In the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable.

Wireless communication systems have undergone fast development in recent years. Based on GSM/EDGE and UMTS/HSPA, the 3rd Generation Partnership Project (3GPP) specified the Long Term Evolution (LTE) standard to cope with rapidly increasing demands, including capacity, coverage, and data rate. To achieve this goal, several key techniques have been adopted by LTE, such as Multiple-Input and Multiple-Output (MIMO), Orthogonal Frequency-Division Multiplexing (OFDM), and heterogeneous network (HetNet). However, there are some inherent drawbacks regarding these techniques. Direct conversion architecture is adopted to provide a simple, low cost transmitter solution. The problem of I/Q imbalance arises due to the imperfection of circuit components; the orthogonality of OFDM is vulnerable to carrier frequency offset (CFO) and sampling frequency offset (SFO). The doubly selective channel can also severely deteriorate the receiver performance. In addition, the deployment of Heterogeneous Network (HetNet), which permits the co-existence of macro and pico cells, incurs inter-cell interference for cell edge users. The impact of these factors then results in significant degradation in relation to system performance. This dissertation aims to investigate the key techniques which can be used to mitigate the above problems. First, I/Q imbalance for the wideband transmitter is studied and a self-IQ-demodulation based compensation scheme for frequency-dependent (FD) I/Q imbalance is proposed. This combats the FD I/Q imbalance by using the internal diode of the transmitter and a specially designed test signal without any external calibration instruments or internal low-IF feedback path. The instrument test results show that the proposed scheme can enhance signal quality by 10 dB in terms of image rejection ratio (IRR). In addition to the I/Q imbalance, the system suffers from CFO, SFO and frequency-time selective channel. To mitigate this, a hybrid optimum OFDM receiver with decision feedback equalizer (DFE) to cope with the CFO, SFO and doubly selective channel. The algorithm firstly estimates the CFO and channel frequency response (CFR) in the coarse estimation, with the help of hybrid classical timing and frequency synchronization algorithms. Afterwards, a pilot-aided polynomial interpolation channel estimation, combined with a low complexity DFE scheme, based on minimum mean squared error (MMSE) criteria, is developed to alleviate the impact of the residual SFO, CFO, and Doppler effect. A subspace-based signal-to-noise ratio (SNR) estimation algorithm is proposed to estimate the SNR in the doubly selective channel. This provides prior knowledge for MMSE-DFE and automatic modulation and coding (AMC). Simulation results show that this proposed estimation algorithm significantly improves the system performance. In order to speed up algorithm verification process, an FPGA based co-simulation is developed. Inter-cell interference caused by the co-existence of macro and pico cells has a big impact on system performance. Although an almost blank subframe (ABS) is proposed to mitigate this problem, the residual control signal in the ABS still inevitably causes interference. Hence, a cell-specific reference signal (CRS) interference cancellation algorithm, utilizing the information in the ABS, is proposed. First, the timing and carrier frequency offset of the interference signal is compensated by utilizing the cross-correlation properties of the synchronization signal. Afterwards, the reference signal is generated locally and channel response is estimated by making use of channel statistics. Then, the interference signal is reconstructed based on the previous estimate of the channel, timing and carrier frequency offset. The interference is mitigated by subtracting the estimation of the interference signal and LLR puncturing. The block error rate (BLER) performance of the signal is notably improved by this algorithm, according to the simulation results of different channel scenarios. The proposed techniques provide low cost, low complexity solutions for LTE and beyond systems. The simulation and measurements show good overall system performance can be achieved.

By using existing radio network infrastructure, a user can be positioned even where GPS and other positioning technologies lack coverage. The LTE Positioning Protocol (LPP) supports user Reference Signal Time Difference (RSTD) reports based on the Time of Arrival (TOA) for a Positioning Reference Signal (PRS). In the current reporting format, only one RSTD for each base station is considered, but for indoor environments this is easily biased due to fading and multipath issues, resulting in a Non-Line of Sight (NLOS) bias. With a rich User Equipment (UE) feedback that can represent the multipath channel for each Base Station (BS), the positioning accuracy can be increased. This thesis develops and evaluates a UE reporting format representing multiple TDOA candidates, and a probabilistic positioning algorithm, in terms of positioning accuracy and amount of data reported. By modeling time measurements as Gaussian Mixture (GM), the time information can be compressed with arbitrary resolution and used in a Maximum-Likelihood (ML) estimation to find the position. Results were obtained through simulation in a radio network simulator and post-processing of simulation data in Matlab. The results suggest that several TOA candidates improve the positioning accuracy, but that the largest improvement comes from a noise based threshold by increasing LOS detectability reducing the NLOS bias, while suppressing noise. The results also suggest that the accuracy for the method can be further improved by combining multiple time measurement occasions.

Thesis maps the situation in the telecommunications market in the Czech Republic, analyzes the major players on the Czech nad world market, and analyzes the possibilities of marketing and presentation of high-tech to customers in user-friendly form.

Magíster en Ingeniería de Redes de Comunicaciones / Un estudio exhaustivo de las técnicas modernas de modulación es esencial para el diseño de sistemas futuros. Las tecnologías basadas en OFDM, como LTE, se están volviendo más penetrantes a medida que los sistemas descendientes de LTE han adoptado esta técnica de modulación. Los sistemas celulares inalámbricos 5G probablemente seguirán esta tendencia. Es importante estudiar las fortalezas y debilidades de las modulaciones basadas en OFDM para mejorar el rendimiento con las nuevas generaciones. Por esta razón, es esencial determinar qué componentes contribuyen al rendimiento del sistema y eliminar o reemplazar aquellos que no lo hacen. Se estudió un sistema de SC-FDMA usando varios métodos de mapeo de portadoras. En este trabajo se realizó dos tipos de estudios: 1) Análisis exhaustivo del mapeo de las portadoras de SC-FDMA, específicamente SC-LFDMA y SC-IFDMA. Para estudiar las fortalezas y debilidades de SC-LFDMA y SC-IFDMA se genera un escenario donde se considera el canal AWGN y 2) Para poder enfatizar los beneficios de SC-IFDMA se genera dos escenarios: a) Canal con desvanecimiento selectivo en frecuencia y ganancia selectiva de frecuencia usando ruido AWGN y b) Canal con desvanecimiento selectivo en frecuencia usando ruido AWGN. El ruido estudiado en este trabajo es el AWGN. Específicamente se quiere estudiar el beneficio d e los tipos de mapeo de portadoras usando redundancia. Como escenario de control se utiliza el mismo esquema pero sin redundancia. La modulación ascendente de LTE implementa SC-LFDMA, que tiene un PAPR alto comparado con el SC-IFDMA. Se argumenta que SC-LFDMA tiene un alto Eb/N0, sin embargo, aquí se demuestra que sólo la varianza de la Eb/N0 se incrementa, pero el promedio sigue siendo el mismo en un escenario donde se considera el canal AWGN. En un canal con desvanecimiento selectivo en frecuencia usando ruido AWGN, la Eb/N0 de SC-IFDMA es superior a SC-LFDMA, en el escenario de control y también para el caso con redundancia. Para un canal con desvanecimiento selectivo en frecuencia y ganancia selectiva de frecuencia usando ruido AWGN se demuestra que la Eb/N0 de SC-LFDMA es superior a SC-IFDMA en un escenario con redundancia, pero al tener alto BER el SC-LFDMA, el SC-IFDMA es mejor. Para el escenario de control, la Eb/N0 de SC-IFDMA es igual a SC-LFDMA, pero al tener alto BER el SC-LFDMA, el SC-IFDMA es mejor. En términos de PAPR, para todos los casos y escenarios el SC-IFDMA tiene un PAPR bajo comparado con el SC-LFDMA. A pesar de que LTE utiliza SC-LFDMA, las tecnologías futuras deberían considerar el estudio de los beneficios del SC-IFDMA, ya que se demuestra que tiene mucho que ofrecer. En particular, para las transmisiones ascendentes, ya que es más eficiente desde el punto de vista energético y no parece haber un compromiso de rendimiento significativo. Por lo tanto, se debe seleccionar una técnica de modulación de PAPR baja, tal como SC-IFDMA, para transmisiones ascendentes de redes celulares inalámbricas de próxima generación.

Drone usage is increasing, both in recreational use and in the industry. With it comes a number of problems to tackle. Primarily, there are certain areas in which flying drones pose a security threat, e.g., around airports or other no-fly zones. Other problems can appear when there are drones in mobile networks which can cause interference. Such interference comes from the fact that radio transmissions emitted from drones can travel more freely than those from regular UEs (User Equipment) on the ground since there are few obstructions in the air. Additionally, the data traffic sent from drones is often high volume in the form of video streams. The goal of this thesis is to identify so-called "rogue drones" connected to an LTE network. Rogue drones are flying drones that appear to be regular UEs in the network. Drone identification is a binary classification problem where UEs in a network are classified as either a drone or a regular UE and this thesis proposes machine learning methods that can be used to solve it. Classifications are based on radio measurements and statistics reported by UEs in the network. The data for the work in this thesis is gathered through simulations of a heterogenous LTE network in an urban scenario. The primary idea of this thesis is to use a type of cascading classifier, meaning that classifications are made in a series of stages with increasingly complex models where only a subset of examples are passed forward to subsequent stages. The motivation for such a structure is to minimize the computational requirements at the entity making the classifications while still being complex enough to achieve high accuracy. The models explored in this thesis are two-stage cascading classifiers using decision trees and ensemble learning techniques. It is found that close to 60% of the UEs in the dataset can be classified without errors in the first of the two stages. The rest is forwarded to a more complex model which requires more data from the UEs and can achieve up to 98% accuracy.

Submitted by Luciclea Silva (luci@ufpa.br) on 2018-11-09T17:16:39Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Estrategiaotimizacaooffloading.pdf: 4353496 bytes, checksum: 660c9fb62874c25c2071d6e88692d9a9 (MD5) / Approved for entry into archive by Luciclea Silva (luci@ufpa.br) on 2018-11-09T17:17:01Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Estrategiaotimizacaooffloading.pdf: 4353496 bytes, checksum: 660c9fb62874c25c2071d6e88692d9a9 (MD5) / Made available in DSpace on 2018-11-09T17:17:01Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Estrategiaotimizacaooffloading.pdf: 4353496 bytes, checksum: 660c9fb62874c25c2071d6e88692d9a9 (MD5) Previous issue date: 2018-08-31 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O aumento no consumo de tráfego de dados é motivado pelo aumento do número de dispositivos como smartphone e tablets, já que há uma necessidade de estar conectado com tudo e com todos. As aplicações como streaming de vídeo e jogos online demandam por maior taxa de transmissão de dados, essa alta demanda corrobora para um a sobrecarga das redes móveis baseadas por radiofrequência, de modo a culminar em uma possível escassez do espectro RF. Por tanto, este trabalho busca otimizar o offloading entre LTE e VLC, e para isso é utilizado uma metodologia baseado em aprendizado por reforço denominada de Q-Learning. O algoritmo utiliza como entrada as variáveis do ambiente que estão relacionadas à qualidade do sinal, densidade e velocidade do usuário para aprender e selecionar a melhor conexão. Por tanto, os resultados da simulação mostram a eficiência da metodologia proposta em comparação com o esquema RSS predominante na literatura da área. já que provou por métricas de QoS, suportar maiores taxas de transmissão de dados, assim como, garantiu uma melhoria de 18% em relação as interrupções de serviço a medida que o número de usuários aumenta no sistema. / The increase in the consumption of data traffic is motivated by the increasing number of devices like smartphone and tablets, since there is a need to be connected with everything and with everyone. Applications such as streaming video and online games require a higher rate of data transmission, this high demand corroborates the overload of mobile networks based on radio frequency, so as to culminate in a possible shortage of the RF spectrum. Therefore, this work seeks to optimize offloading between LTE and VLC, and for this a methodology based on reinforcement learning called Q-Learning is used. The algorithm uses as input the environment variables that are related to the signal quality, density and speed of the user to learn and select the best connection. Therefore, the results of the simulation show the efficiency of the proposed methodology in comparison with the predominant RSS scheme in the area literature. as it has been proven by QoS metrics to support higher data rates, as well as ensuring an 18% improvement over service interruptions as the number of users increases in the system.

Reliable wireless networks for high speed trains require a significant amount of data communications for enabling safety features such as train collision avoidance and railway management. Cognitive radio integrates heterogeneous wireless networks that will be deployed in order to achieve intelligent communications in future railway systems. One of the primary technical challenges in achieving reliable communications for railways is the handling of high mobility environments involving trains, which includes significant Doppler shifts in the transmission as well as severe fading scenarios that makes it difficult to estimate wireless spectrum utilization. This thesis has two primary contributions: (1) The creation of a Heterogeneous Cooperative Spectrum Sensing (CSS) prototype system, and (2) the derivation of a Long Term Evolution for Railways (LTE-R) system performance analysis. The Heterogeneous CSS prototype system was implemented using Software-Defined Radios (SDRs) possessing different radio configurations. Both soft and hard-data fusion schemes were used in order to compare the signal source detection performance in real-time fading scenarios. For future smart railways, one proposed solution for enabling greater connectivity is to access underutilized spectrum as a secondary user via the dynamic spectrum access (DSA) paradigm. Since it will be challenging to obtain an accurate estimate of incumbent users via a single-sensor system within a real-world fading environment, the proposed cooperative spectrum sensing approach is employed instead since it can mitigate the effects of multipath and shadowing by utilizing the spatial and temporal diversity of a multiple radio network. Regarding the LTE-R contribution of this thesis, the performance analysis of high speed trains (HSTs) in tunnel environments would provide valuable insights with respect to the smart railway systems operating in high mobility scenarios in drastically impaired channels.

Long Term Evolution (LTE) is enormously adopted by several mobile operators and has been introduced as a solution to fulfil ever-growing Users (UEs) data requirements in cellular networks. Enlarged data demands engage resource blocks over prolong time interval thus results into more dynamic power consumption at downlink in Basestation. Therefore, realisation of UEs requests come at the cost of increased power consumption which directly affects operator operational expenditures. Moreover, it also contributes in increased CO2 emissions thus leading towards Global Warming. According to research, Global Information and Communication Technology (ICT) systems consume approximately 1200 to 1800 Terawatts per hour of electricity annually. Importantly mobile communication industry is accountable for more than one third of this power consumption in ICT due to increased data requirements, number of UEs and coverage area. Applying these values to global warming, telecommunication is responsible for 0.3 to 0.4 percent of worldwide CO2 emissions. Moreover, user data volume is expected to increase by a factor of 10 every five years which results in 16 to 20 percent increase in associated energy consumption which directly effects our environment by enlarged global warming. This research work focuses on the importance of energy saving in LTE and initially propose bandwidth expansion based energy saving scheme which combines two resource blocks together to form single super RB, thereby resulting in reduced Physical Downlink Control Channel Overhead (PDCCH). Thus, decreased PDCCH overhead helps in reduced dynamic power consumption up to 28 percent. Subsequently, novel reduced early handover (REHO) based idea is proposed and combined with bandwidth expansion to form enhanced energy ii saving scheme. System level simulations are performed to investigate the performance of REHO scheme; it was found that reduced early handover provided around 35% improved energy saving while compared to LTE standard in 3rd Generation Partnership Project (3GPP) based scenario. Since there is a direct relationship between energy consumption, CO2 emissions and vendors operational expenditure (OPEX); due to reduced power consumption and increased energy efficiency, REHO subsequently proven to be a step towards greener communication with lesser CO2 footprint and reduced operational expenditure values. The main idea of REHO lies in the fact that it initiate handovers earlier and turn off freed resource blocks as compare to LTE standard. Therefore, the time difference (Transmission Time Intervals) between REHO based early handover and LTE standard handover is a key component for energy saving achieved, which is estimated through axiom of Euclidean geometry. Moreover, overall system efficiency is investigated through the analysis of numerous performance related parameters in REHO and LTE standard. This led to a key finding being made to guide the vendors about the choice of energy saving in relation to radio link failure and other important parameters.

One of the key requirements of fifth generation (5G) systems is having a connection to mobile networks without interruption at anytime and anywhere, which is also known as seamless connectivity. Nowadays, fourth generation (4G) systems, Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A), are mature enough to provide connectivity to most terrestrial mobile users. However, for airborne mobile users, there is no connection that exists without interruption. According to the regulations, mobile connectivity for aircraft passengers can only be established when the altitude of the aircraft is above 3000 m. Along with demands to have mobile connectivity during a flight and the seamless connectivity requirement of 5G systems, there is a notable interest in providing in-flight wireless services during all phases of a flight. In this thesis, many issues related to the deployment and operation of the onboard systems have been investigated. A measurement and modelling procedure to investigate radio frequency (RF) propagation inside an aircraft is proposed in this thesis. Unlike in existing studies for in-cabin channel characterization, the proposed procedure takes into account the deployment of a multi-cell onboard system. The proposed model is verified through another set of measurements where reference signal received power (RSRP) levels inside the aircraft are measured. The results show that the proposed model closely matches the in-cabin RSRP measurements. Moreover, in order to enforce the distance between a user and an interfering resource, cell sectorization is employed in the multi-cell onboard system deployment. The proposed propagation model is used to find an optimum antenna orientation that minimizes the interference level among the neighbouring evolved nodeBs (eNBs). Once the optimum antenna deployment is obtained, comprehensive downlink performance evaluations of the multi-cell, multi-user onboard LTE-A system is carried out. Techniques that are proposed for LTE-A systems, namely enhanced inter-cell interference coordination (eICIC) and carrier aggregation (CA), are employed in the system analysis. Different numbers of eNBs, antenna mounting positions and scheduling policies are examined. A scheduling algorithm that provides a good tradeoff between fairness and system throughput is proposed. The results show that the downlink performance of the proposed onboard LTE-A system achieves not only 75% of the theoretical limits of the overall system throughput but also fair user data rate performance, irrespective of a passenger's seat location. In order to provide the seamless connectivity requirement of 5G systems, compatibility between the proposed onboard system deployment and the already deployed terrestrial networks is investigated. Simulation based analyses are carried out to investigate power leakage from the onboard systems while the aircraft is in the parked position on the apron. According to the regulations, the onboard system should not increase the noise level of the already deployed terrestrial system by 1 dB. Results show that the proposed onboard communication system can be operated while the aircraft is in the parked position on the apron without exceeding the 1 dB increase in the noise level of the already deployed terrestrial 4G network. Furthermore, handover parameters are obtained for different transmission power levels of both the terrestrial and onboard systems to make the transition from one system to another without interruption while a passenger boards or leaves the aircraft. Simulation and measurement based analyses show that when the RSRP level of the terrestrial system is below -65 dBm around the aircraft, a boarding passenger can be smoothly handed over to the onboard system and vice versa. Moreover, in order to trigger the handover process without interfering with the data transmission, a broadcast control channel (BCCH) power boosting feature is proposed for the in-cabin eNBs. Results show that employing the BCCH power boosting feature helps to trigger the handover process as soon as the passengers step on board the aircraft.