The Road to Next-Generation Multiple Access: A 50-Year Tutorial Review

The evolution of wireless communications has been significantly influenced by remarkable advancements in multiple access (MA) technologies over the past five decades, shaping the landscape of modern connectivity. Within this context, a comprehensive tutorial review is presented, focusing on representative MA techniques developed over the past 50 years. The following areas are explored: i) The foundational principles and information-theoretic capacity limits of power-domain non-orthogonal multiple access (NOMA) are characterized, along with its extension to multiple-input multiple-output (MIMO)-NOMA. ii) Several MA transmission schemes exploiting the spatial domain are investigated, encompassing both conventional space-division multiple access (SDMA)/MIMO-NOMA systems and near-field MA systems utilizing spherical-wave propagation models. iii) The application of NOMA to integrated sensing and communications (ISAC) systems is studied. This includes an introduction to typical NOMA-based downlink/uplink ISAC frameworks, followed by an evaluation of their performance limits using a mutual information (MI)-based analytical framework. iv) Major issues and research opportunities associated with the integration of MA with other emerging technologies are identified to facilitate MA in next-generation networks, i.e., next-generation multiple access (NGMA). Throughout the paper, promising directions are highlighted to inspire future research endeavors in the realm of MA and NGMA.Comment: 43 pages, 38 figures; Submitted to Proceedings of the IEE

Hybrid satellite–terrestrial networks toward 6G : key technologies and open issues

Future wireless networks will be required to provide more wireless services at higher data rates and with global coverage. However, existing homogeneous wireless networks, such as cellular and satellite networks, may not be able to meet such requirements individually, especially in remote terrain, including seas and mountains. One possible solution is to use diversified wireless networks that can exploit the inter-connectivity between satellites, aerial base stations (BSs), and terrestrial BSs over inter-connected space, ground, and aerial networks. Hence, enabling wireless communication in one integrated network has attracted both the industry and the research fraternities. In this work, we provide a comprehensive survey of the most recent work on hybrid satellite–terrestrial networks (HSTNs), focusing on system architecture, performance analysis, design optimization, and secure communication schemes for different cooperative and cognitive HSTN network architectures. Different key technologies are compared. Based on this comparison, several open issues for future research are discussed

Role of Interference and Computational Complexity in Modern Wireless Networks: Analysis, Optimization, and Design

Owing to the popularity of smartphones, the recent widespread adoption of wireless broadband has resulted in a tremendous growth in the volume of mobile data traffic, and this growth is projected to continue unabated. In order to meet the needs of future systems, several novel technologies have been proposed, including cooperative communications, cloud radio access networks (RANs) and very densely deployed small-cell networks. For these novel networks, both interference and the limited availability of computational resources play a very important role. Therefore, the accurate modeling and analysis of interference and computation is essential to the understanding of these networks, and an enabler for more efficient design.;This dissertation focuses on four aspects of modern wireless networks: (1) Modeling and analysis of interference in single-hop wireless networks, (2) Characterizing the tradeoffs between the communication performance of wireless transmission and the computational load on the systems used to process such transmissions, (3) The optimization of wireless multiple-access networks when using cost functions that are based on the analytical findings in this dissertation, and (4) The analysis and optimization of multi-hop networks, which may optionally employ forms of cooperative communication.;The study of interference in single-hop wireless networks proceeds by assuming that the random locations of the interferers are drawn from a point process and possibly constrained to a finite area. Both the information-bearing and interfering signals propagate over channels that are subject to path loss, shadowing, and fading. A flexible model for fading, based on the Nakagami distribution, is used, though specific examples are provided for Rayleigh fading. The analysis is broken down into multiple steps, involving subsequent averaging of the performance metrics over the fading, the shadowing, and the location of the interferers with the aim to distinguish the effect of these mechanisms that operate over different time scales. The analysis is extended to accommodate diversity reception, which is important for the understanding of cooperative systems that combine transmissions that originate from different locations. Furthermore, the role of spatial correlation is considered, which provides insight into how the performance in one location is related to the performance in another location.;While it is now generally understood how to communicate close to the fundamental limits implied by information theory, operating close to the fundamental performance bounds is costly in terms of the computational complexity required to receive the signal. This dissertation provides a framework for understanding the tradeoffs between communication performance and the imposed complexity based on how close a system operates to the performance bounds, and it allows to accurately estimate the required data processing resources of a network under a given performance constraint. The framework is applied to Cloud-RAN, which is a new cellular architecture that moves the bulk of the signal processing away from the base stations (BSs) and towards a centralized computing cloud. The analysis developed in this part of the dissertation helps to illuminate the benefits of pooling computing assets when decoding multiple uplink signals in the cloud. Building upon these results, new approaches for wireless resource allocation are proposed, which unlike previous approaches, are aware of the computing limitations of the network.;By leveraging the accurate expressions that characterize performance in the presence of interference and fading, a methodology is described for optimizing wireless multiple-access networks. The focus is on frequency hopping (FH) systems, which are already widely used in military systems, and are becoming more common in commercial systems. The optimization determines the best combination of modulation parameters (such as the modulation index for continuous-phase frequency-shift keying), number of hopping channels, and code rate. In addition, it accounts for the adjacent-channel interference (ACI) and determines how much of the signal spectrum should lie within the operating band of each channel, and how much can be allowed to splatter into adjacent channels.;The last part of this dissertation contemplates networks that involve multi-hop communications. Building on the analytical framework developed in early parts of this dissertation, the performance of such networks is analyzed in the presence of interference and fading, and it is introduced a novel paradigm for a rapid performance assessment of routing protocols. Such networks may involve cooperative communications, and the particular cooperative protocol studied here allows the same packet to be transmitted simultaneously by multiple transmitters and diversity combined at the receiver. The dynamics of how the cooperative protocol evolves over time is described through an absorbing Markov chain, and the analysis is able to efficiently capture the interference that arises as packets are periodically injected into the network by a common source, the temporal correlation among these packets and their interdependence

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

Potentzia domeinuko NOMA 5G sareetarako eta haratago

Tesis inglés 268 p. -- Tesis euskera 274 p.During the last decade, the amount of data carried over wireless networks has grown exponentially. Several reasons have led to this situation, but the most influential ones are the massive deployment of devices connected to the network and the constant evolution in the services offered. In this context, 5G targets the correct implementation of every application integrated into the use cases. Nevertheless, the biggest challenge to make ITU-R defined cases (eMBB, URLLC and mMTC) a reality is the improvement in spectral efficiency. Therefore, in this thesis, a combination of two mechanisms is proposed to improve spectral efficiency: Non-Orthogonal Multiple Access (NOMA) techniques and Radio Resource Management (RRM) schemes. Specifically, NOMA transmits simultaneously several layered data flows so that the whole bandwidth is used throughout the entire time to deliver more than one service simultaneously. Then, RRM schemes provide efficient management and distribution of radio resources among network users. Although NOMA techniques and RRM schemes can be very advantageous in all use cases, this thesis focuses on making contributions in eMBB and URLLC environments and proposing solutions to communications that are expected to be relevant in 6G

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Enabling Technologies for Internet of Things: Licensed and Unlicensed Techniques

