A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area

Ultra-Dense Networks in 5G and Beyond: Challenges and Promising Solutions

Ultra-Dense Network (UDN) is one of the promising and leading directions in Fifth Generation and beyond (5GB) networks. In UDNs, Small Cells (SCs) or Small Base Stations (SBSs) such as microcells, picocells, or femtocells are deployed in high densities where inter-site distances are within the range of few or tens of meters. UDNs also require that SCs are typically deployed in relatively large densities compared to the Human-Type Communication Users (HTCUs) such as smartphones, tablets, and/or laptops. Such SCs are characterized by their low transmission powers, small coverage areas, and low cost. Hence, the deployment of the SCs can be done either by the cellular network operators or by the customers themselves within their premises to maintain certain levels of Quality of Service (QoS). However, the randomness of the deployment of the SCs along with the small inter-site distances may degrade the achievable performance due to the uncontrolled Inter-Cell Interference (ICI). Therefore, idle mode capability is an inevitable feature in the high-density regime of SCs. In idle mode, a SC is switched off to prevent ICI when no user is associated to it. In doing so, we can imagine the UDN as a mobile network that keeps following the users to remain as close as possible to them. In 5G, different use cases are required to be supported such as enhanced Mobile Broad-Band (eMBB), Ultra-Reliable and Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). On one hand, the inevitable upcoming era of smart living requires unprecedented advances in enabling technologies to support the main building blocks of this era which are Internet of Things (IoT) devices. Machine-Type Communication (MTC), the cellular version of Machine-to-Machine (M2M) communication, constitutes the main enabling technology to support communications among such devices with minimal or even without human intervention. The massive number of these devices, Machine-Type Communication Devices (MTCDs), and the immense amount of traffic generated by them require a paramount shift in cellular and non-cellular wireless technologies to achieve the required connectivity. On the other hand, the sky-rocketing number of data hungry applications installed on human-held devices, or HTCUs, such as video conferencing and virtual reality applications require their own advances in the wireless infrastructure in terms of high capacity, enhanced reliability, and reduced latency. Throughout this thesis, we exploit the UDN infrastructure integrated with other 5G resources and enabling technologies to explore the possible opportunities in supporting both HTC and MTC, either solely or simultaneously. Given the shorter distances between transmitters and receivers encountered in UDNs, more realistic models of the path loss must be adopted such as the Stretched Exponential Path Loss (SEPL) model. We use tools from stochastic geometry to formulate novel mathematical frameworks that can be used to investigate the achievable performance without having to rely on extensive time-consuming Monte-Carlo simulations. Besides, the derived analytical expressions can be used to tune some system parameters or to propose some approaches/techniques that can be followed to optimize the performance of the system under certain circumstances. Tackling practical scenarios, the complexity, or sometimes in-feasibility, of providing unlimited backhaul capacity for the massive number of SCs must be considered. In this regard, we adopt multiple-association where each HTCU is allowed to associate with multiple SCs. By doing so, we carefully split the targeted traffic among several backhaul links to mitigate the bottleneck forced by limited backhaul capacities. It is noteworthy that for coexisting MTCDs with the HTCUs, activating more SCs would allow more MTCDs to be supported without introducing additional ICI towards the HTCUs. Targeting different application, multiple-association can be also adopted to tackle computation-intensive applications of HTCUs. In particular, for applications such as augmented reality and environment recognition that require heavy computations, a task is split and partially offloaded to multiple SCs with integrated Edge Computing Servers (ECSs). Then, the task partitions are processed in parallel to reduce the end-to-end processing delay. Based on relative densities between HTCUs and SCs, we use tools from stochastic geometry to develop an offline adaptive task division technique that further reduces the average end-to-end processing delay per user. With the frequent serious data breaches experienced in recent years, securing data has become more of a business risk rather than an information technology (IT) issue. Hence, we exploit the dense number of SCs found in UDN along with Physical Layer Security (PLS) protocols to secure data transfer. In particular, we again adopt multiple-association and split the data of HTCUs into multiple streams originating from different SCs to prevent illegitimate receivers from eavesdropping. To support massive number of MTCDs, we deploy the Non-Orthogonal Multiple-Access (NOMA) technique. Using power NOMA, more than one device can be supported over the same frequency/time resource and their signals are distinguished at the receiver using Successive Interference Cancellation (SIC). In the same scope, exploiting the available resources in 5G and beyond networks, we investigate a mMTC scenario in an UDN operating in the Millimeter Wave (mmWave) band and supported by wireless backhauling. In doing so, we shed lights on the possible gains of utilizing the mmWave band where the severe penetration losses of mmWave can be exploited to mitigate the significant ICI in UDNs. Also, the vast bandwidth available in the mmWave band helps to allocate more Resource Blocks (RBs) per SCs which corresponds to supporting more MTCDs

