This master thesis project is about the systems integration of an indoor localizationsystem using Ultra Wideband Impulse Radio and a drone platform which uses theParrot AR.DRONE 2.0 along with the Robot Operating System (ROS). The goal wasto use o-the-shelf components to integrate an indoor localization system which can beused for energy modelling, indoor environmental panoramas and visual inspection oflarge buildings. The system architecture is explored, implemented and then subjectedto extensive testing. Experimental results of the openRTLS UWB system illustrateaccurate readings down to 2cm for Tag positions. The Parrot AR.DRONE 2.0 waschosen due to its low cost and agility; the open source drivers of ROS ensured modularsystem software, which has room for upgrades. The drone system can be used withoptional additional sensors, either attached internally or externally, to scan indoorareas and form environmental panoramas which can quantify ambient environmentalparameters such as temperature, humidity or pressure in harsh or hard to reach areas.The live video feed from the camera facilitates navigation in NLOS conditions. Thereal time ight path of the Parrot AR.DRONE 2.0 combined with the real time positiondata of the openRTLS UWB-IR system oers a unique insight into ne-grain data oflarge buildings.

Awareness of climate change and our environment is affecting the field of mobile communications. The challenge of reducing the carbon footprint and operating expenditures, while the demand for coverage and capacity is growing exponen-tially, is driving the trend of studying energy efficiency of mobile networks. Providing services in a resource efficient way have benefits both for the operator and the environment, which is why requirements on energy performance will be a part of the specifications of future 5G networks. In long term evolution (LTE) networks, indoor small cells are deployed inlarge volume to improve performance in areas with poor macro coverage or high traffic demand. This type of network topology, that consists of several types of access nodes, is called a heterogeneous network (HetNet). In this master thesis we study the energy efficiency of various HetNet deployments in a dense urban environment. The small cells deployments investigated are pico base stations and micro distributed antenna systems. Dense and sparse deployment strategies with varying transmit powers are compared. Furthermore, we investigate the potential for energy savings by setting the small cells into a low power sleep state under certain conditions. Both short sleep periods between transmissions, called discontineous transmission (DTX), and longer sleep cycles during periods of low activity is investigated.This thesis was carried out as a project at Ericsson Systems & Technology in Kista, Stockholm 2015. To be able to evaluate the energy consumption at network level, realistic models for the power consumption of various base station types had to be implemented into a static radio network simulator. Results show good performance of the considered HetNets but at a cost ofhigher power consumption than a macro only network. For example, a pico HetNet with twice the macro capacity consume 75% more energy over one day. However, results show that with DTX and sleep modes enabled, the daily energy consumption of the same HetNets is only 30% higher than the macro only network. Therefore, the main conclusion is that energy saving techniques will be of great importance for improving capacity without increasing network energyconsumption. / Medvetenhet om klimatförändringar i vår miljö påverkar även utvecklingen avmobila kommunikationssystem. Att minska utsläppen av CO2 från kommu-nikationsindustrin samt minska operatörernas kostnader samtidigt som kravenpå nätverkens kapacitet och täckning ökar är en utmaning. Denna utmaningdriver en ny trend att studera energi-effektivitet i mobila nätverk. Att levereratjänster på ett resurs-effektivt sätt är likväl lönsamt för operatörerna som förvår miljö. Detta är en anledning till att tydliga krav på nätverkens energiför-brukning nyligen har lagts till på listan över krav på framtida 5G nätverk. Bas-stationer med låg uteffekt, så kallade “small cells", är vanligt förekommande idagens Long Term Evolution (LTE) nätverk. De placeras ut i områden medantingen dålig täckning eller höga krav på data trafik. Sådana nätverk, sombestår av flera typer av access-noder, kallas för heterogena nätverk. I dettaprojekt studeras energi-effektiviteten av heterogena LTE nätverk i tätbebyggdstadsmiljö. Access-noderna som studeras är så kallade Pico-noder samt olika“distributed-antenna -system". Flera olika nätverks-topplogier undersöks samthur förändringar i access-nodernas ut-effekt påverkar energi-effektiviteten. Vi-dare studeras möjligheterna att spara energi genom att under vissa förutsät-tningar köra bas-stationer i ett läge av låg effektförbrukning. Dessa perioder kanvariera i storleksordningen av en mikrosekund varvid det kallas “discontineoustransmission", ända upp till flera timmar. De olika metoderna utvärderas medhjälp av ett statiskt simulerings-program för LTE nätverk. För att utvärderaenergiförbrukning har realistiska modeller för bas-stationernas effektförbrukningimplementerats i simulerings-programmet.

In this report, parts of the systems engineering of a spacecraft are presented. In 2014 the Royal Institute of Technology KTH initiated a new space technology and research platform, the KTH Space Centre. The first student project at KTH Space Centre was the MIST student satellite with the scope of the system design and construction of a real satellite due for launch in 2017. As part of the MIST project this bachelor thesis covers the mission analysis and parts of the system design. The system design is confined to the orbit lifetime and attitude perturbation analysis of the spacecraft and a complete analysis of the solar array illumination for the power system. The orbit lifetime was simulated in two different software, AGI’s Satellite Toolkit (STK), and NASA’s Debris Assessment Software (DAS). An approximate lifetime could be calculated from the two separate programs. The perturbation analysis was done by deriving parts of the governing equations of disturbance torques in the orbit. The analysis is confined to aerodynamic, magnetic dipole moment and gravity gradient torques. From these calculations the actuatio strength needed by the attitude control system was determined. The solar array configuration analysis was done by looking at the power generation and illumination of the solar panels in all of the possible flight attitudes. Following a computation of the power requirements a power budget was created and in conjunction with the complete configuration analysis of the solar array the optimal flight attitude was determined. The results of the system design analyses are compiled into a baseline design specification. The report is concluded with a discussion of the future work in the project and the lessons learned from the systems design process.

As enterprises continue to grow, as do the quantity of data and the complexity of storing thedata in meaningful ways, for which companies can later capitalize on (e.g. using analyticalsystems). For enterprises with an international presence it is common that a customer may alsobe a customer and supplier across borders and business areas. This complexity has created anumber of challenges in the ways many enterprises has previously managed their data and isespecially important to addresses for some of the enterprises most critical data entities (e.g.customer, supplier, chart of accounts, etc.) also known as master data. Master data management(MDM) is an umbrella term for a set of technology independent disciplines focusing on masterdata with the common goal of helping enterprises to achieve a single version of the truth for itsmaster entities, which in today’s enterprises are usually spread across heterogeneous datasources which has historically made it difficult for some enterprise to achieve a collective viewon, for example, who their customers are and if they are really meeting the market demands.The aim of this thesis to understand what challenges enterprises faces when attempting toimplement MDM with a primary focus on the governance aspect. An empirical study wasconducted in collaboration with NCC AB consisting of interviews with NCC employees,external consultants and literature study. The data obtained from the empirical study where thenused as basis for constructing a set of causal graphs to depict the issues identified and the causalfactors impacting them; along with recommendations obtained from the external consultants onhow to address some of these issues. The purpose is to deduce a number of success factors onhow to overcome these challenges in order to NCC to succeed with their MDM initiative.Results shows that MDM is still a somewhat new concept and where literature on the subject ismany times insufficient in details making it hard to understand how to begin. Furthermore, frominterviews with NCC employees three dominating problem areas were identified Common datadefinition, Success change initiative and Data quality, suggesting that most challenges involvedin implementing MDM is not technology related but rather organizational and governancerelated. It is imperative that the business is the one that drives the efforts within MDM initiativeas it is the business who best knows the problems they are facing, and how better managementof data can improve their ability to realise their business objectives. Furthermore, there needs tobe an appointed governance organization which will be responsible for instituting appropriatepolicies, metrics and roles with clearly defined areas of responsibility in order to instil a sense ofaccountability for the master entities across business areas.

The Smart Grid is the new, modernized, electrical distribution grid. It allows for many applications such as automation, reliability and efficiency of electrical distribution. A key feature of the smart grid is the AMI (Advanced Metering Infrastructure) which is the system that measures, collects and analyzes energy use.When designing an LV/MV AMI smart grid, one can use several different media types, two of those are PLC (Power Line Communication) and GPRS (General Packet Radio Service). Choosing one over another may have differences in both communication performance and overall economic cost.This thesis describes a method to optimally assign the smart meter communication devices in an AMI network to either the secondary substation via the power lines (PLC) or towards the head-end via GPRS. When assigned to the secondary substation, the data collected from the smart meters will be managed by a Data Concentrator or forwarded by a Gateway towards the head-end where a Virtual Data Concentrator would be located. As an alternative to PLC communication, GPRS can be used to wirelessly communicate between smart meters and the virtual data concentrator.The method proposed uses MatLab to read the users input data, such as smart meter and power line link locations. The read data then gets compiled into a network topology consisting of smart meter nodes and power line links between them. For easier comparisons, the network is then clustered into groups. The clustering is done using two methods, one fore PLC and another for GPRS.The cluster data will then be compared with the packet loss ratio data acquired from either simulations or other sources, stored in a repository. The comparisons, along with various constraints set by the user, will then determine if the communication is fit for use.If deemed fit for use, each type of communication have their CAPEX and OPEX costs calculated, based on the users input. This thesis will use data acquired from DSOs (Distribution System Operators) to analyze the costs of four network locations and determine the cheapest assignments for each one for various settings. / Smart Grids, eller smarta elnät, är framtidens moderna elektriska distributionsnät. Smarta elnät tillåter många tillämpningar som automatisering, tillförlitlighet och effektiv elektrisk distribution. En nyckelegenskap hos de smarta näten är funktionen AMI (Advanced Metering Infrastructure), ett system som samlar ihop, mäter och analyserar energiförbrukning.När man designar ett låg- eller mellanspännings AMI elnät kan man utnyttja ett flertal mediatyper, två av dem är PLC (Power Line Communication) eller GPRS (General Packet Radio Service). Att välja den ena framför den andra kan leda till olikheter både när det gäller kommunikationsprestanda och den ekonomiska kostnaden.Detta examensarbete beskriver en metod för att på ett optimalt sätt tilldela smarta elmätare i ett AMI elnätverk till antingen det sekundära ställverket via de elektriska ledningarna (PLC) eller till huvudcentralen (head-end) trådlöst via GPRS. När mätarna tilldelas det sekundära ställverket samlas data från dem ihop av antingen en Data Concentrator (DC) eller en Gateway (GW) . En Gateway skickar därefter datan vidare till huvudcentralen där en Virtual Data Concentrator (VDC) finns. Alternativt utnyttjas GPRS för att trådlöst kommunicera mellan de smarta elmätarna och VDC.Metoden som föreslås utnyttjar MATLAB för att avläsa användarens indata, som till exempel positioner till de smarta elmtarna och de elektriska elledningarna som länkar dem med det sekundära ställverket. Den avlästa indatan används till att bilda en elnätverkstopologi bestående av smarta elmätare och elledningarna. För att enklare jämföra de skapade topologierna med simulerade generella topologier, grupperas nätverket i kluster. Klustermetoden skiljer sig mellan PLC och GPRS.Klusterdatan används sedan för att jämföra packet loss ratio erhållen från antingen simuleringar eller från andra källor. Jämförelserna avgör sedan huruvida kommunikationen med sagd mediatyp upprätthåller användarens kommunikationskrav.Om kommunikationsmöjligheterna för topologin anses vara tillräcklig, kommer varje kommunikationstyp att få sin kostnad uträknad utifrån CAPEX och OPEX. I detta examensarbete utnyttjas kostnader och topologidata erhållen från DSO’s (Distribution System Operators) för att analysera kostnaderna för fyra elnätverk och avgöra de billigaste tilldelningarna för vardera utifrån olika insättningar.

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The new electronic devices and their constant progress brought up the chal-lenge of improving the speech recognitions systems. Indeed, people tend touse more and more hands-free devices that are inclined to be used in noisyenvironments. The evolution of Machine Learning techniques has been very ef-ficient for the last decade and speech recognition system using those techniquesappeared. The main challenge of Automatic Speech Recognition systems nowa-days is the improvement of the robustness to noise and reverberations. DeepLearning methods were used to either improve the speech representations ordefining better distributions probabilities. The problem we face is the drop inthe performance of ASR systems when inputs are noisy. The general approachis to define novel speech features that are more robust using Deep Neural Net-works. To do so we got through different implementations as the incorporationof autooencoders in the MFCC block diagram or the deep denoising autoen-coders with different pre-training methods. The final solution is a system thatbuild more robust features from noisy MFCC. Our input is the demonstrationthat a denoising system using q quantized DDAEs defined by the clustering ofthe training data using K-means is more efficient than one denoising systemapplied to the whole data. The performance gained using such a system is of 2to 3% in terms of phone error rate and might be improved using more trainingdata and better tuned NN parameters.

After many years focused on speech signal processing, the research in audio processing started to investigate the field of music processing. Music Information Retrieval is a very new topic steadily growing since a few years as music is more and more part of our daily life, particularly thanks to the new technologies like mp3 players and smartphones. Moreover, with the development of electronic music and the huge improvements in computational power, new instruments have appeared such as virtual instruments, bringing with them new needs concerning the availability of sounds. One main necessity which came with these novel technologies is to have a user friendly system to make it easy for the users to have access to the whole range of sounds the device can offer.  In this thesis, the purpose is to implement a smart automatic classification of synthesizer sounds based on audio descriptors without any human influence. Hence the study first focus on what is a musical sound and what are the main characteristics of synthesizer sounds that need to be extracted using wisely chosen audio descriptors extraction. Then the interest moves to a classifier system based on the Self-Organizing Map model using unsupervised learning to match with the main purpose to avoid any human bias and use only objective parameters for the sounds classification. Finally the evaluation of the system is done, showing that it gives good results both in terms of accuracy and time efficiency.

Trends in research show the interest of autonomously driving cars. One topic within autonomousdriving is path following, which is the topic studied in this project. More specically, development and implementation of model predictive control for path following. A numberof model predictive controllers are developed. Their path following performance is studiedand evaluated in simulations on at, banked, and sloped road surfaces. The eects of usingdierent levels of prediction model complexities are studied, and also the eects of two wheelsteering compared to four wheel steering. The main focus with the design of the controller isfor it to keep the vehicle as close as possible to the path while the ride comfort is maintainedat an acceptable level. The simulation results show the advantages of using more complex predictionmodels, as well as the advantages of four wheel steering. The studies of the dierentmodel predictive control designs, result in that the most suitable controller is implemented,and the path following performance with the KTH Research Concept Vehicle is studied. Thestudies of the path following with the KTH Research Concept Vehicle show the great potentialof using model predictive control for path following, and further improvements are proposed. / Trender inom forskning visar att det nns ett stort intresse for sjalvkorande bilar. Ett omradeinom sjalvkorande fordon ar \path following", vilket ar det som studeras i detta projekt. Mer specikt utveckling och implementering av \model predictive control" for \path following".Ett antal kontroller utvecklas och deras prestanda testas pa bade platta och sluttandeunderlag. Eekterna av att anvanda olika nivaer av komplexitet hos prediktionsmodellernasoch tvahjulsstyrning jamfort med fyrhjulsstyrning studeras. Huvudfokuset med designenpa kontrollerna ar att halla fordonet sa nara den tankta korvagen som mojligt samtidigtsom akkomforten halls pa en acceptabel niva. Simuleringsresultaten visar fordelarna med attanvanda en mer komplex prediktionsmodell och fyrhjulsstyrning. Studierna av de olika kontrollernaresulterade i att den mest lampliga implementerades och \path following" prestandanmed KTH Research Concept Vehicle studerades. Resultaten med KTH Research Concept Vehiclevisade stor potential och ytterligare forbattringar foreslas.

In this thesis, a top-down hierarchical framework is proposed to deal with multiagentsymbolic motion planning and control. Agents are assigned a distributable globalmission, and are partitioned into leaders and followers. The global mission is distributedamong the followers and each one synthesizes a discrete motion plan. By exploitingthe concept of network controllability, an open-loop optimal control law is synthesizedcentrally and executed in a distributed manner. This control law guarantees the concurrentexecution and fulfillment of the followers’ discrete motion plans. Simulations areperformed to verify the proposed control law both for single- and multi-leader, leaderfollowernetworks.