All-optical and digital non-linear compensation algorithms in flex-coherent grouped and un-grouped contiguous spectrum based networks

We have evaluated that in-line non-linear compensation schemes decrease the complexity of digital backward propagation and enhance the transmission performance of 40/112/224 Gbit/s mixed line rate network. Multiple bit rates, i.e. 40/112/224 Gbit/s and modulation formats (i.e. DP-QPSK and DP-16QAM) are transmitted over 1280 km of Large $$\hbox {A}_{eff}$$Aeff Pure-Silica core fiber. Both grouped and un-grouped spectral allocation schemes are investigated. Optical add-drop multiplexers are used to drop the required wavelength for signal processing in the transmission link. Moreover, hybrid mid-link spectral inversion and in-line non-linear compensation methods are also analyzed. This gives us enhanced system performance and DBP step-size of 400 km in WDM 224 Gbit/s DP-16QAM system, significantly reducing the complexity of digital backward propagation

Recent Progress in the Quantum-to-the-Home Networks

For secure data transmission to the end users in a conventional fiber-to-the-home (FTTH) network, quantum cryptography (QC) is getting much consideration nowadays. QC or more specifically quantum key distribution (QKD) promises unconditionally secure protocol, the Holy Grail of communication and information security that is based on the fundamental laws of quantum physics. In this chapter, we discuss the design issues in a hybrid quantum-classical communication network, performance of the cost-effective off-the-shelf telecommunication equipment, our latest results on a four-state (Quadrature Phase Shift Keying, ‘QPSK’) RF sub-carrier assisted continuous-variable quantum key distribution (CV-QKD) multiuser network based on ultra-low loss quantum channel (pure silica core fiber, ‘PSCF’) and microelectromechanical systems (MEMS) based add/drop switch. The results are thoroughly compared with the commercially available high-cost encryption modules. It is expected that the discussed cost-effective and energy efficient QKD network can facilitate the practical applications of the CV-QKD protocol on the commercial scale in near future for smart access networks

Post-quantum cryptosystems for internet-of-things: A survey on lattice-based algorithms

The latest quantum computers have the ability to solve incredibly complex classical cryptography equations particularly to decode the secret encrypted keys and making the network vulnerable to hacking. They can solve complex mathematical problems almost instantaneously compared to the billions of years of computation needed by traditional computing machines. Researchers advocate the development of novel strategies to include data encryption in the post-quantum era. Lattices have been widely used in cryptography, somewhat peculiarly, and these algorithms have been used in both; (a) cryptoanalysis by using lattice approximation to break cryptosystems; and (b) cryptography by using computationally hard lattice problems (non-deterministic polynomial time hardness) to construct stable cryptographic functions. Most of the dominant features of lattice-based cryptography (LBC), which holds it ahead in the post-quantum league, include resistance to quantum attack vectors, high concurrent performance, parallelism, security under worst-case intractability assumptions, and solutions to long-standing open problems in cryptography. While these methods offer possible security for classical cryptosytems in theory and experimentation, their implementation in energy-restricted Internet-of-Things (IoT) devices requires careful study of regular lattice-based implantation and its simplification in lightweight lattice-based cryptography (LW-LBC). This streamlined post-quantum algorithm is ideal for levelled IoT device security. The key aim of this survey was to provide the scientific community with comprehensive information on elementary mathematical facts, as well as to address real-time implementation, hardware architecture, open problems, attack vectors, and the significance for the IoT networks

Future quantum-to-the-Home (QTTH) all-optical networks

For imparting data security to the end-users in a archetypal fiber-to-the-home (FTTH) network, quantum cryptography (QC) is getting much attention now-a-days. QC or more specifically quantum key distribution (QKD) promises unconditionally secure protocol, the Holy Grail of communication and information security, that is based on the fundamental laws of quantum physics. In this talk, we will discuss our latest experiments on a four-state (Quadrature Phase Shift Keying `QPSK') RF sub-carrier assisted continuous-variable quantum key distribution (CV -QKD) multi-user network based on ultra low loss quantum channel (pure silica core fiber `PSCF') and micro-electromechanical systems (MEMS) based add/drop switch. A coherent receiver with local local oscillator (LLO) is implemented, which ideally could not be accessed by eavesdroppers (Eve), aided with digital signal processing (DSP) module for phase noise cancellation (PNC). With 10 Gbit/s QPSK classical WDM signals, we have recorded secure key rates of 8.65 Mbit/s over 20 km and upto 12 Mbit/s over lossless channel. The experimental setup is further extended to a optically switched multi-user network, i.e. multiple Bobs, for implementing add/drop operations to achieve key rates of 5.98 Mbit/s for a 2_2 MEMS switch. It is expected that the proposed cost-effective and energy efficient QKD network can facilitate the practical application of the CV-QKD protocol on commercial scale in near future for smart access networks

Advanced and flexible multi-carrier receiver architecture for high-count multi-core fiber based space division multiplexed applications

Space division multiplexing (SDM), incorporating multi-core fibers (MCFs), has been demonstrated for effectively maximizing the data capacity in an impending capacity crunch. To achieve high spectral-density through multi-carrier encoding while simultaneously maintaining transmission reach, benefits from inter-core crosstalk (XT) and non-linear compensation must be utilized. In this report, we propose a proof-of-concept unified receiver architecture that jointly compensates optical Kerr effects, intra- and inter-core XT in MCFs. The architecture is analysed in multi-channel 512 Gbit/s dual-carrier DP-16QAM system over 800 km 19-core MCF to validate the digital compensation of inter-core XT. Through this architecture: (a) we efficiently compensates the inter-core XT improving Q-factor by 4.82 dB and (b) achieve a momentous gain in transmission reach, increasing the maximum achievable distance from 480 km to 1208 km, via analytical analysis. Simulation results confirm that inter-core XT distortions are more relentless for cores fabricated around the central axis of cladding. Predominantly, XT induced Q-penalty can be suppressed to be less than 1 dB up-to −11.56 dB of inter-core XT over 800 km MCF, offering flexibility to fabricate dense core structures with same cladding diameter. Moreover, this report outlines the relationship between core pitch and forward-error correction (FEC)

