Spatial Modulation for Generalized MIMO:Challenges, Opportunities, and Implementation

A key challenge of future mobile communication research is to strike an attractive compromise between wireless network's area spectral efficiency and energy efficiency. This necessitates a clean-slate approach to wireless system design, embracing the rich body of existing knowledge, especially on multiple-input-multiple-output (MIMO) technologies. This motivates the proposal of an emerging wireless communications concept conceived for single-radio-frequency (RF) large-scale MIMO communications, which is termed as SM. The concept of SM has established itself as a beneficial transmission paradigm, subsuming numerous members of the MIMO system family. The research of SM has reached sufficient maturity to motivate its comparison to state-of-the-art MIMO communications, as well as to inspire its application to other emerging wireless systems such as relay-aided, cooperative, small-cell, optical wireless, and power-efficient communications. Furthermore, it has received sufficient research attention to be implemented in testbeds, and it holds the promise of stimulating further vigorous interdisciplinary research in the years to come. This tutorial paper is intended to offer a comprehensive state-of-the-art survey on SM-MIMO research, to provide a critical appraisal of its potential advantages, and to promote the discussion of its beneficial application areas and their research challenges leading to the analysis of the technological issues associated with the implementation of SM-MIMO. The paper is concluded with the description of the world's first experimental activities in this vibrant research field

High capacity multiuser multiantenna communication techniques

One of the main issues involved in the development of future wireless communication systems is the multiple access technique used to efficiently share the available spectrum among users. In rich multipath environment, spatial dimension can be exploited to meet the increasing number of users and their demands without consuming extra bandwidth and power. Therefore, it is utilized in the multiple-input multiple-output (MIMO) technology to increase the spectral efficiency significantly. However, multiuser MIMO (MU-MIMO) systems are still challenging to be widely adopted in next generation standards. In this thesis, new techniques are proposed to increase the channel and user capacity and improve the error performance of MU-MIMO over Rayleigh fading channel environment. For realistic system design and performance evaluation, channel correlation is considered as one of the main channel impurities due its severe influence on capacity and reliability. Two simple methods called generalized successive coloring technique (GSCT) and generalized iterative coloring technique (GICT) are proposed for accurate generation of correlated Rayleigh fading channels (CRFC). They are designed to overcome the shortcomings of existing methods by avoiding factorization of desired covariance matrix of the Gaussian samples. The superiority of these techniques is demonstrated by extensive simulations of different practical system scenarios. To mitigate the effects of channel correlations, a novel constellation constrained MU-MIMO (CC-MU-MIMO) scheme is proposed using transmit signal design and maximum likelihood joint detection (MLJD) at the receiver. It is designed to maximize the channel capacity and error performance based on principles of maximizing the minimum Euclidean distance (dmin) of composite received signals. Two signal design methods named as unequal power allocation (UPA) and rotation constellation (RC) are utilized to resolve the detection ambiguity caused by correlation. Extensive analysis and simulations demonstrate the effectiveness of considered scheme compared with conventional MU-MIMO. Furthermore, significant gain in SNR is achieved particularly in moderate to high correlations which have direct impact to maintain high user capacity. A new efficient receive antenna selection (RAS) technique referred to as phase difference based selection (PDBS) is proposed for single and multiuser MIMO systems to maximize the capacity over CRFC. It utilizes the received signal constellation to select the subset of antennas with highest (dmin) constellations due to its direct impact on the capacity and BER performance. A low complexity algorithm is designed by employing the Euclidean norm of channel matrix rows with their corresponding phase differences. Capacity analysis and simulation results show that PDBS outperforms norm based selection (NBS) and near to optimal selection (OS) for all correlation and SNR values. This technique provides fast RAS to capture most of the gains promised by multiantenna systems over different channel conditions. Finally, novel group layered MU-MIMO (GL-MU-MIMO) scheme is introduced to exploit the available spectrum for higher user capacity with affordable complexity. It takes the advantages of spatial difference among users and power control at base station to increase the number of users beyond the available number of RF chains. It is achieved by dividing the users into two groups according to their received power, high power group (HPG) and low power group (LPG). Different configurations of low complexity group layered multiuser detection (GL-MUD) and group power allocation ratio (η) are utilized to provide a valuable tradeoff between complexity and overall system performance. Furthermore, RAS diversity is incorporated by using NBS and a new selection algorithm called HPG-PDBS to increase the channel capacity and enhance the error performance. Extensive analysis and simulations demonstrate the superiority of proposed scheme compared with conventional MU-MIMO. By using appropriate value of (η), it shows higher sum rate capacity and substantial increase in the user capacity up to two-fold at target BER and SNR values

Adaptive Communication for Wireless Massive MIMO Systems

The demand for high data rates in wireless communications is increasing rapidly. One way to provide reliable communication with increased rates is massive multiple-input multiple-output (MIMO) systems where a large number of antennas is deployed. We analyze three systems utilizing a large number of antennas to provide enhancement in the performance of wireless communications. First, we consider a general form of spatial modulation (SM) systems where the number of transmitted data streams is allowed to vary and we refer to it as generalized spatial modulation with multiplexing (GSMM). A Gaussian mixture model (GMM) is shown to accurately model the transmitted spatially modulated signal using a precoding framework. Using this transmit model, a general closed-form expression for the achievable rate when operating over Rayleigh fading channels is evaluated along with a tight upper and a lower bounds for the achievable rate. The obtained expressions are flexible enough to accommodate any form of SM by adjusting the precoding set. Followed by that, we study quantized distributed wireless relay networks where a relay consisting of many geographically dispersed nodes is facilitating communication between unconnected users. Due to bandwidth constraints, distributed relay networks perform quantization at the relay nodes, and hence they are referred to as quantized distributed relay networks. In such systems, users transmit their data simultaneously to the relay nodes through the uplink channel that quantize their observed signals independently to a few bits and broadcast these bits to the users through the downlink channel. We develop algorithms that can be employed by the users to estimate the uplink channels between all users and all relay nodes when the relay nodes are performing simple sign quantization. This setup is very useful in either extending coverage to unconnected regions or replacing the existing wireless infrastructure in case of disasters. Using the uplink channel estimates, we propose multiple decoders that can be deployed at the receiver side. We also study the performance of each of these decoders under different system assumptions. A different quantization framework is also proposed for quantized distributed relay networking where the relay nodes perform vector quantization instead of sign quantization. Applying vector quantization at the relay nodes enables us to propose an algorithm that allocates quantization resources efficiently among the relay nodes inside the relay network. We also study the beamforming design at the users’ side in this case where beamforming design is not trivial due to the quantization that occurs at the relay network. Finally, we study a different setup of distributed communication systems called cell-free massive MIMO. In cell-free massive MIMO, regular cellular communication is replaced by multiple access points (APs) that are placed randomly over the coverage area. All users in the coverage area are sharing time and frequency resources and all APs are serving all UEs while power allocation is done in a central processor that is connected to the APs through a high speed backhaul network. We study the power allocation in cell-free massive MIMO system where APs are equipped with few antennas and how the distribution of the available antennas among access points affects both the performance and the infrastructure cost

Cooperative diversity for the cellular uplink: Sharing strategies, performance analysis, and receiver design

In this thesis, we propose data sharing schemes for the cooperative diversity in a cellular uplink to exploit diversity and enhance throughput performance of the system. Particularly, we consider new two and three-or-more user decode and forward (DF) protocols using space time block codes. We discuss two-user and three-user amplify and forward (AF) protocols and evaluate the performance of the above mentioned data sharing protocols in terms of the bit error rate and the throughput in an asynchronous code division multiple access (CDMA) cellular uplink. We develop a linear receiver for joint space-time decoding and multiuser detection that provides full diversity and near maximum-likelihood performance.;We also focus on a practical situation where inter-user channel is noisy and cooperating users can not successfully estimate other user\u27s data. We further design our system model such that, users decide not to forward anything in case of symbol errors. Channel estimation plays an important role here, since cooperating users make random estimation errors and the base station can not have the knowledge of the errors or the inter-user channels. We consider a training-based approach for channel estimation. We provide an information outage probability analysis for the proposed multi-user sharing schemes. (Abstract shortened by UMI.)

Design of terahertz transceiver schemes for ultrahigh-speed wireless communications

