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  • 1.
    Prokic, Theodoros
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Antenna Design for Angle of Arrival Measurement in Access Control Applications2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The Bluetooth direction finding working group proposed functionalities to the Bluetooth core that can realize Angle of Arrival estimations using interferometry. The technology can be employed to develop new access control applications. Following previous findings in Englund (2018), the purpose of this project is to investigate the feasibility of such systems when antennas are being used. The goal is to design a matchbox size antenna array which can be used by the system to distinguish between two sides in an inside-outside scenario. A number of antennas were designed, simulated and tested on a prototype. While the simulations results were consistent with the theory, the prototype measurements were not. However, it is shown that it is possible to estimate between inside and outside.

  • 2.
    Jafeth Villasana Tinajero, Pedro
    KTH, School of Electrical Engineering and Computer Science (EECS).
    New Variants of Nonnegative Matrix Factorization with Application to Speech Coding and Speech Enhancement2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis, new variants of nonnegative matrix factorization (NMF) based ona convolutional data model, -divergence and sparsication are developed andanalyzed. These NMF variants are collectively referred to as -CNMF. Commonsparsication techniques such as L1-norm minimization and elastic net arediscussed and a new regularizer is proposed. It is shown that the new regularizer,unlike the above-mentioned sparsication techniques, has control overthe number of active bases in the NMF dictionary. Moreover, the -CNMF isextended to multichannel signals: it learns a common dictionary by exploitingthe correlation between channels through a multichannel coecient matrix. Asa result, an algorithm for source separation based on multichannel -CNMF isdeveloped. The algorithm is further tested in a multilayer setting, in which thefrequency-shifted coecient matrices serve as input to the next higher layer.Finally, three variants of the algorithm are evaluated in the context of speechenhancement, focusing on the problem of speech extraction from complex auditoryscenes. Figures obtained from the SiSEC 2016 data show that the proposedalgorithms perform comparably or better than the state of the art.

  • 3.
    Yu, Liangcheng
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Towards Learning for System Behavior2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Traditional network management typically relies on clever heuristics to capture thecharacteristics of environments, workloads in order to derive an accurate model.While such methodology has served us well in early days, it is challenged by thegrowing intricacies of modern network design from various dimensions: the rocketingtraffic volumn, proliferation of software applications and varied hardware, higheruser-specific Quality of Experience (QoE) requirements with respect to bandwidthand latencies, overwhelming number of knobs and configurations and so forth. Allthese surging complexity and dynamics pose greater difficulty on us to understandand derive management rules to reach global optimum with heuristics that fits thedynamic context. Driven by the pulls of the challenges and encouraged by the successin machine learning techniques, this work elaborates on augmenting adaptive systemsbehaviors with learning approaches. This thesis specifically investigates the use caseof the packet scheduling. The work explores the opportunity to augment systemsto learn existing behaviors and explore custom behaviors with Deep ReinforcementLearning (DRL). We show the possibility to approximate the existing canonicalbehaviors with a generic representation, meanwhile, the agent is able to explorecustomized policy that are comparable to the state-of-art approaches. The resultsdemonstrate the potentials of learning based approaches as an alternative to canonicalscheduling approaches.

  • 4.
    She, Baoqing
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Deep Learning for Error Prediction In MIMO-OFDM system With Maximum Likelihood Detector2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    To increase link throughput in multi-input multi-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems, transmission parameters such as code rate andmodulation order are required to be set adaptively. Therefore, block error rate (BLER)becomes a crucial measure which illustrates the quality of the link, thus being used in LinkAdaptation (LA) to determine the transmission parameters. However, existing methods topredict BLER are only valid for linear detectors, e.g. Minimum Mean Square Error (MMSE)detector [1]. In this thesis, we show that signal-to-interference-plus-noise ratio (SINR)exists in MIMO-OFDM system with MLD (maximum likelihood detection). Then, a machinelearning based method with Deep Neural Network (DNN) is proposed to analyze therelation between input features (channel matrix, modulation and coding scheme (MCS),signal-to-noise ratio(SNR)) and labels (CRC). Results shows that the classification of DNNis good. However, there is still deviation when compared output of DNN with thesimulated BLER.

