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

Advanced constellation and demapper schemes for next generation digital terrestrial television broadcasting systems

206 p.Esta tesis presenta un nuevo tipo de constelaciones llamadas no uniformes. Estos esquemas presentan una eficacia de hasta 1,8 dB superior a las utilizadas en los últimos sistemas de comunicaciones de televisión digital terrestre y son extrapolables a cualquier otro sistema de comunicaciones (satélite, móvil, cable¿). Además, este trabajo contribuye al diseño de constelaciones con una nueva metodología que reduce el tiempo de optimización de días/horas (metodologías actuales) a horas/minutos con la misma eficiencia. Todas las constelaciones diseñadas se testean bajo una plataforma creada en esta tesis que simula el estándar de radiodifusión terrestre más avanzado hasta la fecha (ATSC 3.0) bajo condiciones reales de funcionamiento.Por otro lado, para disminuir la latencia de decodificación de estas constelaciones esta tesis propone dos técnicas de detección/demapeo. Una es para constelaciones no uniformes de dos dimensiones la cual disminuye hasta en un 99,7% la complejidad del demapeo sin empeorar el funcionamiento del sistema. La segunda técnica de detección se centra en las constelaciones no uniformes de una dimensión y presenta hasta un 87,5% de reducción de la complejidad del receptor sin pérdidas en el rendimiento.Por último, este trabajo expone un completo estado del arte sobre tipos de constelaciones, modelos de sistema, y diseño/demapeo de constelaciones. Este estudio es el primero realizado en este campo

Peak to average power ratio reduction and error control in MIMO-OFDM HARQ System

Currently, multiple-input multiple-output orthogonal frequency division multiplexing (MIMOOFDM) systems underlie crucial wireless communication systems such as commercial 4G and 5G networks, tactical communication, and interoperable Public Safety communications. However, one drawback arising from OFDM modulation is its resulting high peak-to-average power ratio (PAPR). This problem increases with an increase in the number of transmit antennas. In this work, a new hybrid PAPR reduction technique is proposed for space-time block coding (STBC) MIMO-OFDM systems that combine the coding capabilities to PAPR reduction methods, while leveraging the new degree of freedom provided by the presence of multiple transmit chairs (MIMO). In the first part, we presented an extensive literature review of PAPR reduction techniques for OFDM and MIMO-OFDM systems. The work developed a PAPR reduction technique taxonomy, and analyzed the motivations for reducing the PAPR in current communication systems, emphasizing two important motivations such as power savings and coverage gain. In the tax onomy presented here, we include a new category, namely, hybrid techniques. Additionally, we drew a conclusion regarding the importance of hybrid PAPR reduction techniques. In the second part, we studied the effect of forward error correction (FEC) codes on the PAPR for the coded OFDM (COFDM) system. We simulated and compared the CCDF of the PAPR and its relationship with the autocorrelation of the COFDM signal before the inverse fast Fourier transform (IFFT) block. This allows to conclude on the main characteristics of the codes that generate high peaks in the COFDM signal, and therefore, the optimal parameters in order to reduce PAPR. We emphasize our study in FEC codes as linear block codes, and convolutional codes. Finally, we proposed a new hybrid PAPR reduction technique for an STBC MIMO-OFDM system, in which the convolutional code is optimized to avoid PAPR degradation, which also combines successive suboptimal cross-antenna rotation and inversion (SS-CARI) and iterative modified companding and filtering schemes. The new method permits to obtain a significant net gain for the system, i.e., considerable PAPR reduction, bit error rate (BER) gain as compared to the basic MIMO-OFDM system, low complexity, and reduced spectral splatter. The new hybrid technique was extensively evaluated by simulation, and the complementary cumulative distribution function (CCDF), the BER, and the power spectral density (PSD) were compared to the original STBC MIMO-OFDM signal

A survey on OFDM-based elastic core optical networking

Orthogonal frequency-division multiplexing (OFDM) is a modulation technology that has been widely adopted in many new and emerging broadband wireless and wireline communication systems. Due to its capability to transmit a high-speed data stream using multiple spectral-overlapped lower-speed subcarriers, OFDM technology offers superior advantages of high spectrum efficiency, robustness against inter-carrier and inter-symbol interference, adaptability to server channel conditions, etc. In recent years, there have been intensive studies on optical OFDM (O-OFDM) transmission technologies, and it is considered a promising technology for future ultra-high-speed optical transmission. Based on O-OFDM technology, a novel elastic optical network architecture with immense flexibility and scalability in spectrum allocation and data rate accommodation could be built to support diverse services and the rapid growth of Internet traffic in the future. In this paper, we present a comprehensive survey on OFDM-based elastic optical network technologies, including basic principles of OFDM, O-OFDM technologies, the architectures of OFDM-based elastic core optical networks, and related key enabling technologies. The main advantages and issues of OFDM-based elastic core optical networks that are under research are also discussed

TRANSMISSION PERFORMANCE OPTIMIZATION IN FIBER-WIRELESS ACCESS NETWORKS USING MACHINE LEARNING TECHNIQUES

The objective of this dissertation is to enhance the transmission performance in the fiber-wireless access network through mitigating the vital system limitations of both analog radio over fiber (A-RoF) and digital radio over fiber (D-RoF), with machine learning techniques being systematically implemented. The first thrust is improving the spectral efficiency for the optical transmission in the D-RoF to support the delivery of the massive number of bits from digitized radio signals. Advanced digital modulation schemes like PAM8, discrete multi-tone (DMT), and probabilistic shaping are investigated and implemented, while they may introduce severe nonlinear impairments on the low-cost optical intensity-modulation-direct-detection (IMDD) based D-RoF link with a limited dynamic range. An efficient deep neural network (DNN) equalizer/decoder to mitigate the nonlinear degradation is therefore designed and experimentally verified. Besides, we design a neural network based digital predistortion (DPD) to mitigate the nonlinear impairments from the whole link, which can be integrated into a transmitter with more processing resources and power than a receiver in an access network. Another thrust is to proactively mitigate the complex interferences in radio access networks (RANs). The composition of signals from different licensed systems and unlicensed transmitters creates an unprecedently complex interference environment that cannot be solved by conventional pre-defined network planning. In response to the challenges, a proactive interference avoidance scheme using reinforcement learning is proposed and experimentally verified in a mmWave-over-fiber platform. Except for the external sources, the interference may arise internally from a local transmitter as the self-interference (SI) that occupies the same time and frequency block as the signal of interest (SOI). Different from the conventional subtraction-based SI cancellation scheme, we design an efficient dual-inputs DNN (DI-DNN) based canceller which simultaneously cancels the SI and recovers the SOI.Ph.D

Simultaneous Wireless Information and Power Transfer in 5G communication

Green communication technology is expected to be widely adopted in future generation networks to improve energy efficiency and reliability of wireless communication network. Among the green communication technologies,simultaneous wireless information and power transfer (SWIPT) is adopted for its flexible energy harvesting technology through the radio frequency (RF) signa lthati sused for information transmission. Even though existing SWIPT techniques are flexible and adoptable for the wireless communication networks, the power and time resources of the signal need to be shared between infor- mation transmission and RF energy harvesting, and this compromises the quality of the signal. Therefore,SWIP Ttechniques need to be designed to allow an efficient resource allocation for communication and energy harvesting. The goal oft his thesisis to design SWIP Ttechniques that allow efficient,reliable and secure joint communications and power transference. A problem associated to SWIPT techniques combined with multi carrier signals is that the increased power requirements inherent to energy harvesting purposes can exacerbate nonlinear distortion effects at the transmitter. Therefore, we evaluate nonlinear distortion and present feasible solutions to mitigate the impact of nonlinear distortion effects on the performance.Another goal of the thesisis to take advantage of the energy harvesting signals in SWIP Ttechniques for channel estimation and security purposes.Theperformance of these SWIPT techniques is evaluated analytically, and those results are validated by simulations. It is shownthatthe proposed SWIPT schemes can have excellent performance, out performing conventional SWIPT schemes.Espera-se que aschamadas tecnologiasde green communications sejam amplamente ado- tadas em futuras redes de comunicação sem fios para melhorar a sua eficiência energética a fiabilidade.Entre estas,encontram-se as tecnologias SWIPT (Simultaneous Wireless Information and Power Transference), nas quais um sinal radio é usado para transferir simultaneamente potência e informações.Embora as técnicas SWIPT existentes sejam fle- xíveis e adequadas para as redes de comunicações sem fios, os recursos de energia e tempo do sinal precisam ser compartilhados entre a transmissão de informações e de energia, o que pode comprometer a qualidade do sinal. Deste modo,as técnicas SWIPT precisam ser projetadas para permitir uma alocação eficiente de recursos para comunicação e recolha de energia. O objetivo desta tese é desenvolver técnicas SWIPT que permitam transferência de energia e comunicações eficientes,fiáveis e seguras.Um problema associado às técnicas SWIPT combinadas com sinais multi-portadora são as dificuldades de amplificação ine- rentes à combinação de sinais de transmissão de energia com sinais de transferência de dados, que podem exacerbar os efeitos de distorção não-linear nos sinais transmitidos. Deste modo, um dos objectivos desta tese é avaliar o impacto da distorção não-linear em sinais SWIPT, e apresentar soluções viáveis para mitigar os efeitos da distorção não-linear no desempenho da transmissão de dados.Outro objetivo da tese é aproveitar as vantagens dos sinais de transferência de energia em técnicas SWIPT para efeitos de estimação de canal e segurança na comunicação.Os desempenhos dessas técnicas SWIPT são avaliados analiticamente,sendo os respectivos resultados validados por simulações.É mostrado que os esquemas SWIPT propostos podem ter excelente desempenho, superando esquemas SWIPT convencionais

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review

Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications