Técnicas de pré-codificação para sistemas multicelulares coordenados

Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido crescimento e uma solução promissora para controlar a interferência entre células em sistemas celulares, melhorando a equidade do sistema e aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced sob o conceito de coordenação multiponto (COMP). Existem várias abordagens sobre coordenação multicélula, dependendo da quantidade e do tipo de informação partilhada pelas estações base, através da rede de suporte (backhaul network), e do local onde essa informação é processada, i.e., numa unidade de processamento central ou de uma forma distribuída em cada estação base. Nesta tese, são propostas técnicas de pré-codificação e alocação de potência considerando várias estratégias: centralizada, todo o processamento é feito na unidade de processamento central; semidistribuída, neste caso apenas parte do processamento é executado na unidade de processamento central, nomeadamente a potência alocada a cada utilizador servido por cada estação base; e distribuída em que o processamento é feito localmente em cada estação base. Os esquemas propostos são projectados em duas fases: primeiro são propostas soluções de pré-codificação para mitigar ou eliminar a interferência entre células, de seguida o sistema é melhorado através do desenvolvimento de vários esquemas de alocação de potência. São propostas três esquemas de alocação de potência centralizada condicionada a cada estação base e com diferentes relações entre desempenho e complexidade. São também derivados esquemas de alocação distribuídos, assumindo que um sistema multicelular pode ser visto como a sobreposição de vários sistemas com uma única célula. Com base neste conceito foi definido uma taxa de erro média virtual para cada um desses sistemas de célula única que compõem o sistema multicelular, permitindo assim projectar esquemas de alocação de potência completamente distribuídos. Todos os esquemas propostos foram avaliados em cenários realistas, bastante próximos dos considerados no LTE. Os resultados mostram que os esquemas propostos são eficientes a remover a interferência entre células e que o desempenho das técnicas de alocação de potência propostas é claramente superior ao caso de não alocação de potência. O desempenho dos sistemas completamente distribuídos é inferior aos baseados num processamento centralizado, mas em contrapartida podem ser usados em sistemas em que a rede de suporte não permita a troca de grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems to mitigate inter-cell interference, improving system fairness and increasing capacity and thus is already under study in LTE-A under the coordinated multipoint (CoMP) concept. There are several coordinated transmission approaches depending on the amount of information shared by the transmitters through the backhaul network and where the processing takes place i.e. in a central processing unit or in a distributed way on each base station. In this thesis, we propose joint precoding and power allocation techniques considering different strategies: Full-centralized, where all the processing takes place at the central unit; Semi-distributed, in this case only some process related with power allocation is done at the central unit; and Fulldistributed, where all the processing is done locally at each base station. The methods are designed in two phases: first the inter-cell interference is removed by applying a set of centralized or distributed precoding vectors; then the system is further optimized by centralized or distributed power allocation schemes. Three centralized power allocation algorithms with per-BS power constraint and different complexity tradeoffs are proposed. Also distributed power allocation schemes are proposed by considering the multicell system as superposition of single cell systems, where we define the average virtual bit error rate (BER) of interference-free single cell system, allowing us to compute the power allocation coefficients in a distributed manner at each BS. All proposed schemes are evaluated in realistic scenarios considering LTE specifications. The numerical evaluations show that the proposed schemes are efficient in removing inter-cell interference and improve system performance comparing to equal power allocation. Furthermore, fulldistributed schemes can be used when the amounts of information to be exchanged over the backhaul is restricted, although system performance is slightly degraded from semi-distributed and full-centralized schemes, but the complexity is considerably lower. Besides that for high degrees of freedom distributed schemes show similar behaviour to centralized ones

Allocation des ressources fondée sur la qualité du canal pour la voie descendante des systèmes LTE

