Non-orthogonal signal transmission over nonlinear optical channels

The performance of spectrally efficient frequency division multiplexing (SEFDM) in optical communication systems is investigated considering the impact of fiber nonlinearities. Relative to orthogonal frequency division multiplexing (OFDM), sub-carriers within SEFDM signals are packed closer at a frequency spacing less than the symbol rate. In order to recover the data, a specially designed sphere decoding detector is used at the receiver end to compensate for the self-created inter carrier interference encountered in SEFDM signals. Our research demonstrated the benefits of the use of sphere decoding in SEFDM and also demonstrates the performance improvement of long-haul optical communication systems using SEFDM compared to the use of conventional OFDM, when fiber nonlinearities are considered. Different modulation formats ranging from4QAM to 32QAM are studied and it is shown that, for the same spectral efficiency and information rate, SEFDM signals allow a significant increase in the transmission distance compared to conventional OFDM signals

Transmission Experiment of Bandwidth Compressed Carrier Aggregation in a Realistic Fading Channel

In this paper, an experimental testbed is designed to evaluate the performance of a bandwidth compressed multicarrier technique termed spectrally efficient frequency division multiplexing (SEFDM) in a carrier aggregation (CA) scenario1. Unlike orthogonal frequency division multiplexing (OFDM), SEFDM is a non-orthogonal waveform which, relative to OFDM, packs more sub-carriers in a given bandwidth, thereby improving spectral efficiency. CA is a long term evolution-advanced (LTE-Advanced) featured technique that offers a higher throughput by aggregating multiple legacy radio bands. Considering the scarcity of radio spectrum, SEFDM signals can be utilized to enhance CA performance. The combination of the two techniques results in a larger number of aggregated component carriers (CCs) and therefore increased data rate in a given bandwidth with no additional spectral allocation. It is experimentally shown that CA-SEFDM can aggregate up to 7 CCs in a limited bandwidth while CA-OFDM can only put 5 CCs in the same bandwidth. In this work, LTE-like framed CA-SEFDM signals are generated and delivered through a realistic LTE channel. A complete experimental setup is described together with error performance and effective spectral efficiency comparisons. Experimental results show that the measured BER performance for CA-SEFDM is very close to CA-OFDM and the effective spectral efficiency of CA-SEFDM can be substantially higher than that of CA-OFDM

mm-Wave Data Transmission and Measurement Techniques: A Holistic Approach

The ever-increasing demand on data services places unprecedented technical requirements on networks capacity. With wireless systems having significant roles in broadband delivery, innovative approaches to their development are imperative. By leveraging new spectral resources available at millimeter-wave (mm-wave) frequencies, future systems can utilize new signal structures and new system architectures in order to achieve long-term sustainable solutions.This thesis proposes the holistic development of efficient and cost-effective techniques and systems which make high-speed data transmission at mm-wave feasible. In this paradigm, system designs, signal processing, and measurement techniques work toward a single goal; to achieve satisfactory system level key performance indicators (KPIs). Two intimately-related objectives are simultaneously addressed: the realization of efficient mm-wave data transmission and the development of measurement techniques to enable and assist the design and evaluation of mm-wave circuits.The standard approach to increase spectral efficiency is to increase the modulation order at the cost of higher transmission power. To improve upon this, a signal structure called spectrally efficient frequency division multiplexing (SEFDM) is utilized. SEFDM adds an additional dimension of continuously tunable spectral efficiency enhancement. Two new variants of SEFDM are implemented and experimentally demonstrated, where both variants are shown to outperform standard signals.A low-cost low-complexity mm-wave transmitter architecture is proposed and experimentally demonstrated. A simple phase retarder predistorter and a frequency multiplier are utilized to successfully generate spectrally efficient mm-wave signals while simultaneously mitigating various issues found in conventional mm-wave systems.A measurement technique to characterize circuits and components under antenna array mutual coupling effects is proposed and demonstrated. With minimal setup requirement, the technique effectively and conveniently maps prescribed transmission scenarios to the measurement environment and offers evaluations of the components in terms of relevant KPIs in addition to conventional metrics.Finally, a technique to estimate transmission and reflection coefficients is proposed and demonstrated. In one variant, the technique enables the coefficients to be estimated using wideband modulated signals, suitable for implementation in measurements performed under real usage scenarios. In another variant, the technique enhances the precision of noisy S-parameter measurements, suitable for characterizations of wideband mm-wave components

Harnessing machine learning for fiber-induced nonlinearity mitigation in long-haul coherent optical OFDM

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has attracted a lot of interest in optical fiber communications due to its simplified digital signal processing (DSP) units, high spectral-efficiency, flexibility, and tolerance to linear impairments. However, CO-OFDM’s high peak-to-average power ratio imposes high vulnerability to fiber-induced non-linearities. DSP-based machine learning has been considered as a promising approach for fiber non-linearity compensation without sacrificing computational complexity. In this paper, we review the existing machine learning approaches for CO-OFDM in a common framework and review the progress in this area with a focus on practical aspects and comparison with benchmark DSP solutions.Peer reviewe

A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems

Optical communication systems represent the backbone of modern communication networks. Since their deployment, different fiber technologies have been used to deal with optical fiber impairments such as dispersion-shifted fibers and dispersion-compensation fibers. In recent years, thanks to the introduction of coherent detection based systems, fiber impairments can be mitigated using digital signal processing (DSP) algorithms. Coherent systems are used in the current 100 Gbps wavelength-division multiplexing (WDM) standard technology. They allow the increase of spectral efficiency by using multi-level modulation formats, and are combined with DSP techniques to combat the linear fiber distortions. In addition to linear impairments, the next generation 400 Gbps/1 Tbps WDM systems are also more affected by the fiber nonlinearity due to the Kerr effect. At high input power, the fiber nonlinear effects become more important and their compensation is required to improve the transmission performance. Several approaches have been proposed to deal with the fiber nonlinearity. In this paper, after a brief description of the Kerr-induced nonlinear effects, a survey on the fiber nonlinearity compensation (NLC) techniques is provided. We focus on the well-known NLC techniques and discuss their performance, as well as their implementation and complexity. An extension of the inter-subcarrier nonlinear interference canceler approach is also proposed. A performance evaluation of the well-known NLC techniques and the proposed approach is provided in the context of Nyquist and super-Nyquist superchannel systems.Comment: Accepted in the IEEE Communications Surveys and Tutorial

Non-orthogonal Frequency Division Multiplexing with Index Modulation

Orthogonal Frequency Division Multiplexing (OFDM) is a well-established technique in wired and wireless communications due to its high spectral efficiency compared to other multicarrier transmission schemes. However, the explosion of Internet of Things (IoT) has demanded a more spectrally-efficient technique to utilize small bandwidths, on which numerous low-power low-rate devices operate. This thesis aims to provide solutions for this problem. First, the integration of index modulation to fast-OFDM, which is a special variant of OFDM, is investigated. The highest obtainable bit rate of this system is derived, which demonstrates enhancements compared to OFDM systems in the low-power low-rate regions. Furthermore, an improved one-dimension constellation is found to optimize the overall bit error rate (BER) of this system. Numerical results show that the proposed system exhibits enhancements in both bit rate and error performance, leading to higher spectral efficiency compared to OFDM in the low-power regions. The second part of the thesis is concerned with reducing the bandwidth consumed by multicarrier transmissions. This results in the mutual orthogonality among subchannels being relaxed, yielding a Non-orthogonal Frequency Division Multiplexing (NFDM) system. The main contribution in this part includes a novel and feasible design for NFDM systems, which is capable of eliminating inter-channel interference (ICI), which is the major limitation of the conventional NFDM system. Because ICI is completely eliminated, the BER performance of the proposed system is the same as that of an OFDM system over additive white Gaussian noise channels. The power spectrum density (PSD) of the proposed system is also investigated, leading to design guidelines and tradeoffs between the PSD shape and the system's bit rate. Finally, index modulation is incorporated in the proposed NFDM systems. Thanks to our ICI-free design of NFDM, this combined system (NFDM-IM) and fast-OFDM-IM share a similar simple two-stage signal detection mechanism. Improved QAM constellations are found for NFDM-IM systems to optimize their overall BER. Obtained results show that with low modulation orders such as 8-QAM (Quadrature Amplitude Modulation), NFDM-IM systems employing the improved constellation achieve BER performance close to that of NFDM in the low BER regions. With equivalent occupied bandwidth and error performance, an NFDM-IM system with optimal 8-QAM constellation produces better spectral efficiency than the one using the conventional hexagonal constellation

Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation

This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined. The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies