Single carrier optical FDM in visible light communication

In this paper a comparison between a spiral and a strip shaped LED is presented in terms of the maximum link distance achievable in visible light based car to car communications (VLC-C2C). The transmitted data is recovered from the frame brightness of the video signal. The intensity modulated LED is captured from two scenarios, using a focused and unfocused camera. A data rate of 180 bps with the bit error rate performance below the FEC limit of 10-3 at a distance of 100 cm is successfully achieved, sufficient for transmitting road safety messages for VLC-C2C. It is shown that under the same conditions, the strip LED can effectively recover the data from a greater distance than its spiral counterpart

Neuromorphic computing using wavelength-division multiplexing

Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potential to dramatically enhance the computing power and energy efficiency of mainstream electronic processors, due to their ultralarge bandwidths of up to 10s of terahertz together with their analog architecture that avoids the need for reading and writing data back and forth. Different multiplexing techniques have been employed to demonstrate ONNs, amongst which wavelength division multiplexing (WDM) techniques make sufficient use of the unique advantages of optics in terms of broad bandwidths. Here, we review recent advances in WDM based ONNs, focusing on methods that use integrated microcombs to implement ONNs. We present results for human image processing using an optical convolution accelerator operating at 11 Tera operations per second. The open challenges and limitations of ONNs that need to be addressed for future applications are also discussed.Comment: 13 pages, 8 figures, 160 reference

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

Fully-photonic digital radio over fibre for future super-broadband access network applications

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityIn this thesis a Fully-Photonic DRoF (FP-DRoF) system is proposed for deploying of future super-broadband access networks. Digital Radio over Fibre (DRoF) is more independent of the fibre network impairments and the length of fibre than the ARoF link. In order for fully optical deployment of the signal conversion techniques in the FP-DRoF architecture, two key components an Analogue-to-Digital Converter (ADC) and a Digital-to-Analogue Converter (DAC)) for data conversion are designed and their performance are investigated whereas the physical functionality is evaluated. The system simulation results of the proposed pipelined Photonic ADC (PADC) show that the PADC has 10 GHz bandwidth around 60 GHz of sampling rate. Furthermore, by changing the bandwidth of the optical bandpass filter, switching to another band of sampling frequency provides optimised performance condition of the PADC. The PADC has low changes on the Effective Number of Bit (ENOB) response versus analogue RF input from 1 GHz up to 22 GHz for 60 GHz sampling frequency. The proposed 8-Bit pipelined PADC performance in terms of ENOB is evaluated at 60 Gigasample/s which is about 4.1. Recently, different methods have been reported by researchers to implement Photonic DACs (PDACs), but their aim was to convert digital electrical signals to the corresponding analogue signal by assisting the optical techniques. In this thesis, a Binary Weighted PDAC (BW-PDAC) is proposed. In this BW-PDAC, optical digital signals are fully optically converted to an analogue signal. The spurious free dynamic range at the output of the PDAC in a back-to-back deployment of the PADC and the PDAC was 26.6 dBc. For further improvement in the system performance, a 3R (Retiming, Reshaping and Reamplifying) regeneration system is proposed in this thesis. Simulation results show that for an ultrashort RZ pulse with a 5% duty cycle at 65 Gbit/s using the proposed 3R regeneration system on a link reduces rms timing jitter by 90% while the regenerated pulse eye opening height is improved by 65%. Finally, in this thesis the proposed FP-DRoF functionality is evaluated whereas its performance is investigated through a dedicated and shared fibre links. The simulation results show (in the case of low level signal to noise ratio, in comparison with ARoF through a dedicated fibre link) that the FP-DRoF has better BER performance than the ARoF in the order of 10-20. Furthermore, in order to realize a BER about 10-25 for the ARoF, the power penalty is about 4 dBm higher than the FP-DRoF link. The simulation results demonstrate that by considering 0.2 dB/km attenuation of a standard single mode fibre, the dedicated fibre length for the FP-DRoF link can be increased to about 20 km more than the ARoF link. Moreover, for performance assessment of the proposed FP-DRoF in a shared fibre link, the BER of the FP-DRoF link is about 10-10 magnitude less than the ARoF link for -19 dBm launched power into the fibre and the power penalty of the ARoF system is 10 dBm more than the FP-DRoF link. It is significant to increase the fibre link’s length of the FP-DRoF access network using common infrastructure. In addition, the simulation results are demonstrated that the FP-DRoF with non-uniform Wavelength Division Multiplexing (WDM) is more robust against four wave mixing impairment than the conventional WDM technique with uniform wavelength allocation and has better performance in terms of BER. It is clearly verified that the lunched power penalty at CS for DRoF link with uniform WDM techniques is about 2 dB higher than non-uniform WDM technique. Furthermore, uniform WDM method requires more bandwidth than non-uniform scheme which depends on the total number of channels and channels spacing

Novel linear and nonlinear optical signal processing for ultra-high bandwidth communications

The thesis is articulated around the theme of ultra-wide bandwidth single channel signals. It focuses on the two main topics of transmission and processing of information by techniques compatible with high baudrates. The processing schemes introduced combine new linear and nonlinear optical platforms such as Fourier-domain programmable optical processors and chalcogenide chip waveguides, as well as the concept of neural network. Transmission of data is considered in the context of medium distance links of Optical Time Division Multiplexed (OTDM) data subject to environmental fluctuations. We experimentally demonstrate simultaneous compensation of differential group delay and multiple orders of dispersion at symbol rates of 640 Gbaud and 1.28 Tbaud. Signal processing at high bandwidth is envisaged both in the case of elementary post-transmission analog error mitigation and in the broader field of optical computing for high level operations (“optical processor”). A key innovation is the introduction of a novel four-wave mixing scheme implementing a dot-product operation between wavelength multiplexed channels. In particular, it is demonstrated for low-latency hash-key based all-optical error detection in links encoded with advanced modulation formats. Finally, the work presents groundbreaking concepts for compact implementation of an optical neural network as a programmable multi-purpose processor. The experimental architecture can implement neural networks with several nodes on a single optical nonlinear transfer function implementing functions such as analog-to-digital conversion. The particularity of the thesis is the new approaches to optical signal processing that potentially enable high level operations using simple optical hardware and limited cascading of components

All-passive pixel super-resolution of time-stretch imaging

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the- art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate --- hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (approx. 2--5 GSa/s) --- more than four times lower than the originally required readout rate (20 GSa/s) --- is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time- stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing.Comment: 17 pages, 8 figure

Digital signal processing waveform aggregation and its experimental demonstration for next generation mobile fronthaul

L'abstract è presente nell'allegato / the abstract is in the attachmen