The Internet of Things (IoT) is a novel paradigm which is shaping the evolution of the future Internet. According to the vision underlying the IoT, the next step in increasing the ubiquity of the Internet, after connecting people anytime and everywhere, is to connect inanimate objects. By providing objects with embedded communication capabilities and a common addressing scheme, a highly distributed and ubiquitous network of seamlessly connected heterogeneous devices is formed, which can be fully integrated into the current Internet and mobile networks, thus allowing for the development of new intelligent services available anytime, anywhere, by anyone and anything. Such a vision is also becoming known under the name of Machine-to-Machine (M2M), where the absence of human interaction in the system dynamics is further emphasized. A massive number of wireless devices will have the ability to connect to the Internat through the IoT framework. With the accelerating pace of marketing such framework, the new wireless communications standards are studying/proposing solutions to incorporate the services needed for the IoT. However, with an estimate of 30 billion connected devices, a lot of challenges are facing the current wireless technology. In our research, we address a variety of technology candidates for enabling such a massive framework. Mainly, we focus on the nderlay cognitive radio networks as the unlicensed candidate for IoT. On the other hand, we look into the current efforts done by the standardization bodies to accommodate the requirements of the IoT into the current cellular networks. Specifically, we survey the new features and the new user equipment categories added to the physical layer of the LTE-A. In particular, we study the performance of a dual-hop cognitive radio network sharing the spectrum of a primary network in an underlay fashion. In particular, the cognitive network consists of a source, a destination, and multiple nodes employed as amplify-and-forward relays. To improve the spectral efficiency, all relays are allowed to instantaneously transmit to the destination over the same frequency band. We present the optimal power allocation that maximizes the received signal-to-noise ratio (SNR) at the destination while satisfying the interference constrains of the primary network. The optimal power allocation is obtained through an eigen-solution of a channel-dependent matrix, and is shown to transform the transmission over the non-orthogonal relays into parallel channels. Furthermore, while the secondary destination is equipped with multiple antennas, we propose an antenna selection scheme to select the antenna with the highest SNR. To this end, we propose a clustering scheme to subgroup the available relays and use antenna selection at the receiver to extract the same diversity order. We show that random clustering causes the system to lose some of the available degrees of freedom. We provide analytical expression of the outage probability of the system for the random clustering and the proposed maximum-SNR clustering scheme with antenna selection. In addition, we adapt our design to increase the energy-efficiency of the overall network without significant loss in the data rate. In the second part of this thesis, we will look into the current efforts done by the standardization bodies to accommodate the equirements of the IoT into the current cellular networks. Specifically, we present the new features and the new user equipment categories added to the physical layer of the LTE-A. We study some of the challenges facing the LTE-A when dealing with Machine Type communications (MTC). Specifically, the MTC Physical Downlink control channel (MPDCCH) is among the newly introduced features in the LTE-A that carries the downlink control information (DCI) for MTC devices. Correctly decoding the PDCCH, mainly depends on the channel estimation used to compensate for the channel errors during transmission, and the choice of such technique will affect both the complexity and the performance of the user equipment. We propose and assess the performance of a simple channel estimation technique depends in essence on the Least Squares (LS) estimates of the pilots signal and linear interpolations for low-Doppler channels associated with the MTC application

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Deep Learning Designs for Physical Layer Communications

Wireless communication systems and their underlying technologies have undergone unprecedented advances over the last two decades to assuage the ever-increasing demands for various applications and emerging technologies. However, the traditional signal processing schemes and algorithms for wireless communications cannot handle the upsurging complexity associated with fifth-generation (5G) and beyond communication systems due to network expansion, new emerging technologies, high data rate, and the ever-increasing demands for low latency. This thesis extends the traditional downlink transmission schemes to deep learning-based precoding and detection techniques that are hardware-efficient and of lower complexity than the current state-of-the-art. The thesis focuses on: precoding/beamforming in massive multiple-inputs-multiple-outputs (MIMO), signal detection and lightweight neural network (NN) architectures for precoder and decoder designs. We introduce a learning-based precoder design via constructive interference (CI) that performs the precoding on a symbol-by-symbol basis. Instead of conventionally training a NN without considering the specifics of the optimisation objective, we unfold a power minimisation symbol level precoding (SLP) formulation based on the interior-point-method (IPM) proximal ‘log’ barrier function. Furthermore, we propose a concept of NN compression, where the weights are quantised to lower numerical precision formats based on binary and ternary quantisations. We further introduce a stochastic quantisation technique, where parts of the NN weight matrix are quantised while the remaining is not. Finally, we propose a systematic complexity scaling of deep neural network (DNN) based MIMO detectors. The model uses a fraction of the DNN inputs by scaling their values through weights that follow monotonically non-increasing functions. Furthermore, we investigate performance complexity tradeoffs via regularisation constraints on the layer weights such that, at inference, parts of network layers can be removed with minimal impact on the detection accuracy. Simulation results show that our proposed learning-based techniques offer better complexity-vs-BER (bit-error-rate) and complexity-vs-transmit power performances compared to the state-of-the-art MIMO detection and precoding techniques