Network Management, Optimization and Security with Machine Learning Applications in Wireless Networks

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, self-sufficient wireless sensor networks. We consider a WPCN with Non-Orthogonal Multiple Access (NOMA) and study two decoding schemes aiming for optimizing the performance with and without interference cancellation. This leads to solving convex and non-convex optimization problems. The second challenge (Network Management) is studied for cellular networks and handled using Machine Learning (ML). Two scenarios are considered. First, we target energy conservation. We propose an ML-based approach to turn Multiple Input Multiple Output (MIMO) technology on/off depending on certain criteria. Turning off MIMO can save considerable energy of the total site consumption. To control enabling and disabling MIMO, a Neural Network (NN) based approach is used. It learns some network features and decides whether the site can achieve satisfactory performance with MIMO off or not. In the second scenario, we take a deeper look into the cellular network aiming for more control over the network features. We propose a Reinforcement Learning-based approach to control three features of the network (relative CIOs, transmission power, and MIMO feature). The proposed approach delivers a stable state of the cellular network and enables the network to self-heal after any change or disturbance in the surroundings. In the third challenge (Cyber Security), we propose an NN-based approach with the target of detecting False Data Injection (FDI) in industrial data. FDI attacks corrupt sensor measurements to deceive the industrial platform. The proposed approach uses an Autoencoder (AE) for FDI detection. In addition, a Denoising AE (DAE) is used to clean the corrupted data for further processing

Multiuser non coherent massive MIMO schemes based on DPSK for future communication systems

