Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing.

In the United States, the Federal Communications Commission has adopted rules permitting commercial wireless networks to share spectrum with federal incumbents in the 3.5 GHz Citizens Broadband Radio Service band. These rules require commercial systems to vacate the band when sensors detect radars operated by the U.S. military; a key example being the SPN-43 air traffic control radar. Such sensors require highly-accurate detection algorithms to meet their operating requirements. In this paper, using a library of over 14,000 3.5 GHz band spectrograms collected by a recent measurement campaign, we investigate the performance of thirteen methods for SPN-43 radar detection. Namely, we compare classical methods from signal detection theory and machine learning to several deep learning architectures. We demonstrate that machine learning algorithms appreciably outperform classical signal detection methods. Specifically, we find that a three-layer convolutional neural network offers a superior tradeoff between accuracy and computational complexity. Last, we apply this three-layer network to generate descriptive statistics for the full 3.5 GHz spectrogram library. Our findings highlight potential weaknesses of classical methods and strengths of modern machine learning algorithms for radar detection in the 3.5 GHz band.

Calibration of Time-Interleaved Errors in Digital Real-Time Oscilloscopes.

A channel mismatch calibration method is proposed for use in time-interleaved digital real-time oscilloscope (DRTO) applications. Linear equations are derived using Fourier transforms of the separated signals from each of the time-interleaved analog-to-digital converters (TIADCs). Thus the errors in the TIADCs can be easily calibrated by inversion of a matrix, as opposed to most previous work where additional filters are employed. The calibration accuracy of the proposed method is limited only by the noise produced after the TIADC circuitry, while other methods depend on the filter design. A transfer function measurement method is then proposed for application to commercially available DRTOs. Two-tone signals are measured using DRTOs from various suppliers to validate the proposed method. The occurrence of signals at spurious frequencies is considerably reduced, as demonstrated by the calibrated results.

High-accuracy photoreceiver frequency response measurements at 1.55 µm by use of a heterodyne phase-locked loop.

We demonstrate a high-accuracy heterodyne measurement system for characterizing the magnitude of the frequency response of high-speed 1.55 µm photoreceivers from 2 MHz to greater than 50 GHz. At measurement frequencies below 2 GHz, we employ a phase-locked loop with a double-heterodyne detection scheme, which enables precise tuning of the heterodyne beat frequency with an RF synthesizer. At frequencies above 2 GHz the system is operated in free-run mode with thermal tuning of the laser beat frequency. We estimate the measurement uncertainties for the low frequency range and compare the measured high-frequency response of a photoreceiver to a measurement using electro-optic sampling.

Optical Fiber Geometry: Accurate Measurement of Cladding Diameter.

We have developed three instruments for accurate measurement of optieal fiber cladding diameter: a contact micrometer, a scanning confocal microscope, and a white-light interference microscope. Each instrument has an estimated uncertainty (3 standard deviations) of 50 nm or less, but the confocal microscope may display a 20 nm systematic error as well. The micrometer is used to generate Standard Reference Materials that are commercially available.