  • 5.
    Ravi, Akshaya
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Design of equalization filter for non-linear distortion of the loudspeaker array with listener's movement2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The importance of the real-time virtual auditory environment is dependent on the fidelity of reproducing the sound. The loudspeaker array provided with its ideal response is suitable for the sound reproduction. However, there exists frequency and phase distortions in the loudspeaker response that cause audible artifacts at the listener's ears. Therefore, this non-ideal response of the loudspeaker is equalized by an equalization filter before their use in the immersive audio environment. The frequency response of the loudspeaker is dependent on the listener's position and hence equalization must be performed at each of their positions. Whereas, to measure the frequency response at all such position is troublesome. In this thesis, the frequency response of the loudspeakers is measured for selected listener's position with respect to the loudspeaker array. The frequency responses at the unmeasured positions are estimated using interpolation techniques. The equalization routine for the loudspeaker is performed in this thesis by considering the linear and non-linear distortions individually. The measured frequency response is simplified by the inverse-distance law. These simplified responses or the deviations are representing the non-linear distortions of the loudspeaker response. This deviation is equalized by the design of a mathematical model. This model also achieves the interpolation of the frequency response and ensures the equalization of the deviations at all potential position of the listener. Here, the mathematical model is designed as the former step to the linear equalization filter. The measurements and analysis in this thesis are focused to equalize 36 loudspeakers mounted at the horizontal plane of the 60-channel loudspeaker array and accounting for the listener's movement inside the array. The equalized deviations are statistically analyzed using ANOVA and the performance of the model parameters is evaluated.

  • 6.
    Wang, Xianghan
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Economic Viability Analysis of Remote Take-Over Use Cases in Underground Mining2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Remote take-over means the vehicles are able to drive automatically and can be also operated by the operators remotely. The operators will just play the supervisory role when the vehicles drive automatically, and when the operation is beyond vehicles’ automation area or when some urgent situations happen, the remote operators will take over the control and operate the vehicles remotely.

    This thesis is intended to find out the economic viability of the combination of current mobile communication technologies and heavy industrial mining environment. An economic viability analysis of remote take-over system based on cellular network in underground mining is presented.

    The main cost of this solution includes vehicle Capex & Opex, network Capex & Opex, as well as the remote control station cost. And the savings mainly result from the enhanced productivity, which leads to reduced vehicle units and operators. Cost-Benefit Analysis (CBA) approach is used to evaluate the viability of the investment, which helps to predict if the benefit will outweigh the costs of and how much the difference will be. This approach takes time value of money into account, thus cash flows of both benefits and costs will be expressed in terms of net present value (NPV).

    Kankberg mine of Boilden is set as a model mine to study in Case I. The result shows that investment should be done in the 2nd year and be kept until the end of mine’s life. However, you can still make investment in the 6th year and still make a profit.

    Case II is the same with Case I, but with investment done in year 1. The relative merits by using different purchase methods Outright purchase vs. Finance lease is studied. The recommendation will vary with the choice of key performance indicators, including net present value (NPV), payback period (PBP) or both. NPV is the difference between the present value of cash inflows and present value of cash outflows. PBP is the expected length of time before an investment will be returned.

    Case III has been set as a mine which uses another mining method (Room and Pillar), and the daily production is the same with case I, to know which type of mine will benefit more from remote take-over system. Also, we aim to know which part of the cost model differs the most, so that mining company can focus on that part to reduce the cost.

    The purpose of the setting of use case IV is to know what will happen when investing remote take-over system to the same type of mine, with different daily productions.

    After the use cases study, sensitivity analysis has also been conducted, to know how the change of an independent parameter would influence the final outcome.

