Advances in single carrier block modulation with frequency domain processing

International audienceThis special issue focuses on single carrier block modulation (SC-BM) with frequency domain processing. This class of modulation and multiple access schemes complements the orthogonal frequency division multiple access (OFDMA) and its variations. For example, LTE (the long term evolution of the 3GPP standard), and LTE-Advanced, employ OFDMA in the downlink (base stations to mobiles) and SC-FDMA, a version of SC-BM in the uplink (mobiles to base stations). The main reason for adapting the technology of SC-FDMA for uplink LTE is the fact that OFDMA has high "peak-to-average power ratio" (PAPR), which is a disadvantage for mobile devices that are limited by power availability. Besides its advantage of low PAPR, SC-BM technology has a similar performance/complexity to that of OFDMA, and simple frequency domain equalization methods for combating dispersive channels. There were 17 papers submitted to this special issue. All had merits, but the review process reduced the number of accepted papers to 9. The accepted papers cover a number of novel and advanced aspects of single carrier block modulation with frequency domain processing: near-optimal nonlinear and iterative equalization techniques; applications to CDMA, MIMO and ARQ; channel estimation; and application to free-space optical transmission. Following is a summary of the papers. In the paper "Iterative Successive Interference Cancellation for Quasi-Synchronous Block Spread CDMA Based on the Orders of the Times of Arrival", Wang, Bocus, and Coon [1] describe an interference cancellation scheme based on the times of arrival of the signals from different users, and they show that for practical channels this ordering criterion is equivalent to ordering with respect to decreasing average SINR. In "Complexity Reduced MLD Based on QR Decomposition in OFDM MIMO Multiplexing with Frequency Domain Spreading and Code Multiplexing", Nagatomi, Kawai, and Higuchi [2] propose a reduced-complexity maximum likelihood signal detection method for MIMO-OFDM systems with frequency-domain spreading and code multiplexing. They show how to exploit signal orthogonalization based on QR decomposition of the product of the channel and spreading code matrices in the frequency domain to obtain significant complexity reductions. In "Frequency-domain Block Signal detection with QRM-MLD for Training Sequence-aided Single-carrier Transmission", Yamamoto, Takeda and Adachi [3] propose replacement of the cyclic prefix with a known training sequence. The object is to improve BER performance of an equalization scheme which uses QR decomposition with M-algorithm detection, while keeping the number of surviving paths low for reduced complexity. The scheme is especially effective for 16QAM and 64QAM modulation. The paper "Joint Iterative Tx/Rx MMSE-FDE and ISI Cancellation for Single-carrier Hybrid ARQ with Chase Combining" by Takeda and Adachi [4] applies transmitter and receiver equalization and iterative intersymbol interference cancellation to a system with hybrid ARQ transmission, Chase combining and antenna diversity. The equalizer parameters at both transmitter and receiver are optimized for each retransmission. The paper "Novel Techniques of Single Carrier Frequency Domain Equalization for Optical Wireless Communications" by Acolaste, Bar-Ness, and Wilson [5] investigates the application of single-carrier frequency-domain equalization to diffuse optical wireless communications and demonstrates its advantages over OFDM in terms of reduced PAPR and improved error rate in the presence of LED nonlinearity. In the paper "Semi-Blind Channel Estimation for IFDMA in Case of Channels with Large Delay Spreads", Sohl and Klein [6] propose a subspace-based channel estimation algorithm which can cope with large delay spreads. In previous work on IFDMA, the number of channel taps that can be estimated was limited to the number of subcarriers per user. The subspace analysis in this paper relaxes this constraint and increases the number of taps that can be estimated. The paper "Channel Frequency response Estimation for MIMO with Systems with Frequency-Domain Equalization " by Yang, Shi, Chew, and Tjhung [7] suggests a training-based channel frequency response (CFR) estimation scheme which is hardware efficient when integrated with and SC-FDE and space time coding (STC) in MIMO Systems. An MSE analysis of this CFR estimation scheme is provided, which considered linear estimators based on both LS and minimum MSE criteria. Also with a given constraint which effectively limits the transmit power of the training signals, the paper investigates the optimal design of training signals under different a priori knowledge of the channel statistics. For the special case of 2 transmit antennas, it was demonstrated that CFR estimation could be implemented in adaptive manner. The paper by Dang, Ruder, Schober and Gerstacker [8], "MMSE Beamforming for SC-FDMA Transmission over MIMO ISI Channels", derives minimum mean squared error beamforming strategies for multi-antenna reception, as well as further modifications to reduce the transmitted peak to average power ratios. The paper by Nishino, Tanahashi, and Ochiai [9], "A Bit Labeling Design for Trellis-Shaped Single-Carrier PSK with PAPR Reduction", investigates application of trellis shaping to reduce the PAPR of band-limited single-carrier PSK signals. The authors demonstrate that the uncoded bit error rate and PAPR reduction capability of trellis shaping is highly dependent on bit labeling. They propose a bit labeling scheme for high-order PSK constellation that can efficiently reduce PAPR while achieving BER performance comparable to that of Gray labeling

Constellation design for future communication systems: a comprehensive survey

[EN] The choice of modulation schemes is a fundamental building block of wireless communication systems. As a key component of physical layer design, they critically impact the expected communication capacity and wireless signal robustness. Their design is also critical for the successful roll-out of wireless standards that require a compromise between performance, efficiency, latency, and hardware requirements. This paper presents a survey of constellation design strategies and associated outcomes for wireless communication systems. The survey discusses their performance and complexity to address the need for some desirable properties, including consistency, channel capacity, system performance, required demapping architecture, flexibility, and independence. Existing approaches for constellation designs are investigated using appropriate metrics and categorized based on their theoretical algorithm design. Next, their application to different communication standards is analyzed in context, aiming at distilling general guidelines applicable to the wireless building block design. Finally, the survey provides a discussion on design directions for future communication system standardization processes.This work was supported in part by the Basque Government under Grant IT1234-19, in part by the PREDOC under Program PRE_2020_2_0105, and in part by the Spanish Government through the Project PHANTOM (MCIU/AEI/FEDER, UE) under Gran

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

Applications of Lattice Codes in Communication Systems

In the last decade, there has been an explosive growth in different applications of wireless technology, due to users' increasing expectations for multi-media services. With the current trend, the present systems will not be able to handle the required data traffic. Lattice codes have attracted considerable attention in recent years, because they provide high data rate constellations. In this thesis, the applications of implementing lattice codes in different communication systems are investigated. The thesis is divided into two major parts. Focus of the first part is on constellation shaping and the problem of lattice labeling. The second part is devoted to the lattice decoding problem. In constellation shaping technique, conventional constellations are replaced by lattice codes that satisfy some geometrical properties. However, a simple algorithm, called lattice labeling, is required to map the input data to the lattice code points. In the first part of this thesis, the application of lattice codes for constellation shaping in Orthogonal Frequency Division Multiplexing (OFDM) and Multi-Input Multi-Output (MIMO) broadcast systems are considered. In an OFDM system a lattice code with low Peak to Average Power Ratio (PAPR) is desired. Here, a new lattice code with considerable PAPR reduction for OFDM systems is proposed. Due to the recursive structure of this lattice code, a simple lattice labeling method based on Smith normal decomposition of an integer matrix is obtained. A selective mapping method in conjunction with the proposed lattice code is also presented to further reduce the PAPR. MIMO broadcast systems are also considered in the thesis. In a multiple antenna broadcast system, the lattice labeling algorithm should be such that different users can decode their data independently. Moreover, the implemented lattice code should result in a low average transmit energy. Here, a selective mapping technique provides such a lattice code. Lattice decoding is the focus of the second part of the thesis, which concerns the operation of finding the closest point of the lattice code to any point in N-dimensional real space. In digital communication applications, this problem is known as the integer least-square problem, which can be seen in many areas, e.g. the detection of symbols transmitted over the multiple antenna wireless channel, the multiuser detection problem in Code Division Multiple Access (CDMA) systems, and the simultaneous detection of multiple users in a Digital Subscriber Line (DSL) system affected by crosstalk. Here, an efficient lattice decoding algorithm based on using Semi-Definite Programming (SDP) is introduced. The proposed algorithm is capable of handling any form of lattice constellation for an arbitrary labeling of points. In the proposed methods, the distance minimization problem is expressed in terms of a binary quadratic minimization problem, which is solved by introducing several matrix and vector lifting SDP relaxation models. The new SDP models provide a wealth of trade-off between the complexity and the performance of the decoding problem

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

Satellite Communications

This study is motivated by the need to give the reader a broad view of the developments, key concepts, and technologies related to information society evolution, with a focus on the wireless communications and geoinformation technologies and their role in the environment. Giving perspective, it aims at assisting people active in the industry, the public sector, and Earth science fields as well, by providing a base for their continued work and thinking

Machine Learning in Digital Signal Processing for Optical Transmission Systems

The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems

Uncoded space-time labeling diversity with three transmit antennas: symbol mapping designs and error performance analysis.

Doctoral Degrees. University of KwaZulu-Natal, Durban.Abstract available in PDF.Publications on page iii