Communications over millimeter wave (mmWave) frequencies is a key component of the fifth generation (5G) cellular networks due to the large bandwidth available at mmWave bands. Thanks to the short wavelength of mmWave bands, large antenna arrays (32 to 256 elements are common) can be mounted at the transceivers. The array sizes are typical of a massive MIMO communication system, which makes fully digital beamforming difficult to implement due to high power consumption and hardware cost. This motivates the development of hybrid beamforming due to its versatile tradeoff between implementation cost (including hardware cost and power consumption) and system performance. However, due to the non-convex constraints on hardware (phase shifters), finding the global optima for hybrid beamforming design is often intractable. In this thesis, we focus on hybrid beamforming design for mmWave cellular communications both narrowband and wideband scenarios are considered. Starting from narrowband SU-MIMO mmWave communications, we propose a Gram-Schmidt orthogonalization (GSO) aided hybrid precoding algorithm to reduce computation complexity. GSO is a recursive process that depends on the order in which the matrix columns are selected. A heuristic solution to the order of column selection is suggested according to the array response vector along which the full digital precoder has the maximum projection. The proposed algorithm, not only constrained to uniform linear arrays (ULAs), can avoid the matrix inversion in designing the digital precoder compared to the orthogonal matching pursuit (OMP) algorithm. For the narrowband MU-MIMO mmWave communications, we propose an interference cancellation (IC) framework on hybrid beamforming design for downlink mmWave multi-user massive MIMO system. Based on the proposed framework, three successive interference cancellation (SIC) aided hybrid beamforming algorithms are proposed to deal with inter-user and intra-user interference. Furthermore, the optimal detection order of data streams is derived according to the post-detection signal-to-interference- plus-noise ratio (SINR). When considering wideband MU-MIMO mmWave communications, how to design a common RF beamformer across all subcarriers becomes the main challenge. Furthermore, the common RF beamformer in wideband channels leads to the need of more effective baseband schemes. By adopting a relaxation of the original mutual information and spectral efficiency maximization problems at the transceiver, we design the radio frequency (RF) precoder and combiner by leveraging the average of the covariance matrices of frequency domain channels, then a SIC aided baseband precoder and combiner are proposed to eliminate inter-user and intra-user interference / Graduate

This thesis is about the researching for 5th generation (5G) communication system, which focus on the improvement of 3D beamforming technology in the antenna array using in the Full Dimension Multiple-Input Multiple-Output (FD-MIMO) system and Millimeter-wave (mm-wave) system. When the 3D beamforming technology has been used in 5G communication system, the beam needs a weighting matrix to direct the beam to cover the UEs, but some compromises should be considered. If the narrow beams are used to transmit signals, then more energy is focused in the desired direction, but this has a restricted coverage area to a single or few User Equipments (UEs). If the BS covers multiple UEs, then multiple beams need to be steered towards more groups of UEs, but there is more interference between these beams from their side lobes when they are transmitted at same time. These challenges are waiting to be solved, which are about interference between each beam when the 3D beamforming technology is used. Therefore, there needs to be one method to decrease the generated interference between each beam through directing the side lobe beams and nulls to minimize interference in the 3D beamforming system. Simultaneously, energy needs to be directed towards the desired direction. If it has been decided that one beam should covera cluster of UEs, then there will be a range of received Signal to Interference plus Noise Ratio (SINR) depending on the location of the UEs relative to the direction of the main beam. If the beam is directed towards a group of UEs then there needs be a clustering method to cluster the UEs. In order to cover multiple UEs, an improved K-means clustering algorithm is used to cluster the multiple UEs into different groups, which is based on the cosine distance. Itcan decrease the number of beams when multiple UEs need be covered by multiple beams at same time. Moreover, a new method has been developed to calculate the weighting matrix for beamforming. It can adjust the values of weighting matrix according to the UEs' location and direct the main beam in a desired direction whilst minimizing its side lobes in other undesired directions. Then the minimum side lobe beamforming system only needs to know the UEs' location and can be used to estimate the Channel State Information (CSI) of UEs. Therefore, the scheme also shows lower complexity when compared to the beamforming methods with pre-coding. In order to test the improved K-means clustering algorithm and the new weighting method that can enhance the performance for 3D beamforming system, the two simulation systems are simulated to show the results such as 3D beamforming LTE system and mm-wave system.

Massive multiple-input multiple-output is a promising technique for the next generation of wireless communication systems which addresses most of the critical challenges associated with concurrent relaying systems, such as digital signal processing complexity, long processing delay, and low latency wireless communications. However, the deployment of conventional fully digital beamforming methods, dedicates one radio frequency (RF) chain to each antenna, is not viable enough due to the high fabrication/implementation cost and power consumption. In this thesis, we envision to address this critical issue by reducing the number of RF chains in a viable analog/digital configuration paradigm which is usually referred to hybrid structure. From another viewpoint, the development of fifth generation enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable, and this is the second key contribution of this thesis.

Millimeter wave (mmWave) spectrum above 30 GHz offers us an opportunity to pursue high-data-rate transmission using a channel bandwidth up to several gigahertz. To provide reliable link quality in mmWave frequency bands, hybrid analog-digital beamforming plays a crucial role in overcoming severe path loss and, meanwhile, satisfies the demand for low-power-consumption radio frequency (RF) devices. Implementing hybrid beamforming based on available channel state information (CSI) is a common solution in the hybrid beamforming literature. However, many reference methods underestimate the computational complexity of channel estimation for large antenna arrays or subsequent steps, such as the singular value decomposition of a channel matrix. To this end, we present a low-complexity scheme that exploits implicit channel knowledge to facilitate the design of hybrid beamforming for frequency-selective fading channels. We start from the study of channel estimation using the orthogonal matching pursuit (OMP) algorithm and realize that the problems of channel estimation and analog beam selection are equivalent if the candidates for analog beamforming vectors in the codebooks are mutually orthogonal. This implies that when orthogonal codebooks are employed, the observations used in channel estimation for large antenna arrays can be used to implement hybrid beamforming directly. The above-mentioned observations can be regarded as \textbf{implicit CSI}; they are coupling coefficients of all possible pairs of analog beamforming vectors on both sides of the channel. The idea of using implicit CSI to implement hybrid beamforming is further extended to the cases of non-orthogonal codebooks. Instead of calculating the mutual information between the transmitter and receiver, we focus on small-size coupling matrices between beam patterns selected by using appropriate key parameters as performance indicators. Therefore, the proposed hybrid beamforming method becomes much simpler: it amounts to collecting different sets of large-power coupling coefficients to construct multiple alternatives to an effective channel matrix. Then, the set yielding the largest Frobenius norm (or the largest absolute value of the determinant) of the effective channel provides the solution to the hybrid beamforming problem. The proposed hybrid beamforming approach clearly shows that the performance of hybrid beamforming is dominated by the quality of the coupling coefficients. Considering a fixed-length training sequence, we exploit mmWave channels' sparsity shown in the delay and angular domains to refine the quality of the coupling coefficients as well as to improve the hybrid beamforming performance.

The evolution to 5G and its use cases is driven by data-intensive applications requiring higher data rates over wireless channels. This has led to research in massive multiple input multiple output (MIMO) techniques and the use of the millimeter wave (mm wave) band. Because of the higher path loss at mm wave frequencies and the poor scattering nature of the mm wave channel (fewer paths exist), this thesis first proposes the use of the sphere decoding (SD) algorithm, and the semidefinite relaxation (SDR) detector to improve the performance of a uniform planar array (UPA) hybrid beamforming technique with large antenna arrays. The second contributions of this thesis consist of a low-complexity algorithm using the gradient descent for hybrid precoding and combining designs in mm wave systems. Also, in this thesis we present a low-complexity algorithm for hybrid precoding and combining designs that uses momentum gradient descent and Newton’s Method for mm wave systems which makes the objective function converge faster compared to other iterative methods in the literature; the two proposed low-complexity algorithms for hybrid precoding and combining do not depend on the antenna array geometry, unlike the orthogonal matching pursuit (OMP) hybrid precoding/combining approach. Moreover, these algorithms allow hybrid precoders/combiners to yield a performance very close to that of the optimal unconstrained digital precoders and combiners with a small number of iterations. Simulation results verify that the proposed hybrid precoding/combining scheme that uses momentum gradient descent and Newton’s Method outperforms previous methods that appear in the literature in terms of bit error rate (BER) and achievable spectral efficiency with lower complexity. Finally, an iterative algorithm that directly converts the hybrid precoding/combining in the full array (FA) architecture to subarray (SA) architecture is proposed and examined in this thesis. It is called direct conversion of iterative hybrid precoding/combining from FA to SA (DCIFS) hybrid precoding/combining. The proposed DCIFS design takes into consideration the matrix structure of the analog and baseband precoding and combining in the design derivation. Moreover, it does not depend on the antenna array geometry, unlike other techniques, such as the orthogonal matching pursuit (OMP) hybrid precoding/combining approach, nor does it assume any other constraints. Simulation results show that the proposed DCIFS hybrid design, when compared to the FA hybrid designs counterpart, can provide a spectral efficiency that is close to optimum while maintaining a very low complexity and better spectral efficiency than the conventional SA hybrid design with the same hardware complexity.

ARAÚJO, D. C. Channel estimation techniques applied to massive MIMO systems using sparsity and statistics approaches. 2016. 124 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2016. / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-06-21T13:52:26Z No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Approved for entry into archive by Marlene Sousa (mmarlene@ufc.br) on 2017-06-21T16:17:55Z (GMT) No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Made available in DSpace on 2017-06-21T16:17:55Z (GMT). No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) Previous issue date: 2016-09-29 / Massive MIMO has the potential of greatly increasing the system spectral efficiency by employing many individually steerable antenna elements at the base station (BS). This potential can only be achieved if the BS has sufficient channel state information (CSI) knowledge. The way of acquiring it depends on the duplexing mode employed by the communication system. Currently, frequency division duplexing (FDD) is the most used in the wireless communication system. However, the amount of overhead necessary to estimate the channel scales with the number of antennas which poses a big challenge in implementing massive MIMO systems with FDD protocol. To enable both operating together, this thesis tackles the channel estimation problem by proposing methods that exploit a compressed version of the massive MIMO channel. There are mainly two approaches used to achieve such a compression: sparsity and second order statistics. To derive sparsity-based techniques, this thesis uses a compressive sensing (CS) framework to extract a sparse-representation of the channel. This is investigated initially in a flat channel and afterwards in a frequency-selective one. In the former, we show that the Cramer-Rao lower bound (CRLB) for the problem is a function of pilot sequences that lead to a Grassmannian matrix. In the frequency-selective case, a novel estimator which combines CS and tensor analysis is derived. This new method uses the measurements obtained of the pilot subcarriers to estimate a sparse tensor channel representation. Assuming a Tucker3 model, the proposed solution maps the estimated sparse tensor to a full one which describes the spatial-frequency channel response. Furthermore, this thesis investigates the problem of updating the sparse basis that arises when the user is moving. In this study, an algorithm is proposed to track the arrival and departure directions using very few pilots. Besides the sparsity-based techniques, this thesis investigates the channel estimation performance using a statistical approach. In such a case, a new hybrid beamforming (HB) architecture is proposed to spatially multiplex the pilot sequences and to reduce the overhead. More specifically, the new solution creates a set of beams that is jointly calculated with the channel estimator and the pilot power allocation using the minimum mean square error (MMSE) criterion. We show that this provides enhanced performance for the estimation process in low signal-noise ratio (SNR) scenarios. / Pesquisas em sistemas MIMO massivo (do inglês multiple-input multiple-output) ganha- ram muita atenção da comunidade científica devido ao seu potencial em aumentar a eficiência espectral do sistema comunicações sem-fio utilizando centenas de elementos de antenas na estação de base (EB). Porém, tal potencial só poderá é obtido se a EB possuir suficiente informação do estado de canal. A maneira de adquiri-lo depende de como os recursos de comunicação tempo-frequência são empregados. Atualmente, a solução mais utilizada em sistemas de comunicação sem fio é a multiplexação por divisão na frequência (FDD) dos pilotos. Porém, o grande desafio em implementar esse tipo solução é porque a quantidade de tons pilotos exigidos para estimar o canal aumenta com o número de antenas. Isso resulta na perda do eficiência espectral prometido pelo sistema massivo. Esta tese apresenta métodos de estimação de canal que demandam uma quantidade de tons pilotos reduzida, mas mantendo alta precisão na estimação do canal. Esta redução de tons pilotos é obtida porque os estimadores propostos exploram a estrutura do canal para obter uma redução das dimensões do canal. Nesta tese, existem essencialmente duas abordagens utilizadas para alcançar tal redução de dimensionalidade: uma é através da esparsidade e a outra através das estatísticas de segunda ordem. Para derivar as soluções que exploram a esparsidade do canal, o estimador de canal é obtido usando a teoria de “compressive sensing” (CS) para extrair a representação esparsa do canal. A teoria é aplicada inicialmente ao problem de estimação de canais seletivos e não-seletivos em frequência. No primeiro caso, é mostrado que limitante de Cramer-Rao (CRLB) é definido como uma função das sequências pilotos que geram uma matriz Grassmaniana. No segundo caso, CS e a análise tensorial são combinado para derivar um novo algoritmo de estimatição baseado em decomposição tensorial esparsa para canais com seletividade em frequência. Usando o modelo Tucker3, a solução proposta mapeia o tensor esparso para um tensor cheio o qual descreve a resposta do canal no espaço e na frequência. Além disso, a tese investiga a otimização da base de representação esparsa propondo um método para estimar e corrigir as variações dos ângulos de chegada e de partida, causados pela mobilidade do usuário. Além das técnicas baseadas em esparsidade, esta tese investida aquelas que usam o conhecimento estatístico do canal. Neste caso, uma nova arquitetura de beamforming híbrido é proposta para realizar multiplexação das sequências pilotos. A nova solução consite em criar um conjunto de feixes, que são calculados conjuntamente com o estimator de canal e alocação de potência para os pilotos, usand o critério de minimização erro quadrático médio. É mostrado que esta solução reduz a sequencia pilot e mostra bom desempenho e cenários de baixa relação sinal ruído (SNR).

La densification des réseaux allant de pair avec le déploiement de petites cellules, les systèmes Massive MIMO disposent de caractéristiques prometteuses pour accroître la capacité des réseaux au travers des techniques de formation de faisceau, appelées beamforming. Les transmissions aux longueurs d’onde millimétriques (mmWave) sont, quant à elle, très convoitées car, non seulement les bandes passantes exploitables sont extrêmement larges, mais le canal de propagation est principalement Line-of-Sight (LOS), ce qui correspond à la visibilité directe entre le terminal et la station de base. L’attrait que peut avoir un système multi-utilisateurs Massive MIMO à de telles fréquences provient, en partie, du faible encombrement du réseau d’antennes, mais aussi du fort gain de beamforming dont il permet de bénéficier afin de contrecarrer les fortes pertes en espace libre que subissent les signaux à de telles longueurs d’onde. Dans un premier temps nous montrons comment l’augmentation de la fréquence porteuse impacte les performances de deux précodeurs connus. Au travers d’une modélisation déterministe et géométrique du canal, on simule un scénario Outdoor à faible mobilité et à forte densité de population en mettant en avant l’influence du trajet direct et des trajets réfléchis sur les performances. Plus précisément on prouve qu’en configuration purement LOS, le précodeur Zero-Forcing est beaucoup plus sensible à la structure du réseau d’antennes, et à la position des utilisateurs, que le Conjugate Beamforming (aussi connu sous le nom de retournement temporel). On introduit alors un précodeur basé uniquement sur la position angulaire des utilisateurs dans la cellule en référence à la station de base, puis l’on compare ses performances à celles des deux autres. La robustesse d’une telle implémentation à une erreur d’estimation d’angles est illustrée pour un scénario spécifique afin de souligner la pertinence des solutions angulaires, une direction étant plus facile à estimer et son évolution dans le temps plus prévisible.On décrit dans un second temps comment la connaissance des positions angulaires des utilisateurs permet d’accroître la capacité de la cellule par le biais d’un procédé d’allocation de puissance reposant sur une évaluation de l’interférence que chaque faisceau génère sur les autres. On prouve à l’aide de simulations que l’obtention de cette interférence, même exprimée sous une forme très simplifiée, permet d’améliorer très nettement la capacité totale de la cellule. Enfin, nous introduisons les systèmes Hybrides Numériques et Analogiques ayant récemment été proposés afin de permettre à une station de base de conserver un large nombre d’antennes, nécessaire à l’obtention d’un fort gain de beamforming, tout en réduisant le nombre de chaînes Radiofréquences (RF). On commence par décrire une solution permettant à un terminal de former un faisceau dont la direction s’adapte à sa propre inclinaison, en temps réel, pour toujours viser la station de base. On compare ensuite les performances de tels récepteurs, associés à des stations de base Massive MIMO, avec celles d’une solution hybride connue, le nombre de chaînes RF des deux systèmes étant identiques. Principalement, la flexibilité et la capacité d’évolution de ces systèmes est mise en avant, ces deux atouts étant particulièrement pertinents pour de nombreux environnements à forte densité de population. / As wireless communication networks are driven toward densification with small cell deployments, massive MIMO technology shows great promises to boost capacity through beamforming techniques. It is also well known that millimeter-Wave systems are going to be an important part of future dense network solutions because, not only do they offer high bandwidth, but channel is mostly Line-of-Sight (LOS). The attractiveness of using a multi-user Massive MIMO system at these frequencies comes partly from the reduced size of a many antenna base station, but also from the high beamforming gains they provide, which is highly suited to combat the high path losses experienced at such small wavelengths. First we show how raising the carrier frequency impacts the performance of some linear precoders widely used in Massive MIMO systems. By means of a geometrical deterministic channel model, we simulate a dense outdoor scenario and highlight the influence of the direct and multi-paths components. More importantly we prove that, in a Line-of-Sight (LOS) configuration, the discriminating skill of the well-known Zero Forcing precoder is much more sensitive to the antenna array structure and the user location than the Conjugate Beamforming precoder, also known as Time-Reversal. A precoder based on the knowledge of the angular position of all users is then introduced and compared to the other precoders based on channel response knowledge. Its robustness against angle estimation error is illustrated for a specific scenario and serves to back up the importance such a solution represents for future dense 5G networks, angular information being easier to estimate, and more so to keep track of.After that, we show how the knowledge of Directions of Arrival can be used to increase the sum capacity of a multi-user transmission through leakage based power allocation. This allocation uses an estimation of inter-user interference, referred to as Leakage, and we show through simulations how this factor, even under its most simplified form, improves realistic transmissions. Moreover this solution is not iterative and is extremely easy to implement which makes it particularly well suited for high deployment scenarios.Finally we introduce the Hybrid Analog and Digital Beamforming systems that have recently emerged to retain a high number of antennas without as many Radio Frequency (RF) chains, in order to keep high beamforming gains while lowering the complexity of conceiving many antenna base stations. We first describe a user equipment solution allowing the system to form a beam that adapts to its own movement so that it always focuses its energy toward the base station, using an on-board analog array and an Inertial Measurement Unit. Then we compare the performance of a known Hybrid solution with a fully digital Massive MIMO system, having as many RF chains as the Hybrid system, but serving user equipments with beamforming abilities. Mostly we emphasize how such a system allows for great flexibility and evolution, both traits being invaluable features in many future networks.

Future 6G wireless communications network will increase the data capacity to unprecedented numbers and thus empower the deployment of new real-time applications. Millimeter-Wave (mmWave) band and Massive MIMO are considered as two of the main pillars of 6G to handle the gigantic influx in data traffic and number of mobile users and IoT devices. The small wavelengths at these frequencies mean that more antenna elements can be placed in the same area. Thereby, high spatial processing gains are achievable that can theoretically compensate for the higher isotropic path loss. The propagation characteristics at mmWave band, create sparse channels in typical scenarios, where only few paths convey significant power. Considering this feature, Hybrid (analog-digital) Beamforming introduces a new signal processing framework which enables energy and cost-efficient implementation of massive MIMO with innovative smart arrays. In this setup, the analog beamalignment via beam selection in link access phase, is the critical performance limiting step. Considering the variable operating condition in mmWave channels, a desirable solution should have the following features: efficiency in training (limited coherence time, delay constraints), adaptivity to channel conditions (large SNR range) and robustness to realized channels (LOS, NLOS, Multipath, non-ideal beam patterns). For the link access task, we present a new energy-detection framework based on variable length channel measurements with (orthogonal) beam codebooks. The proposed beam selection technique denoted as composite M-ary Sequential Competition Test (SCT) solves the beam selection problem when knowledge about the SNR operating point is not available. It adaptively changes the test length when the SNR varies to achieve an essentially constant performance level. In addition, it is robust to non-ideal beam patterns and different types of the realized channel. Compared to the conventional fixed length energy-detection techniques, the SCT can increase the training efficiency up to two times while reducing the delay if the channel condition is good. Having the flexibility to allocate resources for channel measurements through different beams adaptively in time, we improve the SCT to eliminate unpromising beams from the remaining candidate set as soon as possible. In this way, the Sequential Competition and Elimination Test (SCET) significantly further reduces training time by increasing the efficiency. The developed ideas can be applied with different codebook types considered for practical applications. The reliable performance of the beam selection technique is evident through experimental evaluation done using the state-of-the-art test-bed developed at the Vodafone Chair that combines a Universal Software Radio Peripheral (USRP) based platform with mmWave frontends.

A new communication paradigm is foreseen for beyond 2020 society, due to the emergence of new broadband services and the Internet of Things era. The set of requirements imposed by these new applications is large and diverse, aiming to provide a ubiquitous broadband connectivity. Research community has been working in the last decade towards the definition of the 5G mobile wireless networks that will provide the proper mechanisms to reach these challenging requirements. In this framework, three key research directions have been identified for the improvement of capacity in 5G: the increase of the spectral efficiency by means of, for example, the use of massive MIMO technology, the use of larger amounts of spectrum by utilizing the millimeter wave band, and the network densification by deploying more base stations per unit area. This dissertation addresses densification as the main enabler for the broadband and massive connectivity required in future 5G networks. To this aim, this Thesis focuses on the study of the UDN. In particular, a set of technology enablers that can lead UDN to achieve their maximum efficiency and performance are investigated, namely, the use of higher frequency bands for the benefit of larger bandwidths, the use of massive MIMO with distributed antenna systems, and the use of distributed radio resource management techniques for the inter-cell interference coordination. Firstly, this Thesis analyzes whether there exists a fundamental performance limit related with densification in cellular networks. To this end, the UDN performance is evaluated by means of an analytical model consisting of a 1-dimensional network deployment with equally spaced BS. The inter-BS distance is decreased until reaching the limit of densification when this distance approaches 0. The achievable rates in networks with different inter-BS distances are analyzed for several levels of transmission power availability, and for various types of cooperation among cells. Moreover, UDN performance is studied in conjunction with the use of a massive number of antennas and larger amounts of spectrum. In particular, the performance of hybrid beamforming and precoding MIMO schemes are assessed in both indoor and outdoor scenarios with multiple cells and users, working in the mmW frequency band. On the one hand, beamforming schemes using the full-connected hybrid architecture are analyzed in BS with limited number of RF chains, identifying the strengths and weaknesses of these schemes in a dense-urban scenario. On the other hand, the performance of different indoor deployment strategies using HP in the mmW band is evaluated, focusing on the use of DAS. More specifically, a DHP suitable for DAS is proposed, comparing its performance with that of HP in other indoor deployment strategies. Lastly, the presence of practical limitations and hardware impairments in the use of hybrid architectures is also investigated. Finally, the investigation of UDN is completed with the study of their main limitation, which is the increasing inter-cell interference in the network. In order to tackle this problem, an eICIC scheduling algorithm based on resource partitioning techniques is proposed. Its performance is evaluated and compared to other scheduling algorithms under several degrees of network densification. After the completion of this study, the potential of UDN to reach the capacity requirements of 5G networks is confirmed. Nevertheless, without the use of larger portions of spectrum, a proper interference management and the use of a massive number of antennas, densification could turn into a serious problem for mobile operators. Performance evaluation results show large system capacity gains with the use of massive MIMO techniques in UDN, and even greater when the antennas are distributed. Furthermore, the application of ICIC techniques reveals that, besides the increase in system capacity, it brings significant energy savings to UDNs. / A partir del año 2020 se prevé que un nuevo paradigma de comunicación surja en la sociedad, debido a la aparición de nuevos servicios y la era del Internet de las cosas. El conjunto de requisitos impuesto por estas nuevas aplicaciones es muy amplio y diverso, y tiene como principal objetivo proporcionar conectividad de banda ancha y universal. En las últimas décadas, la comunidad científica ha estado trabajando en la definición de la 5G de redes móviles que brindará los mecanismos necesarios para garantizar estos requisitos. En este marco, se han identificado tres mecanismos clave para conseguir el necesario incremento de capacidad de la red: el aumento de la eficiencia espectral a través de, por ejemplo, el uso de tecnologías MIMO masivas, la utilización de mayores porciones del espectro en frecuencia y la densificación de la red mediante el despliegue de más estaciones base por área. Esta Tesis doctoral aborda la densificación como el principal mecanismo que permitirá la conectividad de banda ancha y universal requerida en la 5G, centrándose en el estudio de las Redes Ultra Densas o UDNs. En concreto, se analiza el conjunto de tecnologías habilitantes que pueden llevar a las UDNs a obtener su máxima eficiencia y prestaciones, incluyendo el uso de altas frecuencias para el aprovechamiento de mayores anchos de banda, la utilización de MIMO masivo con sistemas de antenas distribuidas y el uso de técnicas de reparto de recursos distribuidas para la coordinación de interferencias. En primer lugar, se analiza si existe un límite fundamental en la mejora de las prestaciones en relación a la densificación. Con este fin, las prestaciones de las UDNs se evalúan utilizando un modelo analítico de red unidimensional con BSs equiespaciadas, en el que la distancia entre BSs se disminuye hasta alcanzar el límite de densificación cuando ésta se aproxima a 0. Las tasas alcanzables en redes con distintas distancias entre BSs son analizadas, considerando distintos niveles de potencia disponible en la red y varios grados de cooperación entre celdas. Además, el comportamiento de las UDNs se estudia junto al uso masivo de antenas y la utilización de anchos de banda mayores. Más concretamente, las prestaciones de ciertas técnicas híbridas MIMO de precodificación y beamforming se examinan en la banda milimétrica. Por una parte, se analizan esquemas de beamforming en BSs con arquitectura híbrida en función de la disponibilidad de cadenas de radiofrecuencia en escenarios exteriores. Por otra parte, se evalúan las prestaciones de ciertos esquemas de precodificación híbrida en escenarios interiores, utilizando distintos despliegues y centrando la atención en los sistemas de antenas distribuidos o DAS. Además, se propone un algoritmo de precodificación híbrida específico para DAS, y se evalúan y comparan sus prestaciones con las de otros algoritmos de precodificación utilizados. Por último, se investiga el impacto en las prestaciones de ciertas limitaciones prácticas y deficiencias introducidas por el uso de dispositivos no ideales. Finalmente, el estudio de las UDNs se completa con el análisis de su principal limitación, el nivel creciente de interferencia en la red. Para ello, se propone un algoritmo de control de interferencias basado en la partición de recursos. Sus prestaciones son evaluadas y comparadas con las de otras técnicas de asignación de recursos. Tras este estudio, se puede afirmar que las UDNs tienen gran potencial para la consecución de los requisitos de la 5G. Sin embargo, sin el uso conjunto de mayores porciones del espectro, adecuadas técnicas de control de la interferencia y el uso masivo de antenas, las UDNs pueden convertirse en serios obstáculos para los operadores móviles. Los resultados de la evaluación de prestaciones de estas tecnologías confirman el gran aumento de la capacidad de las redes mediante el uso masivo de antenas y la introducción de mecanismos de I / A partir de l'any 2020 es preveu un nou paradigma de comunicació en la societat, degut a l'aparició de nous serveis i la era de la Internet de les coses. El conjunt de requeriments imposat per aquestes noves aplicacions és ampli i divers, i té com a principal objectiu proporcionar connectivitat universal i de banda ampla. En les últimes dècades, la comunitat científica ha estat treballant en la definició de la 5G, que proveirà els mecanismes necessaris per a garantir aquests exigents requeriments. En aquest marc, s'han identificat tres mecanismes claus per a aconseguir l'increment necessari en la capacitat: l'augment de l'eficiència espectral a través de, per exemple, l'ús de tecnologies MIMO massives, la utilització de majors porcions de l'espectre i la densificació mitjançant el desplegament de més estacions base per àrea. Aquesta Tesi aborda la densificació com a principal mecanisme que permetrà la connectivitat de banda ampla i universal requerida en la 5G, centrant-se en l' estudi de les xarxes ultra denses (UDNs). Concretament, el conjunt de tecnologies que poden dur a les UDNs a la seua màxima eficiència i prestacions és analitzat, incloent l'ús d'altes freqüències per a l'aprofitament de majors amplàries de banda, la utilització de MIMO massiu amb sistemes d'antenes distribuïdes i l'ús de tècniques distribuïdes de repartiment de recursos per a la coordinació de la interferència. En primer lloc, aquesta Tesi analitza si existeix un límit fonamental en les prestacions en relació a la densificació. Per això, les prestacions de les UDNs s'avaluen utilitzant un model analític unidimensional amb estacions base equidistants, en les quals la distància entre estacions base es redueix fins assolir el límit de densificació quan aquesta distància s'aproxima a 0. Les taxes assolibles en xarxes amb diferents distàncies entre estacions base s'analitzen considerant diferents nivells de potència i varis graus de cooperació entre cel·les. A més, el comportament de les UDNs s'estudia conjuntament amb l'ús massiu d'antenes i la utilització de majors amplàries de banda. Més concretament, les prestacions de certes tècniques híbrides MIMO de precodificació i beamforming s'examinen en la banda mil·limètrica. D'una banda, els esquemes de beamforming aplicats a estacions base amb arquitectures híbrides és analitzat amb disponibilitat limitada de cadenes de radiofreqüència a un escenari urbà dens. D'altra banda, s'avaluen les prestacions de certs esquemes de precodificació híbrida en escenaris d'interior, utilitzant diferents estratègies de desplegament i centrant l'atenció en els sistemes d' antenes distribuïdes (DAS). A més, es proposa un algoritme de precodificació híbrida distribuïda per a DAS, i s'avaluen i comparen les seues prestacions amb les de altres algoritmes. Per últim, s'investiga l'impacte de les limitacions pràctiques i altres deficiències introduïdes per l'ús de dispositius no ideals en les prestacions de tots els esquemes anteriors. Finalment, l' estudi de les UDNs es completa amb l'anàlisi de la seua principal limitació, el nivell creixent d'interferència entre cel·les. Per tractar aquest problema, es proposa un algoritme de control d'interferències basat en la partició de recursos. Les prestacions de l'algoritme proposat s'avaluen i comparen amb les d'altres tècniques d'assignació de recursos. Una vegada completat aquest estudi, es pot afirmar que les UDNs tenen un gran potencial per aconseguir els ambiciosos requeriments plantejats per a la 5G. Tanmateix, sense l'ús conjunt de majors amplàries de banda, apropiades tècniques de control de la interferència i l'ús massiu d'antenes, les UDNs poden convertir-se en seriosos obstacles per als operadors mòbils. Els resultats de l'avaluació de prestacions d' aquestes tecnologies confirmen el gran augment de la capacitat de les xarxes obtingut mitjançant l'ús massiu d'antenes i la introducci / Giménez Colás, S. (2017). Ultra Dense Networks Deployment for beyond 2020 Technologies [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86204 / TESIS

This thesis exploits index modulation techniques to design energy- and spectrum-efficient system models to operate in future wireless networks. In this respect, index modulation techniques are studied considering two different media: mapping the information onto the frequency indices of multicarrier systems, and onto the antenna array indices of a platform that comprises multiple antennas. The index modulation techniques in wideband communication scenarios considering orthogonal and generalized frequency division multiplexing systems are studied first. Single cell multiuser networks are considered while developing the system models that exploit the index modulation on the subcarriers of the multicarrier systems. Instead of actively modulating all the subcarriers, a subset is selected according to the index modulation bits. As a result, there are subcarriers that remain idle during the data transmission phase and the activation pattern of the subcarriers convey additional information. The transceivers for the orthogonal and generalized frequency division multiplexing systems with index modulation are both designed considering the uplink and downlink transmission phases with a linear combiner and precoder in order to reduce the system complexity. In the developed system models, channel state information is required only at the base station. The linear combiner is designed adopting minimum mean square error method to mitigate the inter-user-interference. The proposed system models offer a flexible design as the parameters are independent of each other. The parameters can be adjusted to design the system in favor of the energy efficiency, spectrum efficiency, peak-to-average power ratio, or error performance. Then, the index modulation techniques are studied for large-scale multiple-input multiple-output systems that operate in millimeter wave bands. In order to overcome the drawbacks of transmission in millimeter wave frequencies, channel properties should be taken in to account while envisaging the wireless communication network. The large-scale multiple-input multiple-output systems increase the degrees of freedom in the spatial domain. This feature can be exploited to focus the transmit power directly onto the intended receiver terminal to cope with the severe path-loss. However, scaling up the number of hardware elements results in excessive power consumption. Hybrid architectures provide a remedy by shifting a part of the signal processing to the analog domain. In this way, the number of bulky and high power consuming hardware elements can be reduced. However, there will be a performance degradation as a consequence of renouncing the fully digital signal processing. Index modulation techniques can be combined with the hybrid system architecture to compensate the loss in spectrum efficiency to further increase the data rates. A user terminal architecture is designed that employs analog beamforming together with spatial modulation where a part of the information bits is mapped onto the indices of the antenna arrays. The system is comprised a switching stage that allocates the user terminal antennas on the phase shifter groups to minimize the spatial correlation, and a phase shifting stage that maximizes the beamforming gain to combat the path-loss. A computationally efficient optimization algorithm is developed to configure the system. The flexibility of the architecture enables optimization of the hybrid transceiver at any signal-to-noise ratio values. A base station is designed in which hybrid beamforming together with spatial modulation is employed. The analog beamformer is designed to point the transmit beam only in the direction of the intended user terminal to mitigate leakage of the transmit power to other directions. The analog beamformer to transmit the signal is chosen based on the spatial modulation bits. The digital precoder is designed to eliminate the inter-user-interference by exploiting the zero-forcing method. The base station computes the hybrid beamformers and the digital combiners, and only feeds back the digital combiners of each antenna array-user pair to the related user terminals. Thus, a low complexity user architecture is sufficient to achieve a higher performance. The developed optimization framework for the energy efficiency jointly optimizes the number of served users and the total transmit power by utilizing the derived upper bound of the achievable rate. The proposed transceiver architectures provide a more energy-efficient system model compared to the hybrid systems in which the spatial modulation technique is not exploited. This thesis develops low-complexity system models that operate in narrowband and wideband channel environments to meet the energy and spectrum efficiency demands of future wireless networks. It is corroborated in the thesis that adopting index modulation techniques both in the systems improves the system performance in various aspects.:1 Introduction 1 1.1 Motivation 1 1.2 Overview and Contribution 2 1.3 Outline 9 2 Preliminaries and Fundamentals 13 2.1 Multicarrier Systems 13 2.2 Large-scale Multiple Input Multiple Output Systems 17 2.3 Index Modulation Techniques 19 2.4 Single Cell Multiuser Networks 22 3 Multicarrier Systems with Index Modulation 27 3.1 Orthogonal Frequency Division Multiplexing 28 3.2 Generalized Frequency Division Multiplexing 40 3.3 Summary 52 4 Hybrid Beamforming with Spatial Modulation 55 4.1 Uplink Transmission 56 4.2 Downlink Transmission 74 4.3 Summary 106 5 Conclusion and Outlook 109 5.1 Conclusion 109 5.2 Outlook 111 A Quantization Error Derivations 113 B On the Achievable Rate of Gaussian Mixtures 115 B.1 The Conditional Density Function 115 B.2 Tight Bounds on the Differential Entropy 116 B.3 A Bound on the Achievable Rate 118 C Multiuser MIMO Downlink without Spatial Modulation 121 Bibliography