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

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

Когерентный прием неортогональных спектрально-эффективных многочастотных сигналов при использовании алгоритма с обратной связью по решению

Introduction. Spectrally efficient frequency division multiplexing (SEFDM) is a promising technology for improving spectral efficiency. Since SEFDM signals transmitted on subcarriers are not orthogonal, interchannel interference occurs due to the mutual influence of signals transmitted on adjacent subcarriers. Algorithms for receiving SEFDM signals can be distinguished into element-by-element coherent detection and maximum-likelihood sequence estimation (MLSE). The former method, although being simpler, is characterized by a low bit error rate performance. The latter method, although providing for a higher energy efficiency, is more complicated and does not allow high absolute message rates.Aim. To consider a trade-off solution to the problem of coherent detection of SEFDM signals under the condition of significant interchannel interference, namely, the use of an iterative algorithm of element-by-element processing with decision feedback at each subcarrier frequency.Materials and methods. Analytical expressions for the operation of a demodulator solver were derived. A simulation model for transmission of SEFDM signals was built in the MatLab environment, including element-by-element detection with decision feedback.Results. The simulation results confirmed the efficiency of the proposed algorithm. For error probabilities p =102…103, the energy gains reach values from 0.2 to 7.5 dB for different values of the non-orthogonal subcarrier spacing. At the same time, the efficiency of the detection algorithm with decision feedback turns out to be significantly lower than that when using the detection algorithm MLSE.Conclusion. The proposed detection algorithm can be used in future generations of mobile communications, which require high transmission rates. By reducing the computational complexity of the algorithm, it is possible to provide for a lower power consumption of mobile devices.Введение. В настоящее время спектрально-эффективное частотное мультиплексирование (Spectrally efficient frequency division multiplexing – SEFDM) является многообещающей технологией, используемой для повышения спектральной эффективности и скорости передачи информации. Алгоритмы приема SEFDMсигналов можно разделить на 2 класса: поэлементный когерентный прием и прием всей информационной посылки. Первый метод более прост, но обладает низкой помехоустойчивостью. При приеме всей посылки возможно получение высокой энергетической эффективности, но реализация такого приема очень сложна и не позволяет реализовать высокие абсолютные скорости передачи сообщений.Цель работы. Рассмотрение компромиссного решения задачи когерентного приема SEFDM-сигналов в условиях существенной межканальной интерференции, а именно использование на каждой поднесущей частоте итерационного алгоритма поэлементной обработки с обратной связью по решению.Материалы и методы. Описание работы демодулятора решающего устройства выполнено аналитическим методом. Имитационная модель передачи SEFDM-сигналов с использованием в приемнике алгоритма поэлементной обработки с обратной связью по решению построена в среде MatLab.Результаты. Результаты моделирования показали, что предложенный алгоритм является достаточно эффективным. При допустимой вероятности ошибок p =102…103 энергетический выигрыш достигает значений 0.2…7.5 дБ для различного неортогонального разноса поднесущих частот. В то же время эффективность алгоритма обнаружения с обратной связью по решению оказывается существенно ниже, чем при приеме всей информационной посылки.Заключение. Предложенный алгоритм приема может быть использован в будущих поколениях мобильной связи, в которых требуются высокие скорости передачи. Благодаря снижению вычислительной сложности алгоритма возможно обеспечить меньшее энергопотребление мобильных устройств

The First 15 Years of SEFDM: A Brief Survey

Spectrally efficient frequency division multiplexing (SEFDM) is a multi-carrier signal waveform, which achieves higher spectral efficiency, relative to conventional orthogonal frequency division multiplexing (OFDM), by violating the orthogonality of its sub-carriers. This survey provides the history of SEFDM development since its inception in 2003, covering fundamentals and concepts, wireless and optical communications applications, circuit design and experimental testbeds. We focus on work done at UCL and outline work done other universities and research laboratories worldwide. We outline techniques to improve the performance of SEFDM and its practical utility with focus on signal generation, detection and channel estimation

Waveform Advancements and Synchronization Techniques for Generalized Frequency Division Multiplexing