Design and Implementation of System Components for Radio Frequency Based Asset Tracking Devices to Enhance Location Based Services. Study of angle of arrival techniques, effects of mutual coupling, design of an angle of arrival algorithm, design of a novel miniature reconfigurable antenna optimised for wireless communication systems

The angle of arrival estimation of multiple sources plays a vital role in the field of array signal processing as MIMO systems can be employed at both the transmitter and the receiver end and the system capacity, reliability and throughput can be significantly increased by using array signal processing. Almost all applications require accurate direction of arrival (DOA) estimation to localize the sources of the signals. Another important parameter of localization systems is the array geometry and sensor design which can be application specific and is used to estimate the DOA. In this work, various array geometries and arrival estimation algorithms are studied and then a new scheme for multiple source estimation is proposed and evaluated based on the performance of subspace and non-subspace decomposition methods. The proposed scheme has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation and Bartlett estimation techniques. The new scheme has a better performance advantage at low and high signal to noise ratio values (SNRs). The research work also studies different array geometries for both single and multiple incident sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna array elements. This research also considers the shape of the ground plane and its effects on the angle of arrival estimation and in addition it shows how the mutual couplings between the elements effect the overall estimation and how this error can be minimised by using a decoupling matrix. At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver base station is designed and tested. The antenna radiation patterns in the azimuth angle are almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral with striplines feeding network and biased components to improve the impedance bandwidth. The antenna provides the benefit of small size, and re-configurability and is very well suited for the asset tracking applications

Deep Neural Networks for Future Low Carbon Energy Technologies: Potential, Challenges and Economic Development

The global energy demands are growing every year, and fossil fuels won't be able to fulfill our energy needs in the near future. Carbon emissions from the fossil fuels hit an all-time high in 2018 due to increased energy consumption around the globe. On the other hand, renewable energy is an emerging technology and considered as a reliable alternative to the fossil fuels. It is much safer and cleaner than conventional sources. With the advancements in technology, the renewable energy sector has made significant progress in the last decade. One most significant challenge, the large scale renewable energy farms are facing is the un-predictability of the weather patterns. This stochastic nature of the weather data is impacting the solar and wind farms significantly. Although, the classical technologies are in place for weather forecasting but they are not efficient enough to give a feedback to the base-station for any sudden change or future predictions. The demand for renewable energy will only increase in the future. And, that is why renewable energy companies need to invest in Artificial Intelligence (AI), Internet-of-Things (IoT), and other emerging technologies to improve productivity and overcome the shortfalls. Even the large consumers of renewable energy, like supermarkets, factories, offices, railways can use AI technology to make data-driven decisions on power usage and demand. In this article, we present an overview of AI techniques for modelling, prediction and forecasting of wind farming data. Additionally, we have presented economic impact of low carbon energy techniques by analysing the climate change patterns and diverse sources of power generation for the Scotland, United Kingdom region, as a case study

AI secured SD-WAN architecture as a latency critical IoT enabler for 5G and beyond communications

Software-defined Wide Area Network (SD-WAN) is an elementary change in the way network architects and service providers transpose their focus from hardware to the software oriented paradigm. Using a virtual network overlay, SD-WAN classifies and prioritizes how each application goes through the network based on business priority, quality of service (QoS), service-level agreements (SLAs) and security requirements. In this paper, we reviewed a system level concept and implementation of AI secured SD-WAN technology that is helping service providers to easily connect to and integrate across all the different IoT compute edges required to optimize the traffic and management of 5G cells. This architecture will enable a seamless transition for energy sector towards a full 5G connectivity by managing any data available across the edge, leveraging 5G transport for those critical applications that require ultra-low latency and higher bandwidths. Moreover, we weigh the pros and cons of using hybrid Multi-protocol Label Switching (MPLS) with SD-WAN to provide seamless integration, scalability and flexibility to the energy sector

Reflective in-band full duplex NOMA communications for secure 5G networks

In the context of Internet-of-Things (IoT), big Data analytic and the interconnected world, the scientific revolution is increasing the demand for an improved spectrum utilization. An efficient use of the existing spectrum is required for high data-rate transmission. There are several potential ways of solving the challenges of spectrum scarcity. In-Band Full Duplex (IBFD) and Non-Orthogonal Multiple Access (NOMA) are two techniques that can improve the spectral efficiency (SE) in a 5G and Beyond (5GB) cellular networks. This paper proposes a spectral efficient IBFD scheme, Reflective In-Band Full-Duplex (R-IBFD) algorithm for relay selection to improve security of the system with minimum interference. The interference is basically reduced by the addition of orthogonality between the transmitted and received signal in the IBFD mode. The proposed R-IBFD is evaluated with IBFD, Device-to-Device (D2D) and Artificial Noise (AN). Secrecy Outage Probability (SOP) and throughput is analysed for R-IBFD. The simulation results present the comparison between the R-IBFD and conventional decode-and-forward IBFD communication with one or more users operated as a relay