Blind source separation in the physical layer

Tait, Alexander N.; Lima, Thomas Ferreira de; Philip, Y.; Chang, Matthew P.; Nahmias, Mitchell A.; Shastri, Bhavin J.; Mittal, Prateek; Prucnal, Paul R.

doi:10.1109/ciss.2018.8362288

Cited by 13 publications

(20 citation statements)

References 38 publications

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“…The signals themselves were chosen to show very simple signal processing tasks for typical AM radio signals. Linear fan-in is used in RF processing for dimensionality reduction and principal component analysis [74]. Followed by a rectifying stage, this system effectively acts as a multi-channel envelope detector (i.e.…”

Section: Response To Multiple Inputsmentioning

confidence: 99%

“…The expansion of these squares yields a ±2AB term -a measure of correlation. In radio signal processing, some algorithms for channel estimation are based on calculating correlation to update estimation parameters [74,75]. Very fast measurements of correlation could accelerate the convergence time and tracking rate of those algorithms.…”

Section: Response To Multiple Inputsmentioning

confidence: 99%

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Silicon Photonic Modulator Neuron

et al. 2019

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There has been a recently renewed interest in neuromorphic photonics, a field promising to access pivotal and unexplored regimes of machine intelligence. Progress has been made on isolated neurons and analog interconnects; nevertheless, this renewal has yet to produce a demonstration of a silicon photonic neuron capable of interacting with other like neurons. We report a modulator-class photonic neuron fabricated in a conventional silicon photonic process line. We demonstrate behaviors of transfer function configurability, fan-in, inhibition, time-resolved processing, and, crucially, autaptic cascadability -a sufficient set of behaviors for a device to act as a neuron participating in a network of like neurons. The silicon photonic modulator neuron constitutes the final piece needed to make photonic neural networks fully integrated on currently available silicon photonic platforms.In this work, we fabricate and demonstrate a silicon photonic modulator neuron. It consists of a balanced photodetector directly connected to a microring (MRR) modulator. We demonstrate that this device possesses the necessary capabilities of a network-compatible neuron: fan-in, high-gain optical-to-optical nonlinearity, and arXiv:1812.11898v1 [physics.app-ph]

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Section: Response To Multiple Inputsmentioning

confidence: 99%

Section: Response To Multiple Inputsmentioning

confidence: 99%

Silicon Photonic Modulator Neuron

et al. 2019

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“…Iltis et al [57] studied a non-cooperative scenario using a game theoretic approach, which must assume that all transceivers abide by a common protocol. In [39], we proposed an algorithm for performing BSS when only one reduced-dimension output can be observed at a given time. The only a priori assumption used is that the sources to be separated are statistically independent: a weak and generally true assumption.…”

Section: Using Projected Moment Informationmentioning

confidence: 99%

“…The key realization of [39] is that multi-dimensional correlation and independence can be inferred and exploited based only on measurements of projection moments. The moments of the projections have a simple relationship to the projection angle.…”

Section: Using Projected Moment Informationmentioning

confidence: 99%

“…In prior work, we proposed the concept of synthesizing multivariate signal features based on univariate observations of the analog photonic domain, which led to novel algorithms for performing blind PCA, ICA, and source separation [39]. In this manuscript, we report the first demonstration of this approach by using a silicon photonic weight bank to ascertain the PC dimensions of and then decompose unobservable 1.0 GHz signals.…”

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Demonstration of Multivariate Photonics: Blind Dimensionality Reduction With Integrated Photonics

Tait

Philip

Lima

et al. 2019

J. Lightwave Technol.

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Multi-antenna radio front-ends generate a multi-dimensional flood of information, most of which is partially redundant. Redundancy is eliminated by dimensionality reduction, but contemporary digital processing techniques face harsh fundamental tradeoffs when implementing this class of functions. These tradeoffs can be broken in the analog domain, in which the performance of optical technologies greatly exceeds that of electronic counterparts. Here, we present concepts, methods, and a first demonstration of multivariate photonics: a combination of integrated photonic hardware, analog dimensionality reduction, and blind algorithmic techniques. We experimentally demonstrate 2-channel, 1.0 GHz principal component analysis in a photonic weight bank using recently proposed algorithms for synthesizing the multivariate properties of signals to which the receiver is blind. Novel methods are introduced for controlling blindness conditions in a laboratory context. This work provides a foundation for further research in multivariate photonic information processing, which is poised to play a role in future generations of wireless technology.

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A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency

Zhang,

Lederman,

Ferreira de Lima

et al. 2024

Light Sci Appl

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Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5 G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305 Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor’s ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing.

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Blind source separation in the physical layer

Cited by 13 publications

References 38 publications

Silicon Photonic Modulator Neuron

Silicon Photonic Modulator Neuron

Demonstration of Multivariate Photonics: Blind Dimensionality Reduction With Integrated Photonics

A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency

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