To enable a new level of connectivity among machines as well as between people and machines, future wireless applications will demand higher requirements on data rates, response time, and reliability from the communication system. This will lead to a different system design, comprising a wide range of deployment scenarios. One important aspect is the evolution of physical layer (PHY), specifically the waveform modulation. The novel generalized frequency division multiplexing (GFDM) technique is a prominent proposal for a flexible block filtered multicarrier modulation. This thesis introduces an advanced GFDM concept that enables the emulation of other prominent waveform candidates in scenarios where they perform best. Hence, a unique modulation framework is presented that is capable of addressing a wide range of scenarios and to upgrade the PHY for 5G networks. In particular, for a subset of system parameters of the modulation framework, the problem of symbol time offset (STO) and carrier frequency offset (CFO) estimation is investigated and synchronization approaches, which can operate in burst and continuous transmissions, are designed. The first part of this work presents the modulation principles of prominent 5G candidate waveforms and then focuses on the GFDM basic and advanced attributes. The GFDM concept is extended towards the use of OQAM, introducing the novel frequency-shift OQAM-GFDM, and a new low complexity model based on signal processing carried out in the time domain. A new prototype filter proposal highlights the benefits obtained in terms of a reduced out-of-band (OOB) radiation and more attractive hardware implementation cost. With proper parameterization of the advanced GFDM, the achieved gains are applicable to other filtered OFDM waveforms. In the second part, a search approach for estimating STO and CFO in GFDM is evaluated. A self-interference metric is proposed to quantify the effective SNR penalty caused by the residual time and frequency misalignment or intrinsic inter-symbol interference (ISI) and inter-carrier interference (ICI) for arbitrary pulse shape design in GFDM. In particular, the ICI can be used as a non-data aided approach for frequency estimation. Then, GFDM training sequences, defined either as an isolated preamble or embedded as a midamble or pseudo-circular pre/post-amble, are designed. Simulations show better OOB emission and good estimation results, either comparable or superior, to state-of-the-art OFDM system in wireless channels

Spectrally efficient multicarrier communication systems: signal detection, mathematical modelling and optimisation

This thesis considers theoretical, analytical and engineering design issues relating to non-orthogonal Spectrally Efficient Frequency Division Multiplexing (SEFDM) communication systems that exhibit significant spectral merits when compared to Orthogonal FDM (OFDM) schemes. Alas, the practical implementation of such systems raises significant challenges, with the receivers being the bottleneck. This research explores detection of SEFDM signals. The mathematical foundations of such signals lead to proposals of different orthonormalisation techniques as required at the receivers of non-orthogonal FDM systems. To address SEFDM detection, two approaches are considered: either attempt to solve the problem optimally by taking advantage of special cases properties or to apply sub-optimal techniques that offer reduced complexities at the expense of error rates degradation. Initially, the application of sub-optimal linear detection techniques, such as Zero Forcing (ZF) and Minimum Mean Squared Error (MMSE), is examined analytically and by detailed modelling. To improve error performance a heuristic algorithm, based on a local search around an MMSE estimate, is designed by combining MMSE with Maximum Likelihood (ML) detection. Yet, this new method appears to be efficient for BPSK signals only. Hence, various variants of the sphere decoder (SD) are investigated. A Tikhonov regularised SD variant achieves an optimal solution for the detection of medium size signals in low noise regimes. Detailed modelling shows the SD detector to be well suited to the SEFDM detection, however, with complexity increasing with system interference and noise. A new design of a detector that offers a good compromise between computational complexity and error rate performance is proposed and tested through modelling and simulation. Standard reformulation techniques are used to relax the original optimal detection problem to a convex Semi-Definite Program (SDP) that can be solved in polynomial time. Although SDP performs better than other linear relaxations, such as ZF and MMSE, its deviation from optimality also increases with the deterioration of the system inherent interference. To improve its performance a heuristic algorithm based on a local search around the SDP estimate is further proposed. Finally, a modified SD is designed to implement faster than the local search SDP concept. The new method/algorithm, termed the pruned or constrained SD, achieves the detection of realistic SEFDM signals in noisy environments

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial