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The ever-increasing demand for data rates by mobile users can be fulfilled by radio over fiber (RoF) combined with spectrally-efficient modulation techniques. Thus, RoF is critical to the design of the fronthaul for 5th generation (5G) mobile communication networks. We propose and experimentally demonstrate a low-cost directly modulated laser (DML)-based wavelength division multiplexing (WDM)-RoF transmission system for use in next-generation 5G networks. The proposed architecture provides flexible resource allocation as well, under low and high traffic loads at the remote radio heads (RRHs). We also present robust analytical models of the proposed DML-based WDM-RoF network with spectrally-efficient ${M}$ -ary-quadrature amplitude modulation ( ${M}$ -QAM), beneficial for system designers. In OptiSystem software, we evaluate the error vector magnitudes (EVM) as a function of the optical link lengths, input optical power, and the received optical power with 4/16/64-QAM over the optical link. The EVMs of the link for 4/16/64-QAM are below the 3GPP standards for 5G. We find good agreement between the simulations and the analytical results. We also experimentally demonstrate a small scale model of this network with resource allocation. Such a flexible architecture is suitable for meeting the demands of femtocells in 5G fronthaul networks.

Stimulated Brillouin scattering has been widely utilized to realize frequency-agile narrowband and wideband microwave photonic bandpass filters by primarily utilizing its gain response. However, most demonstrated wideband Brillouin-based filters are limited in operation due to the high-power requirements for bandwidth tailoring. We propose a novel approach to realize wideband reconfigurable, Brillouin-based microwave photonic bandpass filters employing RF interferometry and advanced phase engineering. Demonstrated filters exhibit >20 dB selectivity and >700 MHz bandwidth using only 8 dB peak SBS gain (of intrinsic linewidth 30 MHz), and total optical pump power of only ∼14 dBm. We also demonstrate frequency tunability up to 22 GHz. The filter passband has a very flat and highly linear phase response, thus exhibiting zero group delay which we have experimentally verified by propagating an RF pulse at 10.25 GHz. Furthermore, the filter does not suffer from added Brillouin noise in the passband, which is a major advance compared to conventional Brillouin-based microwave photonic sub-systems. This paper presents simulations, mathematical analysis, and experimental results of the proposed filter. The proposed filter demonstrates a pathway toward power-efficient Brillouin-based microwave photonic filters, utilizing SBS responses, in combination with phase manipulation for advanced filtering operations.

With the rapid development of microwave photonic functionalities to support 5G and defence systems, there has been an increased interest in employing stimulated Brillouin scattering (SBS)-based functionalities to perform tasks that are currently difficult to achieve with conventional electronic devices. Several advances have been made using on-chip SBS to demonstrate RF frequency phase shifters, bandpass and bandstop filters, measurement systems, and delay lines. In this article, we provide an overview of some of these developments made possible by strong on-chip SBS gain. We also provide the reader with design guidelines on the selection of the appropriate waveguide geometry, subsystem design, and analog photonic link configurations to aid them in the realisation of their requisite MWP subsystem. We also focus on some of the design trade-offs that need to be considered when using integrated SBS.

Microwave photonic phase shifters based on stimulated Brillouin scattering (SBS) offer tunable and broadband, optically controllable phase shifts. However, achieving a 360° phase shift requires a large amount of SBS gain which often exceeds the available gain and power handling capability of an integrated waveguide. A Radio Frequency (RF) interference technique has recently been utilized in an integrated silicon platform, which uses forward Brillouin scattering in a suspended waveguide to compensate for the lack of available Brillouin gain in standard silicon on insulator platforms. This interference scheme amplifies the phase shift at the expense of link performance. Here, we demonstrate and analytically model a 360° ultra-broadband phase shifter using backward SBS in both fiber and on-chip by combining SBS and RF interference. The phase enhancement scheme greatly reduces the required Brillouin gain and thus the required optical power. Additionally, the backward architecture reduces filter requirements as the residual pump reflections are simpler to remove compared to the pump in the forward Brillouin scattering case, where the pump co-propagates with the signal. The model provides a deeper insight into the properties of the interferometric phase enhancement scheme and predicts the potential trade-offs of an optimized system, showing reduced link loss at higher levels of Brillouin gain. The model also predicts the sensitivity to variations of the interferometric components. Using this technique, we have demonstrated a broadband phase shift over an ultra-broad bandwidth of 0.1 – 65 GHz, limited only by the bandwidth of the available components. Also, we demonstrate a phase enhancement factor of 10 over a bandwidth of 18 GHz in an integrated chalcogenide waveguide.

