Tracking down interference in complex RF environments
Radio frequency interference occurs in everything from commercial wireless networks and devices to military communications, radar and electronic warfare (EW) systems. Addressing this problem can be especially difficult since measuring interference is unpredictable. Additionally, the intermittent failure modes in typical signal analyzers make data capture particularly challenging. Consequently, when the root cause of a problem is not yet known, it can be difficult for engineers to set up a measurement that captures the failure.
Despite the challenge, the task of finding, identifying and analyzing interfering signals in a crowded spectrum—whether intentional or not—has become increasingly important in a wide array of applications. One RF recording technique that may prove particularly useful in addressing this problem is gapless capture. Using this technique, system engineers can now measure data continuously over long durations and ensure the capture of all RF events when they occur.
Understanding the measurement challenge
When characterizing system interference, system engineers have traditionally relied on a signal analyzer performing continuous long-duration recordings, as shown in Figure 1. The main limitation to long-duration recording is that test equipment typically has limited on-board memory. Signals-of-interest enter the analyzer’s RF input and are processed by subsequent stages, resulting in the displayed waveform on the right of Figure 1. Up to the blue vertical line, all signals-of-interest within the instrument’s capture bandwidth are processed in real-time, assuming a fixed local oscillator. However, once the samples fill the memory buffer or RAM, the instrument no longer looks at incoming digital samples. Instead, it must process previously recorded samples.
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The signal analyzer does not capture any samples while it post-processes previously captured data, effectively creating a gap in its continuous acquisition of data. If events occur while the previous event is being processed or if the new event lasts longer than the available memory, it falls into this gap and may be missed. Moreover, the analyzer’s trigger setup only captures signals for one set of limited conditions. Once the analyzer fails to capture the event, it is gone forever.
A viable alternative
While resolving RF interference problems in complex RF environments can be a tricky task, gapless recording offers a viable solution to the measurement challenges presented by the typical signal analyzer. The technique solves the problem of not knowing when or where an interference event will occur, or how long it will last, by enabling continuous acquisition of data over long durations. Because there is no gap in the data recorded, the signal-of-interest, such as an intermittent RF event, is easily captured.
Figure 2: In this block diagram, the signal analyzer in Figure 1 has been modified for gapless recording
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One such wideband gapless recording solution is Agilent Technologies’ dual-channel M9392A PXI Vector Signal Analyzer, which can provide two independently tunable channels—each able to record data at 100-MHz bandwidth over many hours (Figure 3).
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While wideband recording in an RF environment has proven itself useful as a characterization tool for long duration RF interference studies, powerful search tools can reduce the burden of searching long recordings for culprit signals. The Agilent 89600 Vector Signal Analyzer software, for example, can be used with the M9392A to provide key insight into the characteristics of the interferer and its effects on the victim signal in select data obtained during gapless recording. Using such software simplifies and reduces the time to find target signals-of-interest and also speeds up the process of analyzing and fixing problems.
It may also be helpful if the gapless recording solution sports key functionality like time-stamping so that recorded data can be mapped to an absolute time, triggering and pre-triggering. Pre-triggered data provides engineers access to signal data leading up to a specific trigger event.
Another key capability is dual-channel recording. In a single-channel recording system it can be difficult to trigger on only the desired signal. As a result, more data is usually recorded than is actually required to ensure the interference event is captured. This additional data takes time and resources to process. A dual-channel recording system like the M9392A reduces the likelihood of false triggering and provides an innate ability to record just the data that’s needed. Signals can be acquired and triggered on one channel, while being recorded on the other. By enabling more efficient discovery of the signals in the RF environment, such discretionary triggering saves a great deal of time and also helps the engineer more effectively solve interference problems.
A structured process
Even with gapless capture, the task of resolving RF interference problems is challenging enough that it deserves to be guided by a systematic process. One such process includes:
. Step 1. Capture
In this step, data is acquired using long-duration recording to ensure the capture of the culprit event. Long duration is required because the signals in the RF environment are often long duration. Also, RF environments change over time and typically have crowded spectrums. Moreover, the increasing bandwidth of modern communication signals means the noise spectrum is wider and interactions are often intermittent, subtle or transient.
. Step 2. Search
Once acquired, a recording is played back and analyzed in the lab, as necessary, to extract information about the culprit interferer. Signal search tools, which can perform automatic searches based on many different criteria, are highly recommended for finding interferers in very large records. The search results in a list of signals from the data record that matches the criteria. Once found, these signals can be clipped out and played back using a signal analysis application.
. Step 3. Re-capture Data
Once the engineer has a better understanding of the problem scenario or what the potential culprit interferers are, it may be necessary to capture more specific recordings. In this optional step, the engineer uses that knowledge of the culprit to trigger additional recordings with better signal-to-noise ratio. These recordings can focus on a specific reaction of a victim receiver to a specific culprit interferer. Here, a dual-channel recording system may prove especially useful as it can be configured to use one of its channels to trigger the recording.
. Step 4. Analyze
Finally, the engineer can uncover the effect of the culprit interferer using analysis software.
Utilizing this process, engineers not only acquire knowledge of the RF environment, but are also able to record information in the frequency band over a long duration. As a result, they can efficiently use RF recording to record, search and analyze target signals in complex RF environments. Conclusion
Resolving RF interference problems in complex RF environments is difficult. With gapless recording, however, engineers can now measure data continuously over long durations and ensure the capture of all RF events of interest when they occur. A wideband recording system modified for gapless capture, especially one that’s dual channel, can be very effective in characterizing system interference in RF environments. Utilizing the system in a structure flow provides an efficient way to find and analyze target signals. Such a capability is increasingly important to commercial wireless and EW applications where interference-related issues continue to be problematic.
About the author
Dave Murray is Electronic Measurement Group Application Engineer, Software and Modular Solutions Division, Agilent Technologies
David Murray joined HP / Agilent in 1994. David has 18 years of experience in RF and Microwave applications across a range of different test and measurement products, and has spent almost 10 of those years as a manufacturing development engineer.
Currently David works as an application engineer based in Santa Rosa, California focusing on Microwave and RF applications in modular form factors such as PXI and AXIe.
David holds a Bachelor of Electrical & Electronic Engineering degree from Heriot-Watt University, Edinburgh, Scotland.
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