Les réseaux de cinquième génération sont en cours de définition et leurs différentes composantes commencent à émerger: nouvelles technologies d'accès à la radio, convergence fixe et mobile des réseaux et virtualization.Le contrôle et la gestion de bout en bout (E2E) du réseau ont une importance particulière pour les performances du réseau. Cela étant, nous segmentons le travail de thèse en deux parties: le réseau d’accès radio (RAN) axé sur la technologie MIMO Massif (M-MIMO) et la connexion E2E du point de vue de la couche transport.Dans la première partie, nous considérons la formation de faisceaux focalisés avec un structure hiérarchique dans les réseaux sans fil. Pour un ensemble de flots donnée, nous proposons des algorithmes efficaces en terme de complexité pour une allocation avec alpha-équité. Nous proposons ensuite des formules exactes pour la performance au niveau du flot, à la fois pour le trafic élastique (avec une équité proportionnelle et équité max-min) et le trafic en continu. Nous validons les résultats analytiques par des simulations.La seconde partie de la thèse vise à développer une fonction de réseau auto-organisant (SON) qui améliore la qualité d'expérience (QoE) des connexions en bout-en-bout. Nous considérons un service de type vidéo streaming et développons une fonctionnalité SON qui adapte la QoE de bout-en-bout entre le serveur vidéo et l'utilisateur. La mémoire-tampon reçoit les données d'un serveur avec une connexion E2E en suivant le protocole TCP. Nous proposons un modèle qui décrit ce comportement et nous comparons les formules analytiques obtenues avec les simulations. Enfin, nous proposons un SON qui donne la qualité vidéo de sorte que la probabilité de famine soit égale à une valeur cible fixée au préalable. / Fifth generation networks are being defined and their different components are beginning to emerge: new technologies for access to radio, fixed and mobile convergence of networks and virtualization.End-to-end (E2E) control and management of the network have a particular importance for network performance. Having this in mind, we segment the work of the thesis in two parts: the radio access network (RAN) with a focus on Massive MIMO (M-MIMO) technology and the E2E connection from a point of view of the transport layer.In the first part, we consider hierarchical beamforming in wireless networks. For a given population of flows, we propose computationally efficient algorithms for fair rate allocation. We next propose closed-form formulas for flow level performance, for both elastic (with either proportional fairness and max-min fairness) and streaming traffic. We further assess the performance of hierarchical beamforming using numerical experiments.In the second part, we identify an application of SON namely the control of the starvation probability of video streaming service. The buffer receives data from a server with an E2E connection following the TCP protocol. We propose a model that describes the behavior of a buffer content and we compare the analytical formulas obtained with simulations. Finally, we propose a SON function that by adjusting the application video rate, achieves a target starvation probability.

In centralized radio access network (C-RAN) architecture, the base-band unit (BBU) is connected to one or more remote radio units (RRUs) via a fronthaul (FH) interface. Upgrading base station antennas in C-RAN to support massive multiple-input multiple-output (MIMO) technology can improve network spectral efficiency and largely boost the capacity of the 5G system. Those great benefits also introduce new challenges to the FH interface since the required FH capacity increases proportionally to the number of transceiver units (TXRUs) for traditional receiver processing at the BBU. To reduce the FH link load, different base-band splitting options between RRUs and BBU are considered in practical C-RAN networks. In this project, we investigate three beamforming algorithms (MRC, DFT and Enhanced) which are expected to reduce the number of streams on FH link, and evaluate their performance for single-user MIMO in different mobility scenarios via system-level simulations. The results show that we successfully reach the goal of reducing the number of streams to one-fourth the number of TXRUs meanwhile maintaining relatively good performance. Additionally, we observe that the Enhanced algorithm performs the best in majority of scenarios. / I en centraliserad nätverksarkitektur för radioåtkomst är basbandsenheten ansluten till en eller flera fjärrradionheter via ett fronthaul-gränssnitt. Genom att uppgradera basstationsantennerna i C-RAN för att stödja massiv multipel input-multipel output-teknik kan man förbättra nätverkets spektraleffektivitet och till stor del öka kapaciteten i 5G-systemet. Dessa stora fördelar medför också nya utmaningar för FH-gränssnittet eftersom den nödvändiga FH-kapaciteten ökar proportionellt mot antalet sändare för traditionell mottagarbearbetning vid BBU. För att minska belastningen på FH-länken övervägs olika alternativ för uppdelning av basbandet mellan RRUs och BBU i praktiska C-RAN-nät. I det här projektet undersöker vi tre strålformningsalgoritmer (MRC, DFT och Enhanced) som förväntas minska antalet strömmar på FH-länken och utvärderar deras prestanda för single-user MIMO i olika mobilitetsscenarier med hjälp av simuleringar på systemnivå. Resultaten visar att vi lyckas uppnå målet att minska antalet strömmar till en fjärdedel av antalet TXRU:s samtidigt som vi behåller en relativt god prestanda. Dessutom kan vi konstatera att den förbättrade algoritmen presterar bäst i de flesta scenarier.

