A cell outage management framework for dense heterogeneous networks

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner

Priority Communications for Critical Situations on Mobile Networks

[ES] En la actualidad, las redes públicas de comunicación están ampliamente desplegadas en todo el territorio. Como las redes públicas no contemplan un uso priorizado de los recurso, los cuerpos de seguridad tienden a utilizar redes privadas de uso específico. Estas redes privadas satisfacen los requisitos marcados pero, a cambio, los costes de despliegue y mantenimiento son muy elevados, lo cual limita su despliegue y disponibilidad. Además, la interconexión entre distintas redes privadas no siempre es posible, lo que supone un gran problema cuando la emergencia se produce en zonas fronterizas. Estos grandes inconvenientes justifican un estudio minucioso sobre nuevos mecanismos de priorización en la gestión de recursos radio que permitan hacer uso de las redes públicas por parte de los cuerpos de seguridad y emergencias. Para ello se ha analizado el marco tecnológico actual, se ha contactado con distintos cuerpos de seguridad para averiguar los requisitos de comunicación actuales y los deseables. Caracterizado el sistema, se han definido distintos escenarios realistas utilizados en simulación masivas para finalmente demostrar cómo una red pública es capaz de cursar todo el tráfico que actualmente cursa una red privada en una situación de emergencia.[EN] Technical evaluation for enhancement and priorization of calls during a emergency situation over 2G and 3G networksDíaz Sendra, S. (2012). Priority Communications for Critical Situations on Mobile Networks. http://hdl.handle.net/10251/27446.Archivo delegad

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

Impacto do comportamento transitório de sistemas de radiocomunicações na gestão do espectro

Doutoramento em Engenharia EletrotécnicaThis PhD Thesis falls within the domain of spectrum engineering and spectrum management, and intends to address current and concrete problems, with which, regulators have to deal. Particularly, the definition of technical conditions to be met by radio systems, which will operate in specific bands, selected to introduce novel concepts such as flexibility and technological neutrality. The Block Edge Mask approach was adopted to define technical conditions of operation, in those bands. However, this model, based on spectral masks, which are defined in the frequency domain, do not take into account the transient behavior or time-varying characteristics of signals used by emerging radio communication systems. Furthermore, measurement methodologies developed for validation of technical parameters associated to these models, which are recommended by international bodies, potentially lead to practical issues that must be scrutinized. Thus, alternative time-frequency mixed domain signal processing techniques are explored, in this thesis, to be used for assessing the compliance of radio systems operating under such constraints.Esta Tese de Doutoramento insere-se nos domínios da engenharia do espectro e da gestão do espectro radioelétrico, e pretende abordar problemas atuais e concretos com que os reguladores se deparam. Em particular, a definição de condições técnicas a serem cumpridas pelos sistemas rádio que irão operar em determinadas faixas de frequências, selecionadas para a introdução de abordagens de gestão do espectro mais flexíveis e tecnologicamente neutras. O modelo de Máscara Delimitadora de Bloco (Block Edge Mask) foi adotado, a nível europeu, como estratégia de definição de condições técnicas de operação, nessas faixas. Contudo, este modelo, que recorre a restrições que são apenas estabelecidas no domínio da frequência, não entra em linha de conta com comportamentos transitórios ou com a variabilidade temporal de sinais inerentes aos sistemas de radiocomunicações atuais. Para além disso, a medição e validação de parâmetros técnicos associados a estes modelos, conforme definidas nas recomendações internacionais aplicáveis, levantam problemas práticos que importa escalpelizar. Nesse sentido, são exploradas, nesta tese, técnicas alternativas de processamento de sinal no domínio misto tempo-frequência, tendo em vista a sua utilização na avaliação de conformidade dos sistemas rádio em face das restrições aplicáveis

Header Compression and Signal Processing for Wideband Communication Systems.

This thesis is dedicated to the investigation, development and practical verification of header compression and signal processing techniques over TErrestrial Trunked RAdio (TETRA), TETRA Enhanced Data Services (TEDS) and Power Line Communication (PLC). TETRA release I is a narrowband private mobile radio technology used by safety and security organizations, while TEDS is a widebandsystem. With the introduction of IP support, TEDS enables multimedia based applications and services to communicate across communication systems. However the IP extension for TEDS comes at a cost of significant header contributions with the payload. With small application payloads and fast rate application traffic profiles, the header contribution in the total size of the packet is considerably more than the actual application payload. This overhead constitutes the considerable slot capacity at the physical layer of TEDS and PLC. Advanced header compression techniques such as Robust Header Compression (RoHC) compress the huge header sizes and offer significant compression gain without compromising quality of service (QoS). Systems can utilize this bandwidth to transmit more information payload than control information. In this study, the objective is to investigate the integration of RoHC in TEDS and design a novel IPv6 enabled protocol stack for PLC with integrated RoHC. The purpose of the study is also to investigate the throughput optimization technique such as RoHC over TEDS and PLC by simulating different traffic profile classes and to illustrate the benefit of using RoHC over TEDS and PLC. The thesis also aims to design and simulate the TEDS physical layer for the purpose of investigating the performance of higher order modulation schemes. Current TEDS, standards are based on the transmission frequencies above 400MHz range, however with delays in the standardization of broadband TETRA, it is important to explore all possible avenues to extend the capacity of the system. The research concludes the finding of the application of RoHC for TEDS and PLC, against different traffic classes and propagation channels. The benefit of using RoHC in terms of saving bandwidth, slot capacity and other QoS parameters is presented along with integration aspects into TEDS and PLC communication stacks. The study also presents the TEDS physical layer simulation results for modulation schemes and transmission frequency other than specified in the standard. The research results presented in this thesis have been published in international symposiums and professional journals. The application of the benefits of using RoHC for TEDS has been proposed to the ETSI TETRA for contribution to the TETRA standard under STF 378. Simulation results for the investigation of characteristics of ?/4 DQPSK performance below 200 MHz have also been also presented to ETSI TETRA as a contribution to the existing TEDS standard. The Results presented for the design of IPv6 enabled stacked with integrated RoHC have been submitted as deliverable under the FP-7 project DLC+VIT4IP. All the results, simulations and investigations presented in the thesis have been carried out through the platform provided by HW Communication Ltd

Efficient Discovery and Utilization of Radio Information in Ultra-Dense Heterogeneous 3D Wireless Networks

Emergence of new applications, industrial automation and the explosive boost of smart concepts have led to an environment with rapidly increasing device densification and service diversification. This revolutionary upward trend has led the upcoming 6th-Generation (6G) and beyond communication systems to be globally available communication, computing and intelligent systems seamlessly connecting devices, services and infrastructure facilities. In this kind of environment, scarcity of radio resources would be upshot to an unimaginably high level compelling them to be very efficiently utilized. In this case, timely action is taken to deviate from approximate site-specific 2-Dimensional (2D) network concepts in radio resource utilization and network planning replacing them with more accurate 3-Dimensional (3D) network concepts while utilizing spatially distributed location-specific radio characteristics. Empowering this initiative, initially a framework is developed to accurately estimate the location-specific path loss parameters under dynamic environmental conditions in a 3D small cell (SC) heterogeneous networks (HetNets) facilitating efficient radio resource management schemes using crowdsensing data collection principle together with Linear Algebra (LA) and machine learning (ML) techniques. According to the results, the gradient descent technique is with the highest path loss parameter estimation accuracy which is over 98%. At a latter stage, receive signal power is calculated at a slightly extended 3D communication distances from the cluster boundaries based on already estimated propagation parameters with an accuracy of over 74% for certain distances. Coordination in both device-network and network-network interactions is also a critical factor in efficient radio resource utilization while meeting Quality of Service (QoS) requirements in heavily congested future 3D SCs HetNets. Then, overall communication performance enhancement through better utilization of spatially distributed opportunistic radio resources in a 3D SC is addressed with the device and network coordination, ML and Slotted-ALOHA principles together with scheduling, power control and access prioritization schemes. Within this solution, several communication related factors like 3D spatial positions and QoS requirements of the devices in two co-located networks operated in licensed band (LB) and unlicensed band (UB) are considered. To overcome the challenge of maintaining QoS under ongoing network densification and with limited radio resources cellular network traffic is offloaded to UB. Approximately, 70% better overall coordination efficiency is achieved at initial network access with the device network coordinated weighting factor based prioritization scheme powered with the Q-learning (QL) principle over conventional schemes. Subsequently, coverage information of nearby dense NR-Unlicensed (NR-U) base stations (BSs) is investigated for better allocation and utilization of common location-specific spatially distributed radio resources in UB. Firstly, the problem of determining the receive signal power at a given location due to a transmission done by a neighbor NR-U BS is addressed with a solution based on a deep regression neural network algorithm enabling to predict receive signal or interference power of a neighbor BS at a given location of a 3D cell. Subsequently, the problem of efficient radio resource management is considered while dynamically utilizing UB spectrum for NR-U transmissions through an algorithm based on the double Q-learning (DQL) principle and device collaboration. Over 200% faster algorithm convergence is achieved by the DQL based method over conventional solutions with estimated path loss parameters

Comunicaciones Móviles de Misión Crítica sobre Redes LTE

Mission Critical Communications (MCC) have been typically provided by proprietary radio technologies, but, in the last years, the interest to use commercial-off-the-shelf mobile technologies has increased. In this thesis, we explore the use of LTE to support MCC. We analyse the feasibility of LTE networks employing an experimental platform, PerformNetworks. To do so, we extend the testbed to increase the number of possible scenarios and the tooling available. After exploring the Key Performance Indicators (KPIs) of LTE, we propose different architectures to support the performance and functional requirements demanded by MCC. We have identified latency as one of the KPI to improve, so we have done several proposals to reduce it. These proposals follow the Mobile Edge Computing (MEC) paradigm, locating the services in what we called the fog, close to the base station to avoid the backhaul and transport networks. Our first proposal is the Fog Gateway, which is a MEC solution fully compatible with standard LTE networks that analyses the traffic coming from the base station to decide whether it has to be routed to the fog of processed normally by the SGW. Our second proposal is its natural evolution, the GTP Gateway that requires modifications on the base station. With this proposal, the base station will only transport over GTP the traffic not going to the fog. Both proposals have been validated by providing emulated scenarios, and, in the case of the Fog Gateway, also with the implementation of different prototypes, proving its compatibility with standard LTE network and its performance. The gateways can reduce drastically the end-to-end latency, as they avoid the time consumed by the backhaul and transport networks, with a very low trade-off