The explosive usage of rich multimedia content in wireless devices has overloaded the communication networks. Moreover, the fifth generation (5G) of wireless communications involves new requirements in the radio access network (RAN) which require higher network capacities and new capabilities such as ultra-reliable and low-latency communication (URLLC), vehicular communications or augmented reality. All this has encouraged a remarkable spectrum crisis in the RF bands. A need for searching alternative techniques with more spectral efficiency to accommodate the needs of future emerging wireless communications is emerging. In this context, massive MIMO (m-MIMO) systems have been proposed as a promising solution for providing a substantial increase in the network capacity, becoming one of the key enabling technologies for 5G and beyond. m-MIMO provides high spectral- and energy-efficiency thanks to the deployment of a large number of antennas at the BS. However, we have to take into account that the current communication technologies are based on coherent transmission techniques so far, which require the transmission of a huge amount of signaling. This drawback is escalating with the excessive available number of antennas in m-MIMO. Therefore, the differential encoding and non coherent (NC) detection are an alternative solution to circumvent the drawbacks of m-MIMO in coherent systems. This Ph.D. Thesis is focused on signal processing techniques for NC detection in conjunction with m-MIMO, proposing new constellation designs and NC detection algorithms, where the information is transmitted in the signal differential phase. First, we design new constellation schemes for an uplink multiuser NC m-MIMO system in Rayleigh fading channels. These designs allow us to separate the users' signals at the receiver thanks to a one-to-one correspondence between the constellation for each user and the received joint constellation. Two approaches are considered in terms of BER: each user achieves a different performance and, on the other hand, the same performance is provided for all users. We analyze the number of antennas needed for those designs and compare to the required number by other designs in the literature. It is shown that our designs based on DPSK require a lower number of antennas than that required by their counterpart schemes based on energy. In addition, we compare the performance to their coherent counterpart systems, resulting NC-m-MIMO based on DPSK capable of outperforming the coherent systems with the suitable designs. Second, in order to reduce the number of antennas required for a target performance we propose a multi-user bit interleaved coded modulation - iterative decoding (BICM-ID) scheme as channel coding for a NC-m-MIMO system based on DPSK. We propose a novel NC approach for calculating EXIT curves based on the number of antennas. Then using the EXIT chart we find the best channel coding scheme for our NC-m-MIMO proposal. We show that the number of users served by the BS can be increased with a 70% reduction in the number of antennas with respect to the case without channel coding. In particular, we show that with 100 antennas for error protection equal design for all users and a coding rate of 1/2 we achieve the minimum probability of error. Third, we consider that current scenarios such as backhaul wireless systems, rural or suburban environments, and even new device-to-device (D2D) communications or the communications in higher frequencies (millimeter and the emerging ones in terahertz frequencies) can have a predominant line-of-sight (LOS) component, modeled by Rician fading. For all these new possible scenarios in 5G, we analyze the behavior of the NC m-MIMO systems when we have a Rician fading. We present a new constellation design to overcome the problem of the LOS channel component, as well as an associated detection algorithm to separate each user in reception taking into account the characterization of the constellation. In addition, for contemplating a more realistic scenario, we propose grouping users which experience a Rayleigh fading with those with Rician fading, analyzing the SINR and the performance of such combination in a multi-user NC m-MIMO system based on M-DPSK. The adequate user grouping allows unifying the constellation for both groups of users and the detection algorithm, reducing the complexity of the receiver. Also, the number of users that may be multiplexed may be further increased thanks to the improved performance. In the fourth part of this Thesis, we analyse the performance of multi-user NC m- MIMO based on DPSK in real environments and practical channels defined for the current standards such as LTE, the future technologies such as 5G and even for communications in the terahertz band. For this purpose, we use a metric to model the time-varying characteristics of the practical channels. We employ again the EXIT charts tool for analyzing and designing iteratively decoded systems. This analysis allows us to obtain an estimate of the degradation of the system's performance imposed by realistic channels. Hence, we show that our proposed system is robust to temporal variations, thus it is more recommendable the employment of NC-m-MIMO-DPSK in the future communication standards such as 5G. In order to reduce he number of hardware resources required in terms of RF chains, facilitating its implementation in a real system, we propose incorporating differential spatial modulation (DSM). We present and analyze a novel multiuser scheme for NC-m-MIMO combined with DSM with which we can see that the number of antennas is not a affected by the incorporation of DSM, even we have an improvement on the performance with respect to the coherent case. Finally, we study the viability of multiplexing users by constellation schemes against classical multiplexing techniques such as time division multiple access (TDMA). In order to fully characterize the system performance we analyze the block error rate (BLER) and the throughput of a NC-m-MIMO system. The results show a significant advantage regarding the number of antennas for multiplexing in the constellation against TDMA. However, in some cases, the demodulation of multiple users in constellation could require an excessively large number of antennas compared to TDMA. Therefore, it is necessary to properly manage the tradeoff between throughout and the number of antennas, to reach an optimal operational point, as shown in this Thesis.El inmenso uso de contenido multimedia en los dispositivos inalámbricos ha sobrecargado las redes de comunicaciones. Además, la quinta generación (5G) de sistemas de comunicaciones demanda nuevos requisitos para la red de acceso radio, la cual requiere ofrecer capacidades de red mayores y nuevas funcionalidades como comunicaciones ultra fiables y con muy poca letancia (URLLC), comunicaciones vehiculares o aplicaciones como la realidad aumentada. Todo