Use spectrum/signal analysis to limit RF power and spurious noise emissions

Cindy Ong, National Instruments

June 29, 2007

Cindy Ong, National Instruments

Frequency-domain measurement of RF power is one of the basic measurements done by spectrum and vector signal analyzers. These systems need to comply with standard limits on power transmission or spurious noise emissions, and appropriate measurement techniques must be configured to avoid errors.

Key frequency controls such as frequency span, center frequency, resolution bandwidth (RBW) and measurement time affect measurement results.

Frequency span describes the total frequency spectrum captured by the analyzer. Meanwhile, center frequency corresponds to the center of a frequency span. It is noted that center-frequency control, like frequency span, defines the frequency range on the front panel of the instrument. On the other hand, FFT signal analyzers have two distinct modes for acquisition based on the size of the frequency span.

Figure 1: A spectrum analyzer plots in a frequency vs. amplitude trace.

Frequency spans up to the RBW specifications of the instrument are acquired by downconverting a single frequency block and digitizing the downconverted signal. For frequency spans exceeding RBW, spectrum blocks are sequentially converted and digitized.

RBW controls the frequency resolution of the frequency axis. In traditional analyzers, a narrowband filter is swept across a frequency span to create a spectrum display. Filter bandwidth determines the frequency resolution across the frequency axis, hence the label of the control.

Table 1: RBW frequency resolution relates to the bin size of the FFT analyzer.

Meanwhile, FFT-based analyzers have no analog filter and instead use FFT and its associated windowing parameters to determine frequency resolution or RBW. Current FFT-based analyzers, unlike traditional spectrum analyzers, can offer a choice of windows to limit spectral leakage and improve resolution of closely spaced tones in the frequency domain.

Those familiar with FFT analyzers and FFT may question how the RBW frequency resolution relates to the bin size of the FFT. Table 1 above shows how RBW frequency resolution parameter (specified at 3dB and 6dB RBW definitions) relates to FFT bin size in modern RF signal analyzers.

FFT-based analyzers offer a choice of windows to limit spectral leakage and improve resolution of closely-spaced tones in the frequency domain. Traditional spectrum analyzers do not offer such capability.

Measurement (or sweep) time of a traditional swept-tuned analyzer is inversely proportional to the square of the RBW because of the analog filter settling-time. Lowering RBW to improve frequency resolution can exponentially increase sweep time.

In contrast, the FFT signal analyzer performs a longer acquisition and larger FFT calculation as RBW is lowered. With DSP devices becoming faster, measurement speed results in higher-frequency resolution or narrow RBW measurements.

Amplitude settings
Different amplitude controls also affect measurement results. These include reference level (ref level), attenuator settings and detection mode.

Ref level sets the maximum input range of the spectrum analyzer. It controls the y-axis similar to the volts/div on an oscilloscope, and must be set just above the expected maximum power measurement.

The optimum ref level is a balance between minimizing the instrument distortion (caused by very low ref level that saturates input signal) and noise floor (caused by very high ref level that reduces instrument sensitivity and dynamic range).

Sometimes, it is beneficial to set a low ref level, creating instrument distortion, for broadband noise measurements. Doing so improves measurement sensitivity as it recognizes distortion products and ensures that they are excluded in measurements.

The input range of the instrument is also set by the attenuator settings control. This is normally set to automatic so that the software adjusts the attenuation level based on the ref level setting.

Table 2: The spectrum analyzer detection modes can impact on power measurements

Spectrum analyzers tie the display's y-axis to the ref level or attenuator settings in firmware. For virtual instruments that are not constrained, the display's y-axis can be decoupled from these controls if desired. This feature enables visual zoom-in on a portion of the spectrum without affecting amplitude settings of the instrument.

Note that the ref level and the attenuator setting both affect the programmable attenuator, thus only one of the controls needs to be set.

Detection mode, another amplitude control, applies for traditional swept-tuned spectrum analyzers, but not for FFT-based analyzers. Classified as normal, peak, sample or negative peak, detection-mode control determines how the spectrum analyzer handles reduction or compression of spectral information.

It also impacts on integrated power measurement. When spectrum data points exceed what the spectrum analyzer can display, the analyzer proceeds to a data reduction strategy. This causes the detection mode to alter power measurement.

Factors for precision
A spectrum analyzer uses a frequency sweep between start and stop frequencies. An analog ramp generates this frequency sweep while the start frequency of the span is synthesized from a high accuracy time-base reference. Thus, accuracy in measurement is limited by the analog ramp signal and the IF filter center frequency.

Without such analog ramps, FFT-based analyzers are not constrained by these factors and exhibit uniform accuracy in frequency measurement across a span. Accuracy across the span depends on the time base and the measurement algorithm, thus frequency accuracy and repeatability are obtained more easily.

In a traditional swept-tuned analyzer, the causes of frequency error include reference frequency error, frequency span accuracy (5 percent of the span) and RBW (15 percent of the RBW). In contrast, causes of frequency error in an FFT-based analyzer are reference frequency error and RBW, which depends on the measurement algorithm and varies from > 50 percent to < 10 percent of RBW.

To compare these errors, the reference frequency error must be ignored because a precise frequency reference such as a rubidium source can compensate for it. Frequency span of above 50kHz and RBW settings exceeding 1kHz compromise measurement on a swept-tuned spectrum analyzer, unless optimization techniques - such as placing the 100MHz tone at the center of the span - are applied.

Using smaller RBW translates to longer measurements because of the sweep time as a typical spectrum analyzer has a sweep time of 150- 200ms for the example.

The measurement algorithm limits the accuracy of an FFTbased analyzer. For example, modern toolkits for spectral measurement apply interpolation techniques to measure tone frequency at a higher resolution than that indicated by the RBW, such that in the above example, RBW set at 2kHz would guarantee better accuracy.

FFT-based analyzers use comparatively larger RBW settings to accurately measure frequencies, even without applying accuracy- optimized measurement techniques.

This means faster and more accurate measurements in the same test time. Signal analyzers can perform the measurement example in less than 20ms, which is six times better than spectrum analyzers.

Unless appropriate instrument settings are applied, a wide variance in measurement results can be expected even from the same instrument. Thus, understanding its operation is essential to properly set up the instrument for measurement.

Cindy Ong is Marketing Engineer at National Instruments Corp.