Machine Learning Applications for Short Reach Optical Communication

With the rapid development of optical communication systems, more advanced techniques conventionally used in long-haul transmissions have gradually entered systems covering shorter distances below 100 km, where higher-speed connections are required in various applications, such as the optical access networks, inter- and intra-data center interconnects, mobile fronthaul, and in-building and indoor communications. One of the techniques that has attracted intensive interests in short-reach optical communications is machine learning (ML). Due to its robust problem-solving, decision-making, and pattern recognition capabilities, ML techniques have become an essential solution for many challenging aspects. In particular, taking advantage of their high accuracy, adaptability, and implementation efficiency, ML has been widely studied in short-reach optical communications for optical performance monitoring (OPM), modulation format identification (MFI), signal processing and in-building/indoor optical wireless communications. Compared with long-reach communications, the ML techniques used in short-reach communications have more stringent complexity and cost requirements, and also need to be more sensitive. In this paper, a comprehensive review of various ML methods and their applications in short-reach optical communications are presented and discussed, focusing on existing and potential advantages, limitations and prospective trends.

Optimal Analysis of 40 Gbps Dispersion Compensated Optical Fiber System

Dispersion is one of the main factors that limit the development of optical fiber communication systems regarding data rate and long distance transmission of the signal. This is because of increases in dispersion with the increase in data rate and distance, resulting in signal degradation. In this work, we propose an optimal dispersion compensated optical fiber system, which is designed on the basis of Q-factor, eye height, and bit error rate. The system operates at a bit rate of 40 Gbps and a distance of 100 km. According to the optimization scheme, the system is simulated using the modulation format Non Return to Zero (NRZ) with uniform and Linear Chirped Apodized Fiber Bragg Grating (LCAFBG) as dispersion compensator. After deciding the Fiber Bragg Grating (FBG) structure, other key parameters are simulated to meet the requirements. The simulation results show that using NRZ modulation format with a LCAFBG Tanh profile gives better performance.

On the Impact of Probabilistic Shaping on Fiber Nonlinearities

This paper addresses probabilistic shaping (PS) which has been a latest key technique to approach capacity of fiber-optic channels. We investigate the impact of PS on nonlinear interference (NLI), including self channel interference (SCI), cross channel interference (XCI), and multi channel interference (MCI) for a polarization multiplexed 16*ary quadrature amplitude modulation format in a wavelength division multiplexed (WDM) system. To this end, we consider performing PS in two scenarios: (i) Solely on the channel of interest and (ii) over all C-band WDM channels of a fiber-optic link by analyzing the effective signal to noise ratio and symbol error rate. It is demonstrated that using the enhanced Gaussian noise model with merely 10% overhead in the first scenario, the applied PS scheme increases the SCI and the total experienced NLI by about 19.23%, and 6.6%, respectively. Interestingly, despite enhancing the NLI in this scenario, the simulated PS technique leads to about 47.6% increase in the transmission reach. In the second scenario, the numerical results show increase of the SCI, XCI, and total NLI around 19.8%, 23.34%, and 20.2%, respectively, but resulting in an increase of 32.3% in the transmission reach.<br>

On the Impact of Probabilistic Shaping on Fiber Nonlinearities

This paper addresses probabilistic shaping (PS) which has been a latest key technique to approach capacity of fiber-optic channels. We investigate the impact of PS on nonlinear interference (NLI), including self channel interference (SCI), cross channel interference (XCI), and multi channel interference (MCI) for a polarization multiplexed 16*ary quadrature amplitude modulation format in a wavelength division multiplexed (WDM) system. To this end, we consider performing PS in two scenarios: (i) Solely on the channel of interest and (ii) over all C-band WDM channels of a fiber-optic link by analyzing the effective signal to noise ratio and symbol error rate. It is demonstrated that using the enhanced Gaussian noise model with merely 10% overhead in the first scenario, the applied PS scheme increases the SCI and the total experienced NLI by about 19.23%, and 6.6%, respectively. Interestingly, despite enhancing the NLI in this scenario, the simulated PS technique leads to about 47.6% increase in the transmission reach. In the second scenario, the numerical results show increase of the SCI, XCI, and total NLI around 19.8%, 23.34%, and 20.2%, respectively, but resulting in an increase of 32.3% in the transmission reach.<br>

Detection and blind channel estimation for UAV-aided wireless sensor networks in smart cities under mobile jamming attack

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a “store-carry and forward” fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts – required to implement the proposed detection strategy – are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.

THz-Photonics Transceivers By All-Dielectric Phonon-Polariton Nonlinear Nanoantennas

The THz spectrum (spanning from 0.3 THz to 30 THz) offers the potential of a plethora of applications, ranging from the imaging through non transparent media to wireless-over-fiber communications and THz-photonics. The latter framework would greatly benefit from the development of optical-to-THz wavelength converters. Exploiting Difference Frequency Generation in a nonlinear all dielectric nanoantenna, we propose a compact solution to this problem. By means of a near-Infrared pump beam (at ω1), the information signal in the optical domain (at ω2) is converted to the THz band (at ω3 = ω2 − ω1). The approach is completely transparent with respect to the modulation format, and can be easily integrated in a metasurface platform for simultaneous frequency and spatial moulding of THz beams.