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1. Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation

   https://doi.org/10.1038/s41467-023-36814-4  

   Zhang, Weipeng; Tait, Alexander; Huang, Chaoran; Ferreira de Lima, Thomas; Bilodeau, Simon; Blow, Eric C.; Jha, Aashu; Shastri, Bhavin J.; Prucnal, Paul (December 2023, Nature Communications)

   Abstract The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues. BSS requires minimal prior knowledge to recover signals from their mixtures, agnostic to the carrier frequency, signal format, and channel conditions. However, previous electronic implementations did not fulfil this versatility due to the inherently narrow bandwidth of radio-frequency (RF) components, the high energy consumption of digital signal processors (DSP), and their shared weaknesses of low scalability. Here, we report a photonic BSS approach that inherits the advantages of optical devices and fully fulfils its “blindness” aspect. Using a microring weight bank integrated on a photonic chip, we demonstrate energy-efficient, wavelength-division multiplexing (WDM) scalable BSS across 19.2 GHz processing bandwidth. Our system also has a high (9-bit) resolution for signal demixing thanks to a recently developed dithering control method, resulting in higher signal-to-interference ratios (SIR) even for ill-conditioned mixtures. 

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2. MTJ-Based Dithering for Stochastic Analog-to-Digital Conversion

   https://doi.org/10.1109/ISCAS51556.2021.9401632  

   Mitrovic, Ana; Friedman, Eby G. (May 2021, Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS))

   null (Ed.)

   The stochastic behavior of magnetic tunnel junctions (MTJ) finds use in many applications - from analog-to- digital conversion to neuromorphic computing. In this paper, a dithering method exploiting the stochastic behavior of an MTJ, based on the voltage controlled magnetic anisotropy effect, is proposed. This method is used to measure low frequency analog signals over an interval. The circuit is composed of two MTJ devices that convert an analog signal into a series of high resistance and low resistance stochastic states, creating a dithering effect. The behavior of the input signal is extracted from the switching frequency. The binary nature of the output signal reduces the complexity, enabling a small, fast, and energy efficient circuit for extracting different forms of information from an analog signal. 

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3. Design of Multichannel Spectrum Intelligence Systems Using Approximate Discrete Fourier Transform Algorithm for Antenna Array-Based Spectrum Perception Applications

   https://doi.org/10.3390/a17080338  

   Madanayake, Arjuna; Lawrance, Keththura; Kumarasiri, Bopage Umesha; Sivasankar, Sivakumar; Gunaratne, Thushara; Edussooriya, Chamira_U S; Cintra, Renato J (August 2024, Algorithms)

   The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML-driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML-based algorithms for the sensing and perception of waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to a high chip area and power consumption. We address this issue by exploiting the recently proposed approximate discrete Fourier transform (ADFT), which has its own sparse factorization for real-time implementation at a low complexity and power consumption. The ADFT is used to create a wideband multibeam RF digital beamformer and temporal spectrum-based attention unit that monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm with low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high resolution. This two-step process allows the fine-gain FFT to be applied only to directions and bands of interest as determined by the ADFT-based low-complexity 2D spacetime attention unit. The fine-grain FFT provides a spectral signature that can find future use cases in neural network engines for achieving modulation recognition, IoT device identification, and RFI identification. Beamforming and spectral channelization algorithms, a digital computer architecture, and early prototypes using a 32-element fully digital multichannel receiver and field programmable gate array (FPGA)-based high-speed software-defined radio (SDR) are presented. 

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4. Joint CFO and channel estimation in millimeter wave systems with one-bit ADCs

   https://doi.org/10.1109/CAMSAP.2017.8313145  

   Myers, Nitin Jonathan; Heath, Robert W. (December 2017, Proc. of the : IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP))

   We develop a method to jointly estimate the carrier frequency offset (CFO) and the narrowband channel in millimeter wave (mmWave) MIMO systems operating with one-bit analog-to-digital converters (ADCs). We assume perfect timing synchronization and transform the underlying CFO-channel optimization problem to a higher dimensional space using lifting techniques. Exploiting the sparse nature of mmWave MIMO channels in the angle domain, we perform the joint estimation by solving a noisy quantized compressed sensing problem of the lifted version, using generalized approximate message passing. Simulation results show that our method is able to recover both the channel and the CFO using one-bit measurements. 

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5. Measurement Study of FMCW Radar Configurations for Non-contact Vital Signs Monitoring

   https://doi.org/10.1109/RadarConf2248738.2022.9764200  

   Xie, Zongxing; Hua, Yindong; Ye, Fan (January 2022, IEEE Radar Conference)

   Non-contact vital signs monitoring (NCVSM) with radio frequency (RF) is attracting increasing attention due to its non-invasive nature. Recent advances in COTS radar technologies accelerate the development of RF-based solutions. While researchers have implemented and demonstrated the feasibility of NCVSM with diverse radar hardware, most efforts have been focused on devising algorithms to extract vital signs, with limited understanding about the effects of radar configurations. The deficiency in such understanding hinders the design of software defined radar (SDR) optimally customized for NCVSM. In this work, we first hypothesize the effects of FMCW radar configurations using signal-to-interference-plus-noise ratio (SINR) based signal modeling, then we conduct extensive experiments with a COTS FMCW radar, TinyRad, to understand how various parameters impact NCVSM performance compared to a medical device. We find that a larger bandwidth or higher transmitting power in general improves vital sign estimation accuracy; however, coherent processing of consecutive chirps (time diversity) or multiple receiving antennas (space diversity) does not improve the performance. Observations on the baseband (BB) signal show that coherent processing contributes to a higher amplitude but similar phase patterns, whose periodic changes are the key in extracting vital signs. 

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