esto ha propiciado una crisis notable en el espectro electromagnético, lo que ha llevado a una necesidad por buscar técnicas alternativas con más eficiencia espectral para acomodar todos los requisitos de las tecnologías de comunicaciones emergentes y futuras. En este contexto, los sistemas multi antena masivos, conocidos como massive MIMO, m-MIMO, han sido propuestos como una solución prometedora que proporciona un incremento substancial de la capacidad de red, convirtiéndose en una de las tecnologías claves para el 5G. Los sistemas m-MIMO elevan enormemente el número de antenas en la estación base, lo que les permite ofrecer alta eficiencia espectral y energética. No obstante, tenemos que tener en cuenta que las actuales tecnologías de comunicaciones emplean técnicas coherentes, las cuales requieren de información del estado del canal y por ello la transmisión de una enorme cantidad de información de señalización. Este inconveniente se ve agravado en el caso del m-MIMO debido al enorme número de antenas. Por ello, la codificación diferencial y la detección no coherente (NC) son una solución alternativa para solventar el problema de m-MIMO en los sistemas coherentes. Esta Tesis se centra en las técnicas de procesado de señal para detección NC junto con m-MIMO, proponiendo nuevos esquemas de constelación y algoritmos de detección NC, donde la información sea transmitida en la diferencia de fase de la señal. Primero, diseñamos nuevas constelaciones para un sistema multi usuario NC en m- MIMO en enlace ascendente (uplink) en canales con desvanecimiento tipo Rayleigh. Estos diseños nos permiten separar las señales de los usuarios en el receptor gracias a la correspondencia unívoca entre la constelación de cada usuario individual y la constelación conjunta recibida en la estación base. Hemos considerado dos enfoques para el diseño en términos de probabilidad de error: cada usuario consigue un rendimiento distinto, mientras que por otro lado, todos los usuarios son capaces de recibir las mismas prestaciones de probabilidad de error. Analizamos el número de antenas necesario para estos diseños y comparamos con el número requerido por otros diseños propuestos en la literatura. Nuestro diseño basado en DPSK requiere un número menor de antenas comparado con los sistemas basados en detección de energía. También comparamos con su homólogo coherente, resultando que NC-m-MIMO basado en DPSK es capaz de superar a los sistemas coherentes con los diseños adecuados. En segundo lugar, para reducir el número de antenas requerido para un rendimiento dado, proponemos incluir un esquema de codificación de canal. Hemos optado por un esquema de modulación codificado por bit entrelazado y decodificación iterativa (BICMID). Hemos empleado la herramienta EXIT chart para el diseño de la codificación de canal, proponiendo un nuevo enfoque para calcular las curvas EXIT de forma NC y basadas en el número de antenas. Los resultados muestran que el número de usuarios servidos por la estación base puede ser incrementado reduciendo un 70% el número de antenas con respecto al caso sin codificación de canal. En particular, para un array de 100 antenas y un diseño que ofrezca iguales prestaciones a todos los usuarios, con un código de tasa 1=2, podemos conseguir la mínima probabilidad de error. En tercer lugar, consideramos escenarios donde el canal tenga una componente predominante de visión directa (LOS) con la estación base modelada mediante un desvanecimiento tipo Rician. Por ejemplo, sistemas inalámbricos de backhaul, entornos rurales o sub urbanos, comunicaciones entre dispositivos (D2D), también cuando nos movemos hacia frecuencias superiores como son en la banda de milimétricas o más recientemente, la banda de terahercios para buscar mayores anchos de banda. Todos estos escenarios están contemplados en el futuro 5G. Los diseños presentados para canales Rayleigh ya no son válidos debido a la componente LOS del canal, por ello presentamos un nuevo diseño de constelación que resuelve el problema de la componente LOS, así como una guía para diseñar nuevas constelaciones. También proponemos un algoritmo asociado al diseñno de la constelación para poder separar a los usuarios en recepción. Además, para contemplar un escenario más realista donde podamos encontrar tanto desvanecimiento Rayleigh como Rice, proponemos agrupar usuarios de ambos grupos, analizando su rendimiento y relación señal a interferencia en la combinación. El adecuado agrupamiento permite unificar el diseño de la constelación para ambos desvanecimientos y por tanto reducir la complejidad en el receptor. También, el número de usuarios multiplicados en la constelación podría ser incrementado, gracias a la mejora en el rendimiento. El cuarto módulo de esta tesis es dedicado a analizar el rendimiento de los diseños propuestos en presencia de canales reales, donde disponemos de variabilidad temporal y en frecuencia. Proponemos usar una métrica que modela las características de la variabilidad temporal y, usando de nuevo la herramienta EXIT, analizamos los sistemas decodificados iterativamente considerando ahora los parámetros prácticos del canal. Este análisis nos permite obtener una estimación de la degradación que sufre el rendimiento del sistema impuesto por canales reales. Los resultados muestran que los sistemas NC-m-MIMO basados en DPSK son muy robustos a la variabilidad temporal por lo que son recomendables para los nuevos escenarios propuestos por el 5G, donde el canal cambia rápidamente. Otra consideración para introducir los sistemas NC con m-MIMO es la problemática de necesitar muchas cadenas de radio frecuencia que llevarían a tamaños de dispositivos enormes. Para reducir este número se propone la modulación espacial. En esta Tesis, estudiamos su uso con los sistemas NC, proponiendo una solución de modulación espacial diferencial para esquemas con múltiples usuarios combinado con NC-m-MIMO. Finalmente, estudiamos la viabilidad de multiplexar usuarios en la constelación frente a usar técnicas clásicas de multiplexación como TDMA. Para caracterizar completamente el rendimiento del sistema, analizamos la tasa de error de bloque (BLER) y el throughput de un sistema NC-m-MIMO. Los resultados muestran una ventaja significativa en cuanto al número de antennas para multiplexar usuarios en la constelación frente al requerido por TDMA. No obstante, en algunos casos, la demodulación de múltiples usuarios en la constelación podría requerir un número de antennas excesivamente grande comparado con la multiplexación en el tiempo. Por ello, es necesario gestionar adecuadamente un balance entre el throughput y el número de antenas para alcanzar un punto operacional óptimo, como se muestra en esta Tesis.Programa Oficial de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Ana Isabel Pérez Neira.- Secretario: Máximo Morales Céspedes.- Vocal: María del Carmen Aguayo Torre

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments