mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration. Here, we demonstrate real-time photonic blind interference cancellation using an FPGA-photonic system executing a zero-calibration control algorithm. Our system offers a greater than 200-fold reduction in latency compared to previous work, enabling sub-second cancellation weight identification. We further investigate key trade-offs between system latency, power consumption, and success rate, and we validate sub-Nyquist sampling for blind interference cancellation. We estimate that photonic interference cancellation can reduce the power required for digitization and signal recovery by greater than 74 times compared to the digital electronic alternative.
more » « less- Award ID(s):
- 2128616
- PAR ID:
- 10478997
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract 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.
-
more » « less
An optically-enabled radio frquency (RF) self-interference cancellation system is demonstrated for over-the-air in-band full duplex transmission, based on a signal-of-interest (SOI) driven regular triangle algorithm. Since the goal of a self-interference cancellation system is to retrieve the SOI that is masked by the in-band interference signal, using the SOI quality as the driven parameter for optimizing the self-interference cancellation performance is a natural and effective way to allow the system to adapt to changes and obtain the best cancellation performance. Since regular triangle algorithm has short iteration time, bursts of pseudo-random binary sequence would be used between real data transmission for optimizing the self-interference cancellation performance. The adaptive regular triangle algorithm optimizes the cancellation setting such that the in-band interference can be cancelled to a minimum, i.e., down to the noise floor. During the over-the-air experiment, 22 dB of cancellation depth is obtained over a 300 MHz bandwidth at 18.35 GHz without the need of digital self-interference cancellation.
-
more » « less
Microwave communications have witnessed an incipient proliferation of multi-antenna and opportunistic technologies in the wake of an ever-growing demand for spectrum resources, while facing increasingly difficult network management over widespread channel interference and heterogeneous wireless broadcasting. Radio frequency (RF) blind source separation (BSS) is a powerful technique for demixing mixtures of unknown signals with minimal assumptions, but relies on frequency dependent RF electronics and prior knowledge of the target frequency band. We propose photonic BSS with unparalleled frequency agility supported by the tremendous bandwidths of photonic channels and devices. Specifically, our approach adopts an RF photonic front-end to process RF signals at various frequency bands within the same array of integrated microring resonators, and implements a novel two-step photonic BSS pipeline to reconstruct source identities from the reduced dimensional statistics of front-end output. We verify the feasibility and robustness of our approach by performing the first proof-of-concept photonic BSS experiments on mixed-over-the-air RF signals across multiple frequency bands. The proposed technique lays the groundwork for further research in interference cancellation, radio communications, and photonic information processing.
-
more » « less
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.
