (or higher input attenuation) minimize analyzer-generated distortion but increase measurement noise floor.
  • High mixer levels improve measurement noise floor but increase analyzer-generated distortion.

While the settings for lowest total measurement error are not exactly the same as for minimum analyzer-generated ACP, they are generally very close. In a future post I’ll discuss the differences, and ways to optimize accuracy, no matter what The Fates have in mind for you.

  A quick, intuitive look at what will make them challenging

Noise is fundamental in much of what RF engineers do, and it drives cost/performance tradeoffs in major ways. If you’ve read this blog much, you’ve probably noticed that noise is a frequent focus, and I’m almost always working to find ways to reduce it. You’ve also noticed that I lean toward an intuitive explanation of RF principles and phenomena whenever possible.

In the most recent post here, Nick Ben discussed four fundamentals of noise figure. It’s a useful complement to my previous look at the measurement and the two main ways to make it.

As engineers, we work to develop a keen sense of when we might be venturing into difficult terrain. This helps us anticipate challenging tasks in measurement and design, and it helps us choose the best equipment for the job. In this post I’ll summarize factors that might make noise figure measurements especially troublesome.

First, the most common challenge in noise figure measurements: ensuring that the noise floor of the measurement setup is low enough to separate it from the noise contributed by the DUT. These days, the most frequently used tool for noise figure measurements is a spectrum or signal analyzer, and many offer performance and features that provide an impressively low noise floor for noise figure measurements.

Measurement examples of noise floor for a broad frequency span on Keysight PXA signal analyzer. Lower traces include effect of internal and external preamplifiers.

Internal (middle trace) and external (bottom trace) preamplifiers can dramatically reduce the noise floor of signal analyzers (scale is 4 dB/div). The measurements are from a Keysight PXA X-Series signal analyzer, which also includes a noise subtraction feature as another tool to reduce effective analyzer noise floor.

My instinct is to separate noise figure measurements into four general cases, resulting from two characteristics of the DUT: high or low noise figure versus high or low gain.

I should note that this is something of an oversimplification, and not useful for devices such as attenuators and mixers. For the sake of brevity in this post I’ll limit my discussion to RF amplifiers, and in a future post deal with other devices and the limits of this approach.

Because analyzer noise floor is a critical factor in the measurements, it’s probably no surprise that you’ll have an easier time measuring devices with a relatively high level of output noise. This includes devices that have a poor noise figure, no matter their gain. Less obviously, it also includes devices with a very good noise figure, as long as their gain is high enough.

The intuitive thing to keep in mind is that large amounts of gain will amplify DUT input noise by the same amount, resulting in output noise power large enough to be well above the analyzer’s noise floor.

Thus, the most difficult measurements involve devices with modest gain, especially when their noise figure is very good (low). The resulting noise power at the DUT output is also low, making it difficult to distinguish the noise power at the DUT output from that of the signal analyzer.

In his recent post, Nick also brought up the problems that interference and other (non-noise) signals can cause with noise figure measurements. Shielding your setups and ensuring connection integrity can help, and signal analyzers can identify discrete signals and avoid including them in the noise figure results.

One more complicating factor in noise figure measurements is the impedance mismatches that occur in two places: between the noise source and the DUT, and between the DUT and the analyzer. This problem is generally worse at higher frequencies, making it increasingly relevant in 5G and other millimeter-wave applications. The most thorough way to handle the resulting errors in noise power and gain measurements is to use the “cold source” noise figure method implemented in vector network analyzers.

Noise figure measurements will challenge you in many other ways, but those mentioned above should give noise figure novices a better sense of when it’s most important to be careful with the measurements and cautious in interpreting the results.