The next generation of mobile networks (5G) is currently being standardized, and massive MIMO (Multiple-Input-Multiple-Output) is a strong candidate to be part of this standard. Other than providing higher data rates and lower latency, high accuracy positioning is also required. In this thesis, we evaluate the achievable performance of positioning using massive MIMO systems in open highway scenarios. Relevant theory from sensor array signal processing and Bayesian filtering is presented, and is used in a simulation environment on large antenna arrays representing massive MIMO base stations. Positioning is done by utilizing the uplink pilot reference signals, where the Direction of Arrival (DOA) of the pilot signal is estimated, and then used for position estimation. Estimation of the DOA is done by both a maximum-likelihood method and by using an Extended Kalman Filter (EKF). A positioning error of less than 8 m is achieved with absolute certainty when the vehicle is less than 300 m from the base station. It is also concluded that this result could be improved by using more sophisticated filtering algorithms.

Future wireless networks are evolving to become ever more heterogeneous, including small cells such as picocells and femtocells, and direct device-to-device (D2D) communication that bypasses base stations (BSs) altogether to share stored and personalized content. Conventional user association schemes are unsuitable for heterogeneous networks (HetNets), due to the massive disparities in transmit power and capabilities of different BSs. To make the most of the new low-power infrastructure and D2D communication, it is desirable to facilitate and encourage users to be offloaded from the macro BSs. This dissertation characterizes the gain in network performance (e.g., the rate distribution) from offloading users to small cells and the D2D network, and develops efficient user association, resource allocation, and interference management schemes aiming to achieve the performance gain. First, we optimize the load-aware user association in HetNets with single-antenna BSs, which bridges the gap between the optimal solution and a simple small cell biasing approach. We then develop a low-complexity distributed algorithm that converges to a near-optimal solution with a theoretical performance guarantee. Simulation results show that the biasing approach loses surprisingly little with appropriate bias factors, and there is a large rate gain for cell-edge users. This framework is then extended to a joint optimization of user association and resource blanking at the macro BSs – similar to the enhanced intercell interference coordination (eICIC) proposed in the global cellular standards, 3rd Generation Partnership Project (3GPP). Though the joint problem is nominally combinatorial, by allowing users to associate to multiple BSs, the problem becomes convex. We show both theoretically and through simulation that the optimal solution of the relaxed problem still results in a mostly unique association. Simulation shows that resource blanking can further improve the network performance. Next, the above framework with single-antenna transmission is extended to HetNets with BSs equipped with large-antenna arrays and operating in the massive MIMO regime. MIMO techniques enable the option of another interference management: serving users simultaneously by multiple BSs – termed joint transmission (JT). This chapter formulates a unified utility maximization problem to optimize user association with JT and resource blanking, exploring which an efficient dual subgradient based algorithm approaching optimal solutions is developed. Moreover, a simple scheduling scheme is developed to implement near-optimal solutions. We then change direction slightly to develop a flexible and tractable framework for D2D communication in the context of a cellular network. The model is applied to study both shared and orthogonal resource allocation between D2D and cellular networks. Analytical SINR distributions and average rates are derived and applied to maximize the total throughput, under an assumption of interference randomization via time and/or frequency hopping, which can be viewed as an optimized lower bound to other more sophisticated scheduling schemes. Finally, motivated by the benefits of cochannel D2D links, this dissertation investigates interference management for D2D links sharing cellular uplink resources. Showing that the problem of maximizing network throughput while guaranteeing the service of cellular users is non-convex and hence intractable, a distributed approach that is computationally efficient with minimal coordination is proposed instead. The key algorithmic idea is a pricing mechanism, whereby BSs optimize and transmit a signal depending on the interference to D2D links, who then play a best response (i.e., selfishly) to this signal. Numerical results show that our algorithms converge quickly, have low overhead, and achieve a significant throughput gain, while maintaining the quality of cellular links at a predefined service level. / text

The use of multiple antennas to improve the reliability and capacity of wireless communication has been around for a while, leading to the concept of multiple-input multiple-output (MIMO) communications. To enable full MIMO potentials, the precoding design has been recognized as a crucial component. This thesis aims to design multiuser MIMO precoders of practical interest to achieve high reliability and capacity performance under various real-world constraints like inaccuracy of channel information acquired at the transmitter, hardware complexity, etc. Three prominent cases are considered which constitute the mainstream evolving directions of the current cellular communication standards and future 5G cellular communications. First, in a relay-assisted multiuser MIMO system, heavily quantized channel information obtained through limited feedback contributes to noticeable rate loss compared to when perfect channel information is available. This thesis derives an upper bound to characterize the system throughput loss caused by channel quantization error, and then develops a feedback quality control strategy to maintain the rate loss within a bounded range. Second, in a massive multiuser MIMO channel, due to the large array size, it is difficult to support each antenna with a dedicated radio frequency chain, thus making high-dimensional baseband precoding infeasible. To address this challenge, a low-complexity hybrid precoding scheme is designed to divide the precoding into two cascaded stages, namely, the low-dimensional baseband precoding and the high-dimensional phase-only processing at the radio frequency domain. Its performance is characterized in a closed form and demonstrated through computer simulations. Third, in a mmWave multiuser MIMO scenario, smaller wavelengths make it possible to incorporate excessive amounts of antenna elements into a compact form. However, we are faced with even worse hardware challenges as mixed signal processing at mmWave frequencies is more complex and power consuming. The channel sparsity is taken advantage of in this thesis to enable a simplified precoding scheme to steer the beam for each user towards its dominant propagation paths at the radio frequency domain only. The proposed scheme comes at significantly reduced complexity and is shown to be capable of achieving highly desirable performance based on asymptotic rate analysis. / Graduate

The fifth generation (5G) wireless communications technology will be a paradigm shift which does not only provide an explosive increment on the achievable data rate per cell, but also ideally decreases the costs and energy consumption per data link. The engineering requirements of 5G standard can be intuitively interpreted as highly enhanced spectral efficiency and energy efficiency. This thesis focuses on the practical implementation issues of the massive multiple-input multiple-output (MIMO) and energy harvesting systems. To begin with, massive MIMO, as one of the key technologies of 5G systems, can provide enormous enhancement in spectral efficiency. For a practical massive MIMO system, hybrid processing (precoding/combining), by restricting the number of RF chains to far less than the number of antenna elements, can significantly reduce the implementation cost compared to the full-complexity radio frequency (RF) chain configuration. This thesis designs the hybrid RF and baseband precoders/combiners for multi-stream transmission in the point-to-point (P2P) massive MIMO systems, by directly decomposing the pre-designed digital precoder/combiner of a large dimension. The performance of the matrix decomposition based hybrid processing (MD-HP) scheme is near-optimal compared to the singular value decomposition (SVD) based full-complexity processing. In addition, the downlink communication of a massive multiuser MIMO (MU-MIMO) system is also investigated, and a low-complexity hybrid block diagonalization (Hy-BD) scheme is developed to approach the performance of the traditional BD method. We aim to harvest the large array gain through the phase-only RF precoding and combining and then BD processing is performed on the equivalent baseband channel in the massive MU-MIMO scenario. The MD-HP and Hy-BD schemes are examined in both the large Rayleigh fading channels and millimeter wave channels. On the other hand, energy harvesting is an increasingly attractive and renewable source of power for wireless communications devices, which contributes to the enhancement of the system energy efficiency. This thesis also designs the energy cooperation assisted energy harvesting communication between a practical transmitter and receiver, whose hardware circuits consume non-zero power when active. The energy cooperation save-then-transmit (EC-ST) scheme aims to obtain the optimal active time ratio and energy cooperation power for the maximum throughput under additive white Gaussian channels and the minimum outage probability under block Rayleigh fading channels. / Graduate

This project consists of analyzing and finding solutions to the effect of non-linear distortionon the performance of a Massive Multiple Input Multiple Output (MIMO) system interms of Spectral Efficiency (SE) and Symbol Error Rate (SER). Massive MIMO is one ofthe technologies that are considered the backbone of the 5th generation of wireless communicationsand therefore this technology has gathered much interest from researchersand companies alike [19], as it is proven that this kind of system greatly improves thecapacity of the wireless connection [8]. Since Massive MIMO is still a relatively newtechnology and it is yet to be implemented for commercial use, there are several challengesthat arise when trying to implement such a system. One of these problems arisefrom the fact that the Power Amplifiers (PAs) in the transmitters of Massive MIMO systemsare non-linear and thus impose a distortion on the transmitted signals of the system[12]. The thesis aims to study this non-linear effect on the performance of massive MIMOsystems by first modelling the distortion effect on the transmitted signals using two differentnon-linear models. Moreover, closed-form expressions for one of the models areformed to facilitate the simulation of the non-linear model and facilitate the analysis ofthe distortion effect on the performance metrics. Then the established system model issimulated and based on the results, the effect of each of the power amplifier non-lineardistortion models on the performance metrics of the Massive MIMO system is studied.Furthermore, based on the analysis of the simulation results, a compensation mechanismis introduced to the Massive MIMO system in order to mitigate the distortion effect onthe system performance in terms of SER and SE.

Recently, massive multiple-input multiple-output (MIMO) systems have gained significant attention as a new network architecture to not only achieving unprecedented spectral and energy efficiencies, but also to alleviating propagation losses and inter-user/inter-cell interference. Therefore, massive MIMO has been identified as one of the key candidate technologies for the 5th generation wireless standard. This dissertation thus focuses on (1) developing a performance analysis framework for cognitive massive MIMO systems by investigating the uplink transmissions of multi-cell multi-user massive MIMO secondary systems, which are underlaid in multi-cell multi-user primary massive MIMO systems, with taking into consideration the detrimental effects of practical transmission impairments, (2) proposing a new wireless-powered underlay cognitive massive MIMO system model, as the secondary user nodes is empowered by the ability to efficiently harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission, and (3) developing a secure communication strategy for cognitive multi-user massive MIMO systems, where physical layer secure transmissions are provisioned for both primary and secondary systems by exploiting linear precoders and artificial noise (AN) generation in order to degrade the signal decodability at eavesdropper. The key design feature of the proposed cognitive systems is to leverage the spatial multiplexing strategies to serve a large number of spatially distributed user nodes by using very large numbers of antennas at the base-stations. Moreover, the fundamental performance metrics, the secondary transmit power constraints, which constitute the underlay secondary transmissions subject to a predefined primary interference temperature, and the achievable sum rates of the primary and secondary systems, are characterized under different antenna array configurations. Additionally, the detrimental impact of practical wireless transmission impairments on the performance of the aforementioned systems are quantified. The important insights obtained throughout these analyses can be used as benchmarks for designing practical cognitive spectrum sharing networks.

The broadcast nature of wireless medium has made information security as one of the most important and critical issues in wireless systems. Physical layer security, which is based on information-theoretic secrecy concepts, can be used to secure the wireless channels by exploiting the noisiness and imperfections of the channels. Massive multiple-input multiple-output (MIMO) systems, which are equipped with very large antenna arrays at the base stations, have a great potential to boost the physical layer security by generating the artificial noise (AN) with the exploitation of excess degrees-of-freedom available at the base stations. In this thesis, we investigate physical layer security provisions in the presence of passive/active eavesdroppers for single-hop massive MIMO, dual-hop relay-assisted massive MIMO and underlay spectrum-sharing massive MIMO systems. The performance of the proposed security provisions is investigated by deriving the achievable rates at the user nodes, the information rate leaked into the eavesdroppers, and the achievable secrecy rates. Moreover, the effects of active pilot contamination attacks, imperfect channel state information (CSI) acquisition at the base-stations, and the availability of statistical CSI at the user nodes are quantified. The secrecy rate/performance gap between two AN precoders, namely the random AN precoder and the null-space based AN precoder, is investigated. The performance of hybrid analog/digital precoding is compared with the full-dimensional digital precoding. Furthermore, the physical layer security breaches in underlay spectrum-sharing massive MIMO systems are investigated, and thereby, security provisions are designed/analyzed against active pilot contamination attacks during the channel estimation phase. A power-ratio based active pilot attack detection scheme is investigated, and thereby, the probability of detection is derived. Thereby, the vulnerability of uplink channel estimation based on the pilots transmitted by the user nodes in time division duplexing based massive MIMO systems is revealed, and the fundamental trade-offs among physical layer security provisions, implementation complexity and performance gains are discussed.

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.