This research takes place in the context of Private Mobile Radio networks evolution which aims at designing a new LTE based PMR technology dedicated to public security services. As the frequency bands dedicated to this service is scarce and the need of public safety forces is different, we have revisited the Resource Allocation problem in this thesis with two main objectives: designing new allocation algorithms which outperform the spectrum efficiency and serving fairly the users instead of maximizing the global network throughput.This thesis proposes new Resource Block (RB) allocation strategies in LTE downlink systems. Instead of the well-known resource allocation algorithms, which work on the condition that the RB capacity is already estimated, our RB allocation schemes can improve the potential of the channel capacity, using Beamforming cooperation and game-theoretical problems1. With the MIMO (Multiple-Input-Multiple-output) antennas, the Beamforming technique improves the received signal in order to increase the SINR (Signal-to-Interference-plus-Noise-Ratio), but the improved signal may also influence the inter-cell interference in the neighbouring cells. As inter-cell interference is the main interference in the OFDMA system, a smart scheduling can choose UEs (User Equipment) in adjacent cells to control interference increment caused by Beamforming.In traditional methods, the scheduler allocates RBs to UEs depending on the RB capacities and other parameters, the system then applies the Beamforming technique to these chosen UEs. After the Beamforming, the RB capacity varies but the scheduler keeps the same allocation.Our scheme allocates the RBs and chooses Beamforming vectors at the same time to enhance the performance of the Beamforming technique. It increases the average throughput by increasing the RB’s average capacity. Because more parameters are taken into account, the complexity also increases exponentially. In the thesis we find an iterative method to reduce the complexity. From the simulations, our iterative method also has good performance and improves more than 10% of throughput on the cell edge.2. In contrast to the performance first algorithms, game theoretic allocation schemes maximize the UEs’ utility function from the economical point of view. The NBS (Nash Bargaining Solution) offers a Pareto optimal solution for the utility function.The traditional NBS allocation in an OFDMA system is to optimize the subcarrier allocation at each time slot, but in the OFDMA system, the subcarriers are composed of Resource Blocks (RB) in time series. We propose an RB NBS approach, which is more efficient than the existing subcarrier NBS allocation scheme.We analyze the fast-fading channels and compare them without the path-loss influence. Because of the great path-loss in cell edge, the edge UE always has lower RB capacity than the cell center UE. Our idea is to bring in a compensating factor to overcome this path-loss influence, and the compensating factors are carefully chosen to maximize the NBS function. However, the computation of these factors has a high complexity and we develop four approximated solutions which give same performance and accuracy. The performance evaluation confirms that our method and its approximated solutions are able to spread resources fairly over the entire cell.La recherche effectuée dans cette thèse a pour cadre les réseaux radio privés dédiés aux forces de sécurité civile. En effet, doté actuellement d’un service bande étroite, ils doivent évoluer pour faire face à de nouveaux besoins comme la vidéo ou le multimédia. L’objectif est donc d’adapter la technologie LTE aux contraintes et propriétés de ces réseaux particulier. Ainsi, le nombre d’utilisateurs est limité mais le service doit toujours être disponible et des priorités peuvent être mises en œuvre.Dans ce contexte, l’allocation des ressources de communication est un problème important avec des prérequis différents des réseaux d’opérateurs. Notre conception d’algorithmes d’allocation a donc été menée avec deux objectifs principaux : maximiser l'efficacité du spectre et servir équitablement les utilisateurs au lieu de maximiser le débit global du réseau.Cette thèse propose des nouvelles stratégies de l’allocation des blocs de ressources (RB) dans les systèmes LTE sur le lien descendant. Au contraire des algorithmes classiques d'allocation des ressources qui se basent sur la capacité de RB déjà estimée, nos stratégies d’allocation des RB cherchent à améliorer le débit utilisateur, en utilisant la coopération à base de Beamforming et les modèles de la théorie des jeux.1. L’interférence inter-cellulaire est le principal problème des systèmes OFDMA. Grâce aux antennes MIMO (Multiple-Input-Multiple-Output), la technique de Beamforming améliore le signal reçu afin d'augmenter le SINR (Signal-to-Interference-plus-Noise-Ratio), mais le signal amélioré peut également influencer l’interférence inter-cellulaire dans les cellules voisines. Dans les méthodes traditionnelles, le contrôleur alloue les RBs aux UEs (User Equipement) en fonction de la capacité des RB et d'autres paramètres, le système applique alors la technique de Beamforming aux équipements utilisateurs choisis. Après la formation des faisceaux, la capacité des RB varie mais l'ordonnanceur conserve la même allocation. Au contraire, notre système alloue les RBs et choisit les vecteurs de Beamforming conjointement pour améliorer les performances de la technique de Beamforming. Il accroît le débit moyen en augmentant la capacité moyenne du RB. Comme plusieurs paramètres sont pris en compte, la complexité augmente exponentiellement aussi. Dans cette thèse, nous avons développé une méthode itérative pour réduire la complexité. Notamment, elle améliore de plus de 10% le débit des utilisateurs en bord de la cellule.2. Contrairement aux performances des algorithmes qui maximisent le débit global du réseau, les approches d’allocation de ressources à base de théorie des jeux maximisent la fonction d'utilité des UE du point de vue économique. Si le modèle a une solution NBS (Nash Bargaining Solution) il offre une solution optimale de Pareto de la fonction d'utilité. L’allocation traditionnelle est d'optimiser l'allocation de sous-porteuses à chaque intervalle de temps, mais dans le système OFDMA, les sous-porteuses sont formées de RBs dans le temps. Nous proposons une approche RB NBS, qui est plus efficace que les schémas existants. Nous analysons les canaux de fast-fading et les comparons sans l'influence de l’atténuation. En raison de la grande atténuation de signal en bordure de la cellule, l’utilisateur a toujours des RB de plus faible capacité que celui au centre de la cellule. Notre idée est d'ajouter un facteur de compensation pour combattre l'influence de la perte de propagation. Les facteurs de compensation sont soigneusement choisis afin de maximiser la fonction NBS. Cependant, le calcul de ces facteurs a une grande complexité et nous développons quatre solutions approchées qui donnent les mêmes performances avec une bonne précision. L'évaluation des performances de notre approche confirme que notre méthode et ses solutions approchées sont capables de partager équitablement les ressources sur toute la cellule

Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid

The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency. To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario. In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices. To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches

Practical interference mitigation for Wi-Fi systems

Wi-Fi's popularity is also its Achilles' heel since in the dense deployments of multiple Wi-Fi networks typical in urban environments, concurrent transmissions interfere. The advent of networked devices with multiple antennas allows new ways to improve Wi-Fi's performance: a host can align the phases of the signals either received at or transmitted from its antennas so as to either maximize the power of the signal of interest through beamforming or minimize the power of interference through nulling. Theory predicts that these techniques should enable concurrent transmissions by proximal sender-receiver pairs, thus improving capacity. Yet practical challenges remain. Hardware platform limitations can prevent precise measurement of the wireless channel, or limit the accuracy of beamforming and nulling. The interaction between nulling and Wi-Fi's OFDM modulation, which transmits tranches of a packet's bits on distinct subcarriers, is subtle and can sacrifice the capacity gain expected from nulling. And in deployments where Wi-Fi networks are independently administered, APs must efficiently share channel measurements and coordinate their transmissions to null effectively. In this thesis, I design and experimentally evaluate beamforming and nulling techniques for use in Wi-Fi networks that address the aforementioned practical challenges. My contributions include: - Cone of Silence (CoS): a system that allows a Wi-Fi AP equipped with a phased-array antenna but only a single 802.11g radio to mitigate interference from senders other than its intended one, thus boosting throughput; - Cooperative Power Allocation (COPA): a system that efficiently shares channel measurements and coordinates transmissions between independent APs, and cooperatively allocates power so as to render received power across OFDM subcarriers flat at each AP's receiver, thus boosting throughput; - Power Allocation for Distributed MIMO (PADM): a system that leverages intelligent power allocation to mitigate inter-stream interference in distributed MIMO wireless networks, thus boosting throughput

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

A Comprehensive Survey on Resource Allocation for CRAN in 5G and Beyond Networks

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non- Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions