This study aimed to quantify the thermal noise, distortion, and jitter of signals generated by an iPhone app compared to laboratory signal generators. The iPhone app and two lab generators were connected to a spectrum analyzer. Frequency sweeps were taken and analyzed in MATLAB. The results showed that the iPhone app had significantly more distortion and noise than the lab generators. However, its phase noise was comparable to one generator. This study evaluated the iPhone app as a potential low-cost portable alternative to lab signal generators for integrated circuit testing.

1. Quantification of thermal noise, distortion, and jitter
of signal sources for mixed signal IC testing
Professor Michael P. Flynn, Fred Buhler, Esther Yan
Specific aims:
• Quantify the thermal noise, distortion, and jitter in
low-frequency iPhone signals
• Compare with waveform generators on the market to ensure
performance is at or above standard lab equipment
performance
Big picture:
• Ensure that the input signals for the integrated circuits built
and tested in the lab are as low noise as possible, so that any
noise in the output result is from the IC itself, and the noise from
the input is negligible
• Test if iPhone applications can provide an accurate
low-frequency input that is both portable and relatively
inexpensive
• A 1.5 kHz sine wave was used as the input to the spectrum analyzer
- 0 dB ≈ 340 mVpp (taking spectrum analyzer impedance into
account)
• The phone application had significantly greater distortion than the
other two signal generators; the distortion can be noted in Fig. 1 by
the peaks at each of the harmonic frequencies.
• The phase noise (indicated by the“phase skirt”in Fig. 3) was
comparable to the Rigol signal, but the Agilent was significantly
better.
• The noise floor in all three sets of data were comparable, and most
likely due to the internal noise of the spectrum analyzer.
• The phone had significantly more noise than the lab equipment;
this could be due to the hardware of the phone itself, or to the
headphone cord used to connect the phone to the spectrum
analyzer.
- It is possible that these harmonic frequencies could be filtered
out.
- Another possibility is to first put the signal through a DAC,
which could improve distortion.
• A surprising discovery was that the Agilent signal generator
performed much better than the Rigol signal generator in terms of
phase noise.
Fig. 4: Frequency domain of signals with span 0 - 15 kHz Fig. 5: Frequency domain of signals with span 0 - 3 kHz Fig. 6: Frequency domain of signals with span 1.4 - 1.6 kHz
An important aspect of the testing process is ensuring that the signals sent to
integrated circuits (ICs) are as low-noise as possible, in order to guarantee that the
results from the ICs come only from the chips themselves. A newer source of signal
generators can be found on phones; many apps have been developed in recent
years to produce various waveforms, such as sine, square, sawtooth, and triangle
waves, in the audio frequency range (20 Hz to 20 kHz). If the signals created by
these apps are reliable (e.g. the app produces small amounts of noise), then a
phone could be a reliable low-frequency substitute for a heavier, more expensive
waveform generator. In order to test this, an application was downloaded onto an
iPhone 5s, and the phone was connected to the spectrum analyzers through the
headphone jack on the phone.Through MATLAB, a series of sweeps were taken and
points were averaged out to produce a plot of the spectrum analyzer’s output on a
computer. The same was done with two other waveform generators in the lab, and
the noise floors and harmonic frequencies were analyzed to compare the quality of
the app’s signals with the more typically used lab equipment.
ABSTRACT OBJECTIVES
METHODS
Fig. 1: Screenshot of Signal Generator
application for iPhone
TESTING & RESULTS CONCLUSIONS
Equipment:
• Spectrum analyzer: Agilent 8565EC
• Signal generators: Rigol DG4162, Agilent 33220A
• iPhone 5S, Signal Generator application, headphone cable
• GPIB-USB cable, MATLAB
• Waveform generators: Rigol DG4162, Agilent 33220A
• Output of the signal generator was connected to a spectrum
analyzer via a pair of headphones soldered to an SMA connector
• Sweeps were taken from all three signal inputs; data was stored in
MATLAB and averaged out to create Figs. 2-4
• Noise floors and harmonic frequencies were taken into account to
compare the quality of the app’s signals
Fig. 7: Test equipment
Fig. 2: headphone jack and SMA connector
Fig. 3: GPIB-USB cable connected to spectrum analyzer