Future ultra-high-speed wireless communication systems face difficult challenges due to the fundamental limitations of current technologies operating at microwave frequencies. Supporting high transmission rates will require the use of more spectral resources that are only available at higher frequencies. Within this context, terahertz (THz) communications have been attracting more and more attention, being considered by the research community as one of the most promising research fields on the topic due to the availability of extensive unused bandwidth segments. However, its widespread use is not yet possible due to some obstacles, such as the high propagation losses that occur in this band and the difficulty in designing devices that can effectively perform both transmission and detection tasks. The purpose of this dissertation is to contribute for the solution of both of the aforementioned problems and to propose novel THz transceiver schemes for ultra-high-speed wireless communications. Three main research areas were addressed: device modelling for the THz; index modulation (IM) based schemes for Beyond 5G (B5G) networks and hybrid precoding designs for THz ultra massive (UM) – multiple input multiple output (MIMO) systems. The main contributions of this work include the creation of a new design for a reconfigurable THz filter; the proposal of a precoded generalized spatial modulation scheme for downlink MIMO transmissions in B5G networks; the creation of a low-complexity hybrid design algorithm with a near fully-digital performance for multiuser (MU) mmWave/THz ultra massive MIMO systems that can incorporate different analog architectures; and the system-level assessment of cloud radio access network (C-RAN) deployments based on low-complexity hybrid precoding designs for massive MIMO downlink transmissions in B5G networks. The first contribution is especially suited for the implementation of reconfigurable THz filters and optical modulators, since it is based on a simple design, which transits from situations in which it presents a full transparency to situations where it achieves full opacity. Moreover, this approach can also be used for the implementation of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) which are important for enabling flexible system designs in RIS-assisted networks. The second contribution showed that the implementation of precoding schemes based on generalised spatial modulations is a solution with a considerable potential for future B5G systems, since it can provide larger throughputs when compared to conventional MU-MIMO schemes with identical spectral efficiencies.The last two contributions showed that through the proposed hybrid design algorithm it becomes possible to replace a fully digital precoder/combiner by a fully-connected or even by a partially-connected architecture (array of subarrays and dynamic array of subarrays), while achieving good tradeoffs between spectral efficiency, power consumption and implementation complexity. These proposals are particularly relevant for the support of UM-MIMO in severely hardware constrained THz systems. Moreover, the capability of achieving significant improvements in terms of throughput performance and coverage over typical cellular networks, when considering hybrid precoding‐based C-RAN deployments in two indoor office scenarios at the THz band, was demonstrated.Os futuros sistemas de comunicação sem fios de velocidade ultra-elevada enfrentam desafios difíceis devido às limitações fundamentais das tecnologias atuais que funcionam a frequências de microondas. O suporte de taxas de transmissão altas exigirá a utilização de mais recursos espectrais que só estão disponíveis em frequências mais elevadas. A banda Terahertz (THz) é uma das soluções mais promissoras devido às suas enormes larguras de banda disponíveis no espectro eletromagnético. No entanto, a sua utilização generalizada ainda não é possível devido a alguns obstáculos, tais como as elevadas perdas de propagação que se verificam nesta banda e a dificuldade em conceber dispositivos que possam desempenhar eficazmente as tarefas de transmissão e deteção. O objetivo desta tese de doutoramento, é contribuir para ambos os problemas mencionados anteriormente e propor novos esquemas de transcetores THz para comunicações sem fios de velocidade ultra-elevada. Três grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: a modelação do dispositivo para o THz; esquemas baseados em modulações de índice (IM) para redes pós-5G (B5G) e desenhos de pré-codificadores híbridos para sistemas THz MIMO ultra-massivos. As principais contribuições deste trabalho incluem a criação de um novo design para um filtro THz reconfigurável; a proposta de uma nova tipologia de modulação espacial generalizada pré-codificada para transmissões MIMO de ligação descendente para redes B5G; a criação de um algoritmo de design híbrido de baixa complexidade com desempenho quase totalmente digital para sistemas MIMO multi-utilizador (MU) mmWave/THz ultra massivos que podem incorporar diferentes arquiteturas analógicas e a avaliação das implementações da rede de acesso de rádio na nuvem (C-RAN) com base em designs de pré-codificação híbridos de baixa complexidade para transmissões MIMO de ligação descendente massivas em redes B5G. A primeira contribuição é especialmente adequada para a implementação de filtros THz reconfiguráveis e moduladores óticos, uma vez que se baseia numa concepção mais simples, que transita de situações em que apresenta uma transparência total para situações em que atinge uma opacidade total. Para além disso, esta abordagem também pode ser utilizada para a implementação de superfícies inteligentes reconfiguráveis (RIS) de transmissão e reflexão simultânea (STAR). A segunda contribuição mostrou que a implementação de esquemas de pré-codificação baseados em modulações espaciais generalizadas é uma solução com um potencial considerável para futuros sistemas B5G, uma vez que permite alcançar maiores ganhos em termos de débito binário quando comparado com esquemas convencionais MU-MIMO com eficiências espectrais idênticas. As duas últimas contribuições mostraram que através do algoritmo proposto torna-se possível substituir a utilização de uma arquitectura totalmente digital por uma arquitetura totalmente conectada ou mesmo por uma arquitetura parcialmente conectada (arrays de subarrays e arrays dinâmicos de subarrays), conseguindo-se bons tradeoffs entre eficiência espectral, consumo de energia e complexidade de implementação. Estas propostas são particularmente relevantes para dar suporte a sistemas THz UM-MIMO com restrições severas ao nível de hardware. Demonstrou-se também a capacidade de se alcançar melhorias significativas em termos de débito binário e cobertura em relação a redes celulares típicas, considerando dois cenários na banda THz

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Contention techniques for opportunistic communication in wireless mesh networks

Auf dem Gebiet der drahtlosen Kommunikation und insbesondere auf den tieferen Netzwerkschichten sind gewaltige Fortschritte zu verzeichnen. Innovative Konzepte und Technologien auf der physikalischen Schicht (PHY) gehen dabei zeitnah in zelluläre Netze ein. Drahtlose Maschennetzwerke (WMNs) können mit diesem Innovationstempo nicht mithalten. Die Mehrnutzer-Kommunikation ist ein Grundpfeiler vieler angewandter PHY Technologien, die sich in WMNs nur ungenügend auf die etablierte Schichtenarchitektur abbilden lässt. Insbesondere ist das Problem des Scheduling in WMNs inhärent komplex. Erstaunlicherweise ist der Mehrfachzugriff mit Trägerprüfung (CSMA) in WMNs asymptotisch optimal obwohl das Verfahren eine geringe Durchführungskomplexität aufweist. Daher stellt sich die Frage, in welcher Weise das dem CSMA zugrunde liegende Konzept des konkurrierenden Wettbewerbs (engl. Contention) für die Integration innovativer PHY Technologien verwendet werden kann. Opportunistische Kommunikation ist eine Technik, die die inhärenten Besonderheiten des drahtlosen Kanals ausnutzt. In der vorliegenden Dissertation werden CSMA-basierte Protokolle für die opportunistische Kommunikation in WMNs entwickelt und evaluiert. Es werden dabei opportunistisches Routing (OR) im zustandslosen Kanal und opportunistisches Scheduling (OS) im zustandsbehafteten Kanal betrachtet. Ziel ist es, den Durchsatz von elastischen Paketflüssen gerecht zu maximieren. Es werden Modelle für Überlastkontrolle, Routing und konkurrenzbasierte opportunistische Kommunikation vorgestellt. Am Beispiel von IEEE 802.11 wird illustriert, wie der schichtübergreifende Entwurf in einem Netzwerksimulator prototypisch implementiert werden kann. Auf Grundlage der Evaluationsresultate kann der Schluss gezogen werden, dass die opportunistische Kommunikation konkurrenzbasiert realisierbar ist. Darüber hinaus steigern die vorgestellten Protokolle den Durchsatz im Vergleich zu etablierten Lösungen wie etwa DCF, DSR, ExOR, RBAR und ETT.In the field of wireless communication, a tremendous progress can be observed especially at the lower layers. Innovative physical layer (PHY) concepts and technologies can be rapidly assimilated in cellular networks. Wireless mesh networks (WMNs), on the other hand, cannot keep up with the speed of innovation at the PHY due to their flat and decentralized architecture. Many innovative PHY technologies rely on multi-user communication, so that the established abstraction of the network stack does not work well for WMNs. The scheduling problem in WMNs is inherent complex. Surprisingly, carrier sense multiple access (CSMA) in WMNs is asymptotically utility-optimal even though it has a low computational complexity and does not involve message exchange. Hence, the question arises whether CSMA and the underlying concept of contention allows for the assimilation of advanced PHY technologies into WMNs. In this thesis, we design and evaluate contention protocols based on CSMA for opportunistic communication in WMNs. Opportunistic communication is a technique that relies on multi-user diversity in order to exploit the inherent characteristics of the wireless channel. In particular, we consider opportunistic routing (OR) and opportunistic scheduling (OS) in memoryless and slow fading channels, respectively. We present models for congestion control, routing and contention-based opportunistic communication in WMNs in order to maximize both throughput and fairness of elastic unicast traffic flows. At the instance of IEEE 802.11, we illustrate how the cross-layer algorithms can be implemented within a network simulator prototype. Our evaluation results lead to the conclusion that contention-based opportunistic communication is feasible. Furthermore, the proposed protocols increase both throughput and fairness in comparison to state-of-the-art approaches like DCF, DSR, ExOR, RBAR and ETT