We demonstrate multi-target detection based on optical filter-less photonic-dechirping of a frequency-modulated continuous-wave RADAR through a dual-drive Mach-Zehnder modulator-based receiver for four targets at distances from 150cm to 205cm and a range resolution of

This paper utilises knowledge distillation to compress a convolutional neural network trained to learn the nonlinear Schrodinger equation. The teacher-taught student network has improved generalisation, quicker convergence, and fewer trainable parameters. The proposed network is 91.2% compressed with a mean square error comparable to the teacher.

We propose a fiber-powered antenna system where an antenna at the remote site is powered wholly by optical energy transferred over an optical fiber and demonstrate 5G transmission in a 2-way wireless communication link.

We present the excitation of forward Brillouin scattering using orbital angular momentum modes in silicon waveguides through numerical simulations. The highest gain coefficients (~540W-1m-1) are obtained for equal charges of the pump, and Stoke’s modes.

We investigate the effect of RF power on the generation of two frequencies with equal power using four different modulation formats for quantum atom interferometry with Rb atoms. The power-efficiency and stability of each modulation are discussed.

We propose a method for compensating the transmission nulls in a phase-modulated microwave photonic link demodulated with a Mach Zehnder interferometer. Brillouin-enabled null compensation up to 16dB and frequency tunability up to 23GHz is achieved.

We present a unique approach for learning the pulse evolution in a nonlinear fiber using a deep convolutional neural network (CNN) by solving the nonlinear Schrodinger equation (NLSE). Deep network model compression has become widespread for deploying such models in real-world applications. A knowledge distillation (KD) based framework for compressing a CNN is presented here. The student network, termed here as OptiDistillNet has better generalisation, has faster convergence, is faster and uses less number of trainable parameters. This work represents the first effort, to the best of our knowledge, that successfully applies a KD-based technique for any nonlinear optics application. Our tests show that even by reducing the model size by up to 91.2%, we can still achieve a mean square error (MSE) which is very close to the MSE of 1.04*10−5 achieved by the teacher model. The advantages of the suggested model include the use of a simple architecture, fast optimization, and improved accuracy, opening up applications in optical coherent communication systems.

The interaction of dispersion and nonlinear effects gives rise to a wide variety of pulse dynamics and proves to be a fundamental bottleneck for high speed communications. Traditionally, time consuming and computationally inefficient algorithms are used for this purpose1 and therefore, research in nonlinear optics and optical communications is now implementing machine learning based methods.2–5 We show a comprehensive comparison of different neural network (NN) architectures to learn the nonlinear Schrodinger equation (NLSE). We have used a NN based approach to reconstruct the pulse (temporal and spectral domain) at the transmitter from the pulse received through a highly nonlinear fiber (HNLF) without the prior knowledge of fiber parameters. Additionally, the trained network can also predict the dispersion and nonlinear parameters of an unknown fiber. The proposed NN also mitigates the need of using iterative reconstruction methods which are computationally expensive and slow. A detailed comparison of six different NN based techniques namely fully connected NN (FCNN), cascade NN (CaNN), convolutional NN (CNN), long short term memory networks (LSTM), bidirectional LSTM (BiLSTM) and gated recurrent unit (GRU) is presented. To our knowledge, the literature does not contain a detailed discussion of the NN architecture which is most suitable for learning the transfer function of the fiber. We perform a comprehensive study by including all popular NN architectures which enables the estimation of pulse profile for arbitrary pulse width, chirp, second and third order dispersion, nonlinearity and fiber length which can benefit nonlinear optics experiments and coherent optical communications. The growing popularity of NNs is resulting in increased design and development of hardware that is optimized for processing NN architectures. In light of this flexibility and optimised hardware, popularity of NN in optics is set to increase.

Due to increase in demand of the optical fiber communication system there is a special emphasis on diagnosing ultrashort pulses. The linear and nonlinear distortions introduced during transmission gives rise to wide variety of wave dynamics. The conventional signal processing techniques being used for characterising these pulses are computationally inefficient. Since machine learning has shown improvement compared to other analytical methods, we present a comparative study of different neural network (NN) architectures to predict the output pulse profile after transmission through highly nonlinear and dispersive fibers. The trained network has the ability to learn the mapping from a set of input and output pulses for the case of both known and unknown fibers. Since each NN has its own advantages and disadvantages, we to the best of our knowledge, present a comprehensive analysis of six different NN architectures (i) fully connected NN (FCNN), (ii) cascade forward NN (CaNN), (iii) Convolutional NN (CNN), (iv) long short term memory network (LSTM), (v) bidirectional LSTM (BiLSTM) and (vi) gated recurrent unit (GRU) for the first time.

Microwave signal filtering is a fundamental and central functionality in radio-frequency (RF) systems. Underpinned by advanced integrated photonics technologies, emerging integrated microwave photonic (IMWP) filter platforms enable reconfigurable and widely tunable RF signal filtering functionalities that were unattainable using conventional electronics while also exhibiting superior features in terms of compactness, light weight, stability, low power consumption, and low latency. This paper presents a comprehensive review of the principles, architectures, and performance of IMWP filters. We highlight recent advances of IMWP filters enabled by on-chip nonlinear optics, RF-interference technology and emerging integration platforms, with an emphasis on the RF performance which is critical for their usability in real-world applications. We conclude with a perspective on future research challenges and new possibilities for IMWP filters.

Microwave photonic (MWP) filters using on-chip stimulated Brillouin scattering offer great potential for next-generation radio frequency (RF) applications due to the unprecedented high spectral resolution, flexible programmability, and ultra-wideband frequency agility. Although impressive functionalities have been reported, limited link performance, due to the amplification noise induced by the Brillouin gain process, hinders the practical deployment in existing RF applications. In this paper, we present the first comprehensive numerical and experimental study of chip-based Brillouin MWP bandpass filters implemented in a range of link configurations. In the experiments, key RF performance figures of merit, including link gain, noise figure, passband resolution, bandwidth tunability, and passband extinction of chip-based Brillouin filters are experimentally investigated and numerically analyzed. This comprehensive study points out a preferable filter scheme with optimized system-level performance. The numerical model developed in this paper allows for extrapolations to further improve the performance. The systematic work establishes a feasible design route for achieving high link-performance chip-based Brillouin microwave photonic bandpass filters.

We significantly narrow the effective linewidth in a coherent optical link from 75 kHz to ~ 2 kHz using SBS-based optical carrier recovery. Experiment results show that the phase recovery window length can be enlarged by over 100x with less than 0.5 dB Q2 penalty.

We demonstrate SBS-based optical carrier recovery scheme with full EDFA-band coverage and 20 dB of gain. This approach shows nearly an order of magnitude improvement in the operation range of the conventional SBS filter. © 2020 The Author(s)

In this paper, we present the benefits, limitations, architectures, and milestones of the radio-over-fiber (RoF) network for application in the fronthaul of next-generation 5G mobile networks. RoF is conceived as the fronthaul of the fiber-wireless system based on a centralized radio access network (CRAN), where a fully centralized approach shifts the signal processing from the remote radio heads (RRHs) to a baseband unit (BBU) in a central office. We present our recent advances in RoF-based fronthaul for next-generation 5G mobile networks. Furthermore, we experimentally demonstrate the spectral efficient $M$ -ary quadrature-amplitude modulation ( $M$ -QAM) technique in the wavelength division multiplexed (WDM) hybrid fiber-wireless RoF network using a directly modulated laser (DML) with a symbol rate of 250 MBd (megabaud) on two optical wavelengths. The error vector magnitudes of the overall link for 4/16/64-QAM are below the 3GPP standard for 5G.

We propose a low-cost DML-based hybrid fiber-wireless WDM radio-over-fiber transmission system for 5G fronthaul networks with resource allocation flexibility under different traffic loads and demonstrate it with a proof-of-concept experiment.

Coherent measurements of an optical tone amplified by stimulated Brillouin scattering (SBS) show significant noise when the SBS gain is misaligned, which can be reduced (> 100x) by amplitude clamping through optical injection locking.

Integrated microwave photonics (IMWP) is poised to release the bottlenecks in modern wireless communication systems. The manipulation of microwave signals in the optical domain offers key advantages of broad bandwidth, reconfiguration, and fast tuning speeds. However, in current IMWP devices, there are some challenges that need to be overcome. These include the ~1 GHz frequency resolution of the IMWP functionalities, limited by the on-chip photonic functional devices' performance, which has prompted research into on-chip stimulated Brillouin scattering (SBS) to achieve sub-30 MHz signal processing capabilities. Equally important, the performance metrics including the noise figure, dynamic range, and the insertion loss, need to be improved before commercial deployment. While SBS offers significant advantages of high resolution and reconfigurability, there is potential for improved signal-to-noise ratios and, therefore, to obtain a low noise figure. In this letter, we present an overview of recent approaches for achieving high-performance IMWP functionalities, including SBS-induced noise management and the optimized MWP link configurations.

Simultaneously achieving high link performance and advanced microwave photonic processing functionalities in compact integrated circuits is crucial but challenging for the deployment in future and existing practical applications. In this paper, we present the first comprehensive experimental study to optimize the link performance of a Si 3 N 4 -photonic-chip-based microwave photonic notch filter. This systematic study leads to an optimized link performance of the chip-based filter, demonstrating an RF net gain, a sub-20-dB noise figure and an overall third-order spurious-free dynamic range of 115 dB.Hz 2/3 over a frequency range of 0-12 GHz, in conjunction with advanced filtering functionalities with a notch rejection >50 dB. The achieved performance is based on a unique and low-loss chip-based filter scheme which offers the compatibility with existing link performance optimization techniques, while maintaining the advanced notch filter functionality. Numerical calculations are also performed to explore the future feasibility of implementing a fully integrated microwave photonic filter that approaches the same level of link performance demonstrated in this work. This study is expected to provide a feasible design route to approach fully integrated microwave photonic filters with high link performance.

Modern fiber-optic coherent communications employ advanced, spectrally efficient modulation formats that require sophisticated narrow-linewidth local oscillators (LOs) and complex digital signal processing (DSP). Self-coherent optical orthogonal frequency-division multiplexing (self-CO-OFDM) is a modern technology that retrieves the frequency and phase information from the extracted carrier without employing a LO or additional DSP. However, a wide carrier guard is typically required to easily filter out the optical carrier at the receiver, thus discarding many OFDM middle subcarriers that limit the system data rate. Here, we establish an optical technique for carrier recovery, harnessing large-gain stimulated Brillouin scattering (SBS) on a photonic chip for up to 116.82 Gbit·s−1 self-CO-OFDM signals, without requiring a separate LO. The narrow SBS linewidth allows for a record-breaking small carrier guard band of ∼265 MHz in self-CO-OFDM, resulting in higher capacity than benchmark self-coherent multi-carrier schemes. Chip-based SBS-self-coherent technology reveals comparable performance to state-of-the-art coherent optical receivers while relaxing the requirements of the DSP. In contrast to on-fiber SBS processing, our solution provides phase and polarization stability. Our demonstration develops a low-noise and frequency-tracking filter that synchronously regenerates a low-power narrowband optical tone, which could relax the requirements on very-high-order modulation signaling for future communication networks. The proposed hybrid carrier filtering-and-regeneration technique could be useful in long-baseline interferometry for precision optical timing or reconstructing a reference tone for quantum-state measurements.

Manipulating radio frequency (RF) signals in integrated photonic devices has recently emerged as a new paradigm for wireless communications, enabling high-frequency signal processing and broadband frequency agility in miniaturized photonic platforms. These advances are crucial for space and airborne applications which are weight and size sensitive. Recent progress in on-chip stimulated Brillouin scattering (SBS) using high gain has shown great potentials for RF photonic signal processing, owing to its inherent advantages of high resolution, high reconfigurability, and flexible programmability. On-chip SBS serves as a versatile and high-performance toolbox to process and manipulate the amplitude and phase of RF signals in the optical domain. In this paper, we provide a brief overview of recent advances achieved using SBS in planar waveguides, with a focus on applications requiring phase control of RF signals, including phase shifters, delay lines, and separate carrier tuning. We introduce a power-efficient scheme based on the concept of phase amplification to improve Brillouin-based phase processing capability.

In this paper, we demonstrate a self-homodyne coherent system with a significantly narrowed effective linewidth using optical carrier recovery based on stimulated Brillouin scattering (SBS), employing only coarse path length matching. The effective linewidth of the SBS-based receiver system is reduced from 75 kHz to less than 2 kHz, which is estimated by Lorentzian fitting of power spectra, and confirmed by simulation results of the tolerance window length for phase noise compensation (PNC) with different linewidth. Both experimental and numerical studies on the tracking requirements on PNC algorithms confirm effective linewidth reduction to this level, and show a 32x relaxation of the phase recovery tracking window length. This highlights the potential to significantly reduce the computational complexity of PNC even in coarsely optimized SBS-based self-homodyne coherent systems, providing an alternative to using demanding ultra-low linewidth lasers.

Ultrashort pulses have a crucial role in the evolution of different areas of science such as ultra fast imaging, femtochemistry and high harmonic spectroscopy and therefore, diagnosing and reconstructing ultrashort pulses is important. The interplay of dispersion and nonlinear effects gives rise to a wide variety of pulse dynamics. On the other hand, dispersion, linear and nonlinear effects have proven to be a fundamental bottleneck for high speed communications. Conventionally, time consuming and computationally inefficient algorithms are used to solve these problems. Since machine learning (ML) has proved to be more powerful than other analytical methods we show a comprehensive comparison of different neural network (NN) architectures to learn the mapping of the nonlinear schrodinger equation (NLSE). We have used a ML based approach to construct the distorted output pulse resulting from nonlinear propagation through the fiber. Additionally, the trained network can also predict the dispersion and nonlinear parameters. We have also reconstructed the temporal and spectral profile of transmitted pulse from the pulse distorted due to propagation through a highly nonlinear fiber (HNLF). These techniques can work without the knowledge of fiber parameters. A detailed comparison of six different NN based techniques namely fully connected NN (FCNN), cascade NN (CaNN), convolutional NN (CNN), long short term memory networks (LSTM), bidirectional LSTM (BiLSTM) and gated recurrent unit (GRU) is presented. Results show that a FCNN regressor outperforms the all other architectures.

Processing of microwave signals using photonics has several key advantages for applications in wireless communications. However, to bring photonic-based microwave signal processing to the mainstream requires a reduction of the form factor. Integration is a route for achieving high-performance, low-cost, and small-footprint microwave photonic devices. A high on-chip stimulated Brillouin scattering (SBS) gain is essential for synthesizing several key functionalities for advanced integrated microwave signal processing. We have optimized our on-chip SBS platform to achieve a record on-chip gain of 52 dB. In this paper, we discuss the implications of this giant gain from the viewpoint of new enabled technologies. The giant gain can be distributed over wide frequencies, which can be exploited for the realization of reconfigurable microwave bandpass, bandstop, and multiband filters. High gain also enables the demonstration of low-threshold on-chip lasers, which can be of relevance for a low-noise radio-frequency signal generation. These wide ranges of functionalities are made possible by the breakthrough on-chip gain makes Brillouin-based microwave photonic signal processing a promising approach for real-world implementation in the near future.

Signal processing using on-chip nonlinear or linear optical effects has shown tremendous potential for RF photonic applications. Combining nonlinear and linear elements on the same photonic chip can further enable advanced functionality and enhanced system performance in a robust and compact form. However, the integration of nonlinear and linear optical signal processing units remains challenging due to the competing and demanding waveguide requirements, specifically the combination of high optical nonlinearity in single-pass waveguides, which is desirable for broadband signal processing with low linear loss and negligible nonlinear distortions required for linear signal processing. Here, we report the first demonstration of integrating Brillouin-active waveguides and passive ring resonators on the same integrated photonic chip, enabling an integrated microwave photonic notch filter with ultradeep stopband suppressions of >40 dB, a low filter passband loss of

We present the first demonstration of backward stimulated Brillouin scattering between distinct guided optical spatial modes in an integrated multi-modal photonic circuit. This unique opto-acoustic process enables new opportunities for on-chip Brillouin signal processing technology.

We compare the noise figure (NF) of chip-based tunable microwave photonic bandpass filters using stimulated Brillouin scattering (SBS) gain and loss responses, respectively. The filter using SBS loss scheme exhibits 10-dB lower NF than that using SBS gain scheme.