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Creators/Authors contains: "Fok, Mable P."

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  1. In this Letter, an unsupervised-learning platform—generative adversarial network (GAN)—is proposed for experimental data augmentation in a deep-learning assisted photonic-based instantaneous microwave frequency measurement (IFM) system. Only 75 sets of experimental data are required and the GAN can augment the small amount of data into 5000 sets of data for training the deep learning model. Furthermore, frequency measurement error of the estimated frequency has improved by an order of magnitude from 50 MHz to 5 MHz. The proposed use of GAN effectively reduces the amount of experimental data needed by 98.75% and reduces measurement error by 10 times.

    Free, publicly-accessible full text available October 4, 2023
  2. The radio frequency spectral shaper is an essential component in emerging multi-service mobile communications, multiband satellite and radar systems, and future 5G/6G radio frequency systems for equalizing spectral unevenness, removing out-of-band noise and interference, and manipulating multi-band signal simultaneously. While it is easy to achieve simple spectral functions using either conventional microwave photonic filters or the optical spectrum to microwave spectra mapping techniques, it is challenging to enable complex spectral shaping functions over tens of GHz bandwidth as well as to achieve point-by-point shaping capability to fulfill the needs in dynamic wireless communications. In this paper, we proposed and demonstrated a novel spectral shaping system, which utilizes a two-section algorithm to automatically decompose the target RF response into a series of Gaussian functions and to reconstruct the desired RF response by microwave photonic techniques. The devised spectral shaping system is capable of manipulating the spectral function in various bands (S, C, and X) simultaneously with step resolution of as fine as tens of MHz. The resolution limitation in optical spectral processing is mitigated using the discrete convolution technique. Over 10 dynamic and independently adjustable spectral control points are experimentally achieved based on the proposed spectral shaper.

  3. A photonic-enabled fully-programmable RF spectral shaper capable of point-by-point precise manipulation of wideband RF spectrum with 30-MHz resolution is experimentally demonstrated. Over 10 spectral-control points are achieved with the optimized spectral decomposition and reconstruction algorithm.
  4. The increasing demands to enhance information security in data transmission, providing countermeasures against jamming in military applications, as well as boosting data capacity in mobile and satellite communication, have led to a critical need for high-speed frequency-hopping systems. Conventional electronics-based frequency-hopping systems suffer from low data rate, low hopping speed, and narrow hopping-frequency bandwidth. Unfortunately, those are important aspects to facilitate frequency-hopping in emerging microwave systems. The recent advancement of microwave photonics—the use of light to process microwave signals—provides promising solutions to tackle the challenges faced by electronic frequency-hopping systems. In this paper, the challenges of achieving real-time frequency-hopping systems are examined. The operation principles and results of various microwave photonics-enabled frequency-hopping systems are comprehensively discussed, which have wide hopping-frequency bandwidth and frequency-hopping speed from nanoseconds to tens of picoseconds. Lastly, a bio-inspired jamming-avoidance system that could potentially be used for adaptive frequency-hopping is also introduced.