Towards a new cloud-based planning and optimization methodology for mobile communication networks

The great concern of telecommunication operators to offer high-quality services to their customers requires a constant care with the state of the networks. These networks can present some problems that imply that the experience offered to customers is unsatisfactory. In order to monitor these situations, operators collect, on a fairly regular basis, data, like drive tests, that allow them to monitor and correct minor issues. This thesis takes advantage of the data collected and uses it in network planning in order to precisely obtain the coverage estimation of a network. In order to automate failure correction mechanisms, a totally automatic propagation model is presented, which precisely describes the state of the network, allowing it to be used for network planning and optimisation. After its implementation, the model was compared to a second model, generated through Artificial Intelligence, which is completely agnostic to all telecommunications knowledge. These models, for the considered scenarios, reached average absolute errors between estimated and actual values of 6.1 dB with a standard deviation of 4 dB. The existence of several real telecommunication network measures and their evolution to Multiple Input, Multiple Output (MIMO) systems motivated not only the investigation on the coverage impact with the change from a Single Input, Single Output (SISO) to a MIMO system, but also the investigation on the reduction of complexity of the receivers used in MIMO systems. The closer the Bit Error Rate performance of the receiver is to the Matched Filter Bound, the smaller will be the reduction in the coverage area with the transition from a SISO system to a MIMO system.A grande preocupação dos operadores de telecomunicações em oferecerem serviços de alta qualidade aos seus clientes leva a um constante cuidado com o estado das redes. Estas redes podem apresentar alguns problemas que implicam que a experiência oferecida aos clientes seja desagradável. De forma a monitorizar estas situações, os operadores recolhem, com bastante regularidade, dados, como "drive tests", que lhes permitem avaliar e corrigir pequenos problemas. Esta tese aproveita os dados recolhidos e utiliza-os no planeamento da rede de forma a obter fielmente a estimativa de cobertura de uma rede. De forma a automatizar mecanismos de correção de falhas, é apresentado um modelo de propagação completamente automático, que descreve de forma precisa o estado da rede permitindo que seja aplicado em algoritmos de planeamento e otimização da rede. Após a sua implementação, este modelo foi comparado com um segundo modelo, gerado através de inteligência artificial, que é completamente agnóstico a todo o conhecimento de telecomunicações. Estes modelos, para os cenários estudados, atingiram erros absolutos médios entre os valores estimados e os valores reais de 6.1 dB com um desvio padrão de 4 dB. A existência de diversos dados reais das redes de telecomunicações e a evolução para os sistemas "Multiple Input", "Multiple Output" (MIMO) motivou não só a investigação no impacto da cobertura com a mudança de um sistema "Single Input", "Single Output" (SISO) para um sistema MIMO, mas também a investigação na redução de complexidade dos recetores utilizados em sistemas MIMO. Quanto mais próxima a "Bit Error Rate performance" do recetor estiver do "Matched Filter Bound", menor será a redução na área de cobertura com a transição de um sistema SISO para um sistema MIMO

Cloud-Based Implementation of an Automatic Coverage Estimation Methodology for Self-Organising Network

UIDB/EEA/50008/2020One of the main concerns of telecommunications operators is related to network coverage. A weak coverage can lead to a performance decrease, not only in the user experience, when using the operators' services, such as multimedia streaming, but also in the overall Quality of Service. This paper presents a novel cloud-based framework of a semi-empirical propagation model that estimates the coverage in a precise way. The novelty of this model is that it is automatically calibrated by using drive test measurements, terrain morphology, buildings in the area, configurations of the network itself and key performance indicators, automatically extracted from the operator's network. Requirements and use cases are presented as motivations for this methodology. The results achieve an accuracy of about 5 dB, allowing operators to obtain accurate neighbour lists, optimise network planning and automate certain actions on the network by enabling the Self-Organising Network concept. The cloud implementation enables a fast and easy integration with other network management and monitoring tools, such as the Metric platform, optimising operators' resource usage recurring to elastic resources on-demand when needed. This implementation was integrated into the Metric platform, which is currently available to be used by several operators.publishersversionpublishe

A novel way to automatically plan cellular networks supported by linear programming and cloud computing

With the increasing number of mobile subscribers worldwide, there is a need for fast and reliable algorithms for planning/optimization of mobile networks, especially because, in order to maintain a network’s quality of service, an operator might need to deploy more equipment. This paper presents a quick and reliable way to automatically plan a set of frequencies in a cellular network, using both cloud technologies and linear programming. We evaluate our pattern in a realistic scenario of a Global System for Mobile communications protocol (GSM) network and compare the results to another already implemented commercial tool. Results show that even though network quality was similar, our algorithm was twelve times faster and used four times less memory. It was also able to frequency plan seventy cells simultaneously in less than three minutes. This mechanism was successfully integrated in the professional tool Metric, and is currently being used for cellular planning. Its extension for application to 3/4/5G networks is under study.info:eu-repo/semantics/publishedVersio

Online Mapping and Perception Algorithms for Multi-robot Teams Operating in Urban Environments.

This thesis investigates some of the sensing and perception challenges faced by multi-robot teams equipped with LIDAR and camera sensors. Multi-robot teams are ideal for deployment in large, real-world environments due to their ability to parallelize exploration, reconnaissance or mapping tasks. However, such domains also impose additional requirements, including the need for a) online algorithms (to eliminate stopping and waiting for processing to finish before proceeding) and b) scalability (to handle data from many robots distributed over a large area). These general requirements give rise to specific algorithmic challenges, including 1) online maintenance of large, coherent maps covering the explored area, 2) online estimation of communication properties in the presence of buildings and other interfering structure, and 3) online fusion and segmentation of multiple sensors to aid in object detection. The contribution of this thesis is the introduction of novel approaches that leverage grid-maps and sparse multi-variate gaussian inference to augment the capability of multi-robot teams operating in urban, indoor-outdoor environments by improving the state of the art of map rasterization, signal strength prediction, colored point cloud segmentation, and reliable camera calibration. In particular, we introduce a map rasterization technique for large LIDAR-based occupancy grids that makes online updates possible when data is arriving from many robots at once. We also introduce new online techniques for robots to predict the signal strength to their teammates by combining LIDAR measurements with signal strength measurements from their radios. Processing fused LIDAR+camera point clouds is also important for many object-detection pipelines. We demonstrate a near linear-time online segmentation algorithm to this domain. However, maintaining the calibration of a fleet of 14 robots made this approach difficult to employ in practice. Therefore we introduced a robust and repeatable camera calibration process that grounds the camera model uncertainty in pixel error, allowing the system to guide novices and experts alike to reliably produce accurate calibrations.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113516/1/jhstrom_1.pd

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

Efficient cloud-based cellular planning algorithms for 3G and 4G networks

In mobile network deployments of growing size, the optimum and fast planning of radio resources are a key task. Cloud services enable efficient and scalable implementation of procedures and algorithms. In this dissertation, a cloud-based planning system for 3G and 4G networks is presented, using Amazon Web Services (AWS) for cloud implementation. It extracts configuration and performance data from the network, enabling to accurately estimate cells coverage, identify neighbouring cells and optimally plan Scrambling Codes (SC) in an UMTS network and Physical Cell Identity (PCI) in LTE networks. This system is integrated in a Software-as-a-Service monitoring and planning tool Metric, owned by Multivision, allowing for an easy and efficient allocation of the network resources. The system operation is demonstrated in a small canonical scenario for SCs, a small realistic scenario of PCIs cluster planning, taking less than 0,6 seconds to perform the planning. For a realistic 3G scenario with 12 484 unplanned cells, the planning of SCs is efficiently achieved, taking less than 8 seconds, and guaranteeing no collisions between first order neighbouring cells.Nas implementações de redes móveis grande escala, o planeamento otimizado e rápido dos recursos de rádio é uma tarefa fundamental. Os serviços em cloud permitem a implementação eficiente e escalável de padrões e algoritmos. Nesta dissertação, é apresentado um sistema de planeamento baseado em cloud para redes 3G e 4G, fazendo recurso à Amazon Web Services (AWS) para implementação em cloud. Este sistema extrai dados de configuração e desempenho da rede, o que permite estimar com precisão a cobertura das células, identificar células vizinhas e planear de forma eficiente os Scrambling Codes (SC) em redes UMTS e Physical Cell Identity (PCI) em redes LTE. Este sistema está integrado no Metric, uma ferramenta de planeamento e monitorização de Software-as-a-Service, propriedade da Multivision, permitindo uma alocação fácil e eficiente dos recursos da rede. A operação do sistema é demonstrada num pequeno cenário canónico para SCs, um pequeno cenário realista de um cluster de células pertencentes a uma rede LTE, onde se pretende planear os seus PCIs. O algoritmo executa um planeamento ótimo deste cluster em menos de 0,6 segundos. Para um cenário 3G realista com 12 484 células não planeadas, a alocação dos SCs é realizada com eficiência, levando menos de 8 segundos e garantindo que não existem colisões entre as células vizinhas de primeira ordem

Satellite power system: Concept development and evaluation program. Volume 3: Power transmission and reception. Technical summary and assessment

Efforts in the DOE/NASA concept development and evaluation program are discussed for the solar power satellite power transmission and reception system. A technical summary is provided together with a summary of system assessment activities. System options and system definition drivers are described. Major system assessment activities were in support of the reference system definition, solid state system studies, critical technology supporting investigations, and various system and subsystem tradeoffs. These activities are described together with reference system updates and alternative concepts for each of the subsystem areas. Conclusions reached as a result of the numerous analytical and experimental evaluations are presented. Remaining issues for a possible follow-on program are identified

Aeronautical engineering: A continuing bibliography with indexes (supplement 227)

This bibliography lists 418 reports, articles, and other documents introduced into the NASA scientific and technical information system in May, 1988