Models of Control Channels in the LTE System

Dizertační práce se zabývá zpracováním signálu fyzických řídicích kanálů systému LTE a vyšetřováním bitové chybovosti při přenosu řídicí informace z vysílače do přijímače v závislosti na podmínkách příjmu. Práce je rozdělena do dvou hlavních částí. První část práce je zaměřena na simulaci přenosu řídicí informace LTE v základním pásmu. Jsou zde prezentovány vytvořené simulátory řídicích kanálů ve směru uplink i downlink. Simulace jsou provedeny pro všechny druhy nastavení systému a základní modely přenosového prostředí. Jsou zde popsány výsledky vlivu použití MIMO technologií na kvalitu příjmu řídicí informace především v únikových kanálech. Druhá část práce je zaměřena na možnost nasazení systému LTE ve sdíleném pásmu ISM (2.4 GHz). Jsou zde představeny základní koncepce použití, na jejichž základě je vytvořen scénář simulací. Kapitola dále popisuje tvorbu simulátoru koexistence LTE a systému Wi-Fi v přeneseném pásmu ISM 2.4GHz. Jsou zde uvedeny výsledky simulací koexistence LTE a rušivého systému Wi-Fi provedených dle vytvořeného scénáře. Výsledky simulací koexistence LTE a Wi-Fi jsou ověřeny měřením v laboratorních podmínkách. Toto porovnání je důležité z hlediska optimalizace simulátoru koexistence. Dle výsledků obou typů simulací a měření jsou stanovena provozní doporučení, která mají přispět k bezpečnému a spolehlivému vysílání a příjmu řídicích informací LTE i při nepříznivých podmínkách příjmu.The doctoral thesis is focused on a signal processing in the LTE physical control channels and performance analysis of control information transmission according to receiving conditions. The thesis is divided into two parts. The first part deals with simulation of the transmission of control information in baseband. The created simulators for uplink and downlink are presented. The simulations are performed for all possible system settings and various channel models. The MIMO influence on a quality of control information reception under fading channels is also presented. The second part of the thesis is focused on LTE utilization in shared channel ISM (2.4 GHz). The basic LTE application concept for ISM band is presented. This concept is fundamental to created simulation scenario. The chapter also presents the LTE and Wi-Fi coexistence simulator in 2.4 GHz ISM passband. The coexistence simulation are presented according to simulation scenario and the results are shown. The simulated coexistence analysis results are verified in laboratory environment. The comparison of the simulated and the measured coexistence analysis results is crucial for further optimization of the coexistence simulator. Recommendations for optimal and reliable operation of LTE are specified according to the simulated and the measured results. Recommendations should be useful to the reliable transmission of LTE control information in bad receiving conditions.

On the Support of Massive Machine-to-Machine Traffic in Heterogeneous Networks and Fifth-Generation Cellular Networks

The widespread availability of many emerging services enabled by the Internet of Things (IoT) paradigm passes through the capability to provide long-range connectivity to a massive number of things, overcoming the well-known issues of ad-hoc, short-range networks. This scenario entails a lot of challenges, ranging from the concerns about the radio access network efficiency to the threats about the security of IoT networks. In this thesis, we will focus on wireless communication standards for long-range IoT as well as on fundamental research outcomes about IoT networks. After investigating how Machine-Type Communication (MTC) is supported nowadays, we will provide innovative solutions that i) satisfy the requirements in terms of scalability and latency, ii) employ a combination of licensed and license-free frequency bands, and iii) assure energy-efficiency and security

4G/5G cellular networks metrology and management

La prolifération d'applications et de services sophistiqués s'accompagne de diverses exigences de performances, ainsi que d'une croissance exponentielle du trafic pour le lien montant (uplink) et descendant (downlink). Les réseaux cellulaires tels que 4G et 5G évoluent pour prendre en charge cette quantité diversifiée et énorme de données. Le travail de cette thèse vise le renforcement de techniques avancées de gestion et supervision des réseaux cellulaires prenant l'explosion du trafic et sa diversité comme deux des principaux défis dans ces réseaux. La première contribution aborde l'intégration de l'intelligence dans les réseaux cellulaires via l'estimation du débit instantané sur le lien montant pour de petites granularités temporelles. Un banc d'essai 4G temps réel est déployé dans ce but de fournir un benchmark exhaustif des métriques de l'eNB. Des estimations précises sont ainsi obtenues. La deuxième contribution renforce le découpage 5G en temps réel au niveau des ressources radio dans un système multicellulaire. Pour cela, deux modèles d'optimisation ont été proposés. Du fait de leurs temps d'exécution trop long, des heuristiques ont été développées et évaluées en comparaisons des modèles optimaux. Les résultats sont prometteurs, les deux heuristiques renforçant fortement le découpage du RAN en temps réel.The proliferation of sophisticated applications and services comes with diverse performance requirements as well as an exponential traffic growth for both upload and download. The cellular networks such as 4G and 5G are advocated to support this diverse and huge amount of data. This thesis work targets the enforcement of advanced cellular network supervision and management techniques taking the traffic explosion and diversity as two main challenges in these networks. The first contribution tackles the intelligence integration in cellular networks through the estimation of users uplink instantaneous throughput at small time granularities. A real time 4G testbed is deployed for such aim with an exhaustive metrics benchmark. Accurate estimations are achieved.The second contribution enforces the real time 5G slicing from radio resources perspective in a multi-cell system. For that, two exact optimization models are proposed. Due to their high convergence time, heuristics are developed and evaluated with the optimal models. Results are promising, as two heuristics are highly enforcing the real time RAN slicing

Content-aware radio resource management for IMT-advanced systems

Radio Resource Management (RRM) is crucial to efficiently and correctly manage the delivery of quality-of-service (QoS) in IMT-Advanced systems. Various methods on radio resource management for LTE/LTE-Advanced traffic have been studied by researchers especially regarding QoS handling of video packet transmissions. Usually, cross-layer optimisation (CLO) involving the PHY and MAC layers, has been used to provide proper resource allocation and distribution to the entire system. Further initiatives to include the APP layer as part of CLO techniques have gained considerable attention by researchers. However, some of these methods did not adequately consider the level of compatibility with legacy systems and standards. Furthermore, the methods did not wholly address User Equipment (UE) mobility or performance metrics for a specific data type or a specified period. Consequently, in this thesis, a content-aware radio RRM model employing a cross-layer optimiser focusing on a video conferencing/streaming application for a single cell long-term evolution (LTE) system has been proposed. Based on two constructed look-up tables, the cross-layer optimiser was found to dynamically adjust the transmitted video data rates depending on the UE or eNodeB SINR performance. The proposed look-up tables were derived from the performance study of the LTE classical (baseline) simulation model for various distances at a certain UE velocity. Two performance parameters, namely the average throughput and measured SINR were matched together to find the most suitable data rates for video delivery in both the uplink and downlink transmissions. The developed content-aware RRM model was then tested against the LTE baseline simulation model, to benchmark its capability to be used as an alternative to existing RRM methods in the present LTE system. Based on the detailed simulations, the output performance demonstrated that for video packet delivery in both uplink and downlink transmissions, the content-aware RRM model vastly outperformed the legacy LTE baseline simulation model with regard to the packet loss ratio and average end-to-end delay for the same amount of throughput. The baseline simulation model and the newly developed cross-layer approach were investigated and compared with practical measurement results in which PodNode technology, besides other components and supporting simulation software, were used to emulate the LTE communication system. The first emulation experiment involving the baseline model was generally in sync with the uplink throughput simulation performance. The second test which implemented the cross-layer approach employing the look-up table derived from the previous emulated results, confirmed the viability of the proposed content-aware RRM model to be used in current LTE or LTE-Advanced systems for improving the performance in the packet loss ratio and average packet delay