  • 7.
    Kawahara, Alberto
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Improving Residential In-building Energy Performance for Multi-operator and Multi-standard Radio Access in Distributed Antenna Systems (DAS)2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Good signal in indoor environments has always been one of the mobile operator’s main challenges. The situation gets even more complex when dealing with new energy-efficient buildings that insulate the heat inside the building but at the same time causes higher losses from the macro base stations. In this scenario, indoor solutions are required to overcome this problem. Nowadays, there are two main indoor solutions: Distributed Antenna Systems (DAS) and small cells.

    This thesis focuses on DAS solutions and investigates the power consumption difference between the two main architectures: Passive and Active/Hybrid DAS. The evaluation is made by measuring the power consumption of the active components and adding them to the already existing Base Station power consumptions models. Power consumption measurements were performed for four commercial bands: 900, 1800, 2100, 2600 MHz. Power consumption and system capacity trade-off between the passive and active DAS solutions is also presented. The capacity analysis is focused on LTE and applied to a real case study: Norra Tornen residential building. Final results show that up to 75% of the indoor power consumption can be saved when implementing an active DAS solution without affecting the service quality.

  • 8.
    Montzka, Thomas
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Investigating the Potential of Using SOM on Audit Changed Trades2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    During the last 20 years, operational risk has been identified as an considerablerisk that needs to be tracked and handled, particular in the financial industry.The Basel Committee on banking supervision is a global cooperation thatsets standard regulations for banking corporations. The framework of Basel IIcontains an explicit definition and proposed calculation about the size of riskcapital needed. Beside this, the responsibility of how to manage and lower theoperational risk is still in the hands of the operating companies.The company Handelsbanken has identified that their operational risk riseswhen trades become the object of Audit Change. Because of the large numberof trades every day that are Audit Changed, the motivation is to automatevisualization and categorization of the trades, so focus can be given to thosetrades that are associated with higher risk.This thesis has been carried out to investigate the usage of the Self-OrganizingMaps (SOM), an unsupervised Machine Learning algorithm, to explore its potentialin gaining information from the trades that have been Audit Changed.The results reveal that SOM have several potential applications for Handelsbankento develop around the trades done in their business, especially withinAudit Changed but also in general for categorizing trades done in the company.

  • 9.
    Zhang, Zheyu
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Machine Learning for Metamorphic Testing2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Test oracle is a mechanism used to validate all the functionalities ofsoftware under test. However, the lack of test oracle makes the processof software testing difficult. Metamorphic testing is a state of artapproach for automated software testing without test oracles basedon metamorphic relations. Metamorphic relations are a set of propertiesbetween inputs and outputs that a software could have. However,it is usually difficult to identify metamorphic relations for unknownprograms. This thesis aims for automatic generation of metamorphicrelations by utilizing machine learning algorithms with the methodrandom walk kernel using input from control flow graphs. By applyingKanawala et al. [1] previous work in our targeted system environment,we encountered a series of difficulties, which we also describein this thesis. It is important to introduce an alternative solution forour test suite that is working. The performance of our model is evaluatedby different measures including area under the receiver operatingcharacteristic curve and mean squared error. The results show promisingapplications of automatically predicting metamorphic relations forunknown programs. The study was conducted on software system inthe telecommunicaiton domain.

  • 10.
    Casas Moreno, Xavier
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Noise modelling for high-throughput super-resolution microscopy2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Super-resolution fluorescence microscopy is an emerging imaging fieldthat aims at breaking the di↵raction barrier of light based on state transitionin fluorescent molecules. Current challenges in the existing approachare to achieve large field of views, fast recordings and increasing the imagequality.The Advanced Bio-Imaging group at the Science for Life Laboratory inStockholm invented the Molecular Nanoscale Live Imaging with SectioningAbility (MoNaLISA), a microscope that reaches high spatial resolution(45-65 nm) with low light intensities (kWcm

  • 11.
    Enqvist, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Physical Layer Algorithms for Intrabody Nano-Communications2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis we develop a mathematical model of the physical layerfor an in-body nano-machine (NM) communication. The purpose isfinding what modulation and detection schemes are suitable for applicationin the body and discovering what factors limit the feasiblecommunication distance. Inside the body, the NMs use small antennasoperating in the THz frequency spectrum. They have limited energyresources and low computational power and must fulfill their task ina challenging environment with large absorption losses. By employingon-off-keying pulse modulation and small integrating receiver circuits,it is possible to consume minimal energy while being able communicateover small distances of a few mms. This is shown througha simulation of a point to point nano-communication link. We alsodemonstrate how connecting several NMs in a network and employingamplify-and-forward relaying can facilitate communication overlarger distances. The final analysis shows that communication insidethe body is possible over short distances, a few mms at most, but transmittinga signal strong enough to connect aNMnetwork to an externalterminal may prove challenging.

  • 12.
    Zhou, Linghui
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Polar Codes for Identification Systems2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Identication systems are ubiquitous, for example, biometric identication systemswith ngerprints and Face IDs, etc. Basically, the identication problemconsists of two steps. The enrollment phase where the user's data are captured,compressed and stored, for example taking the ngerprint or capturing some importantfeatures of your face. In the identication phase, an observation, yourngerprint or your face, is compared with the stored information in the databaseto provide an armative answer. Since the system involves many users, bothstoring and searching for the correct user is challenging.This project aims to implement compression and identication algorithms forthe high dimensional identication system which includes M users. Polar codesare employed to be the main toolbox. Firstly, we implement polar codes for thesource compression and then design corresponding identication mappings. Thesource compression can be seen as the channel decoding of polar codes. In theidentication phase, the observation can be seen as the side information, so wewill consider using Wyner-Ziv coding for polar codes to reconstruct and identify.In the next step, we will implement polar codes for two-layer Wyner-Zivcoding for identication systems. This will enable us to store the compresseddata in separate databases and do the reconstruction in two stages. With theenrollment mapping and identication mapping implemented, we will evaluatethe performance of the designed identication systems, such as identicationerror rate and complexity. Some possible further directions would be to implementmore advanced algorithms such as simplied or fast simplied successivecancellation encoding in source coding and universal decoding in identication.

  • 13.
    Sedin, Jonas
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    A comparison of Polar Code Constructions and Punctur-ing methods for AWGN and Fading channels2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Today 5G and other wireless standards are being developed for the future of our society. The different use-cases of future wireless services are going to be ever-more demanding, whether it is vehicular communication or low-powered sensor networks. High-rate, ultra-reliable and low-power are future requirements that will also affect the coding schemes being used. A relatively recent coding scheme, called polar codes, has the potential to fulfill all of these requirements if the coding scheme applied is well-designed. In this thesis we will be focusing on practical algorithms for implementation of polar codes at medium-sized block-lengths.

     

        Polar codes are very different from other modern coding schemes. The code construction is rather unique in that they are dependent on the underlying channel, where the code construction can change with the Signal-to-Noise-Ratio of the AWGN channel. The puncturing of polar codes is also non-trivial compared to other coding schemes. Since the Polar Codes are dependent on the underlying channel, the fading channel performance is thus important to consider. In this thesis we aim to show through simulations how these different concepts affect the Block Error Rate (BLER) performance. Specifically, we compare how code constructions compare over the AWGN channel, how code construction affects the BLER performance with puncturing and how puncturing affects the performance over fading channels. We find that an appropriate code construction is very important for optimal performance over the AWGN channel with puncturing, in our case using Gaussian Approximation. We also find that different puncturing methods have vastly different performances for different rates over the AWGN and Rayleigh fading channel and that applying an interleaver is very important for optimal performance.

  • 14.
    Sarah, Annisa
    KTH, School of Information and Communication Technology (ICT).
    Analysis of 5G Mobile Broadband Solutions in Rural and Remote Areas: A Case Study of Banten, Indonesia2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Providing a broadband access anytime and anywhere is one of the visions of the future 5G network. However, deploying a reliable network connection in remote/rural areas has been a challenging task because of its wide area that needed to be covered and a low density of user compared to urban area. Different geography and traffic condition may need different system solution. In this thesis, we analyze several solutions to providing a broadband access network in practical remote and rural area in Banten, Indonesia: Leuwidamar (remote) and Panimbang (rural). Two approaches are discussed, first one is fulfilling futuristic traffic demand by having LTE System, and the second one is by having 5G System. We included three key technology components in a 5G network: occupying wide bandwidth in high frequency, applying UE-Specific Beamforming, and implementing Carrier Aggregation (CA) scheme. We also account a rain attenuation when deploying a network in high operating frequency, since Indonesia has a high rain rate thus it is important to be considered. We compared five cases of solution: Case 1 is Single Carrier (SC) LTE 1.8 GHz system; Case 2 is Carrier Aggregation (CA) LTE 1.8 GHz + 2.6 GHz; Case 3 is SC 5G 15GHz; Case 4 is SC 5G 28 GHz; Case 5 is CA LTE 1.8 GHz + 5G 15 GHz. Basedon the evaluation, in Leuwidamar scenario, Case 5 gives us the least number of BS needed in order to meet the futuristic requirement with only 1.6 x densification from the current network. In Panimbang, the least number of BS neededis offered by two cases, Case 3 and Case 5 without any additional BS needed(1x densification). However, the solution with the lowest energy consumption for both area is Case 3. This is due to the fact that the carrier aggregation scenario needs additional power to generate the second system. Furthermore, if we introduce cell DTX ability in the 5G network, the Case 3 can give us impressive amount of energy saving, with 97% saving for Leuwidamar and 94% saving for Panimbang, compared to Case 1 solution without any DTX Capability.

  • 15.
    Patil, Darshan
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Block Diagonalization Based Beamforming2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With increasing mobile penetration multi-user multi-antenna wireless communication systems are needed. This is to ensure higher per-user data rates along with higher system capacities by exploiting the excess degree of freedom due to additional antennas at the receiver with spatial multiplexing. The rising popularity of "Gigabit-LTE" and "Massive-MIMO" or "FD-MIMO" is an illustration of this demand for high data rates, especially in the forward link. In this thesis we study the MU-MIMO communication setup and attempt to solve the problem of system sumrate maximization in the downlink data transmission (also known as forward link) under a limited availability of transmit power at the base station. Contrast to uplink, in the downlink, every user in the system is required to perform interference cancellation due to signals intended to other co-users. As the mobile terminals have strict restrictions on power availability and physical dimensions, processing capabilities are extremely narrow (relative to the base station). Therefore, we study the solutions from literature in which most of the interference cancellation can also be performed by the base station (precoding). While doing so we maximize the sumrate and also consider the restrictions on the total transmit power available at the base station. In this thesis, we also study and evaluate different conventional linear precoding schemes and how they relate to the optimal structure of the solution which maximize the effective Signal to Noise Ratio (SINR) at every receiver output. We also study one of the suboptimal precoding solutions known as Block-diagonalization (BD) applicable in the case where a receiver has multiple receive antennas and compare their performance. Finally, we notice that in spite of the promising results in terms of system sumrate performance, they are not deployed in practice. The reason for this is that classic BD schemes are computationally heavy. In this thesis we attempt to reduce the complexity of the BD schemes by exploiting the principle of coherence and using perturbation theory. We make use of OFDM technology and efficient linear algebra methods to update the beamforming weights in a smart way rather than entirely computing them again such that the overall complexity of the BD technique is reduced by at least an order of magnitude. The results are simulated using the exponential correlation channel model and the LTE 3D spatial channel model which is standardized by 3GPP. The simulated environment consists of single cell MU-MIMO in a standardized urban macro environment with up to 100 transmit antennas at the BS and 2 receive antennas per user. We observe that with the increase in spatial correlations and in high SNR regions, BD outperforms other precoding schemes discussed in this thesis and the developed low complex BD precoding solution can be considered as an alternative in a more general framework with multiple antennas at the receiver.

  • 16.
    Ramadhani, Uri Arta
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Evaluation of the Profitability of Quality of Experience-based Resource Allocation Deployment in LTE Network: A Techno-economic Assessment based on Quality of Experience in Video Traffic2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In the current mobile telecommunication market, with slow growth in mobile subscriptions and increasing traffi demand, each mobile operator needs to manage their customer loyalty in order to maintain position in the market. To retain their customer's loyalty, the user quality of satisfaction needs to be preserved. Integrating a Quality of Experience (QoE) approach into a radio resource scheduling scheme can be a means to improve user quality of satisfaction to a service. However, the enhancement of existing resource allocation management to support a QoE-based resource scheduling scheme needs a careful consideration since it will impact the mobile operator's investment cost. A profitability assessment of QoE-based resource allocation is required as a basis for the mobile operator to forecast their potential benefit of QoE-based resource scheduling deployment.

    This thesis investigated the profitability of deploying QoE-based radio resource management (RRM) in terms of revenue loss compared to proportional fair (PF) scheduling, a widely used resource allocation scheme, in delivering a streaming video service. In QoE-based RRM, a buffering percentage experienced by a user was considered in the resource allocation decision process. The two scheduling schemes were simulated in different network configurations. User satisfaction was quantified in terms of mean opinion score. Given the degree of satisfaction for each user, a number of users who would be likely to churn was obtained. A cost-benefit assessment was then conducted by predicting revenue loss due to customer churn.

    The results from the simulation and cost analysis show that although QoE-based resource scheduling provides users with a higher degree of satisfaction for more base stations, the utilization of a QoE-based resource scheduler does not offer significant benefit to the network operator with regard to revenue loss and deployment cost when compared to a PF scheduler. This outcome indicates that if the business target is to reduce customer churn, then the operator should utilize a PF scheduler for their RRM scheme.

  • 17.
    Luan, Dehan
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fundamental Performance Limits on Time of Arrival Estimation Accuracy with 5G Radio Access2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    5G radio access technology stimulates new use cases and emerging businessmodels, evolving the world to become a fully mobile and connected networksociety, expected to be operational by 2020. To enable ultra-high reliable andhighly precise features, there are more stringent positioning accuracy requirementsfor location based services and E911 emergency calls, targeting at bothindoor and outdoor users which include humans, devices, vehicles and machines.In currently deployed Long Term Evolution (LTE) networks, Observed TimeDi↵erence of Arrival (OTDoA) positioning is acting as one of the User Equipment(UE) localization techniques. The positioning accuracy in OTDoA methoddepends on various factors, e.g. network deployment, signal propagation conditionand properties of Positioning Reference Signal (PRS). For a given deploymentand propagation scenario, significant improvements of positioning accuracyis achievable by appropriately redesigning the PRS with 5G radio access.In this thesis, fundamental performance limits (i.e. Cramer Rao Lower Bounds)on Time of Arrival (ToA) estimation are derived respectively considering frequencyselective channel with additive white noise, carrier frequency o↵set andWiener phase noise. Particularly, the e↵ects of flexible bandwidth, subcarrierspacing and power allocation on ToA estimation accuracy have been investigatedin di↵erent settings based on corresponding performance bounds. Furthermore,the performance limits on ToA estimation can be translated into UE positioningaccuracy for a given deployment scenario. Overall, the thesis has built valuableinsights on PRS design and waveform optimization for 5G based positioning.

  • 18.
    Ärlemalm, Filip
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Harbour Porpoise Click Train Classification with LSTM Recurrent Neural Networks2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The harbour porpoise is a toothed whale whose presence is threatened in Scandinavia. Onestep towards preserving the species in critical areas is to study and observe the harbourporpoise population growth or decline in these areas. Today this is done by using underwateraudio recorders, so called hydrophones, and manual analyzing tools. This report describes amethod that modernizes the process of harbour porpoise detection with machine learning. Thedetection method is based on data collected by the hydrophone AQUAclick 100. The data isprocessed and classified automatically with a stacked long short-term memory recurrent neuralnetwork designed specifically for this purpose.

  • 19.
    Zhang, Yuqi
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Lattice Reduction Aided Multiple Input Multiple Output Detection Algorithm Design For 5G Communication2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In recent years, multiple input multiple output system has raised intensive researchinterests for its huge potentials to achieve higher spectral efficiency anddata rate. However, transmitting multiple data streams through the same timeand frequency resources simultaneously leads to severe interference betweentransmitted signals. In order to solve this problem, lattice reduction is proposedas a suboptimal maximum likelihood algorithm. It aims at finding aset of better basis vectors for the channel matrix and results in satisfactoryperformance improvements compared to conventional linear detectors. But theaverage complexity of lattice reduction algorithm is too high for practical uses.This thesis studies conventional linear detection algorithms and lattice reductionaided detection algorithms for uplink receiver design. Further an iterativelattice reduction algorithm is proposed by exploiting the frequency coherence inan orthogonal frequency division multiplexing system to achieve low complexity.In this thesis, algorithm performances are verified in various scenarios throughsimulations. Results show promising performance improvements for presentedlattice reduction detection algorithms, at the cost of an acceptable complexityincrease.

  • 20.
    Agrawal, Navneet
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Machine Intelligence in Decoding of Forward Error Correction Codes2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A deep learning algorithm for improving the performance of the Sum-ProductAlgorithm (SPA) based decoders is investigated. The proposed Neural NetworkDecoders (NND) [22] generalizes the SPA by assigning weights to the edges ofthe Tanner graph. We elucidate the peculiar design, training, and working of theNND. We analyze the edge weight’s distribution of the trained NND and providea deeper insight into its working. The training process of NND learns the edgeweights in such a way that the effects of artifacts in the Tanner graph (such ascycles or trapping sets) are mitigated, leading to a significant improvement inperformance over the SPA.We conduct an extensive analysis of the training hyper-parameters affectingthe performance of the NND, and present hypotheses for determining theirappropriate choices for different families and sizes of codes. Experimental resultsare used to verify the hypotheses and rationale presented. Furthermore,we propose a new loss-function that improves performance over the standardcross-entropy loss. We also investigate the limitations of the NND in termsof complexity and performance. Although the SPA based design of the NNDenables faster training and reduced complexity, the design constraints restrictthe neural network to reach its maximum potential. Our experiments show thatthe NND is unable to reach Maximum Likelihood (ML) performance thresholdfor any plausible set of hyper-parameters. However for short length (n 128)High Density Parity Check (HDPC) codes such as Polar or BCH codes, theperformance improvement over the SPA is significant.

  • 21.
    Gupta, Gagan
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Monitoring Water Distribution Network using Machine Learning2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Water is an important natural resource. It is supplied to our home by water distribution network thatis owned and maintained by water utility companies. Around one third of water utilities across the globereport a loss of 40% of clean water due to leakage. The increase in pumping, treatment and operationalcosts are pushing water utilities to combat water loss by developing methods to detect, locate, and xleaks. However, traditional pipeline leakage detection methods require periodical inspection with humaninvolvement, which makes it slow and inecient for leakage detection in a timely manner. An alternativeis on-line, continuous, real-time monitoring of the network facilitating early detection and localization ofthese leakages. This thesis aims to nd such an alternative using various Machine Learning techniques.For a water distribution network, a novel algorithm is proposed based on the concept of dominantnodes from graph theory. The algorithm nds the number of sensors needed and their correspondinglocations in the network. The network is then sub-divided into several leakage zones, which serves as abasis for leak localization in the network. Thereafter, leakages are simulated in the network virtually,using hydraulic simulation software. The obtained time series pressure data from the sensor nodes ispre-processed using one-dimensional wavelet series decomposition by using daubechies wavelet to extractfeatures from the data. It is proposed to use this feature extraction procedure at every sensor nodelocally, which reduces the transmitted data to the central hub over the cloud thereby reducing the energyconsumption for the IoT sensor in real world.For water leakage detection and localization, a procedure for obtaining training data is proposed,which serves as a basis for recognition of patterns and regularities in the data using supervised Machinelearning techniques such as Logistic Regression, Support Vector Machine, and Articial Neural Network.Furthermore, ensemble of these trained model is used to build a better model for leakage detection andits localization. In addition, Random Forest algorithm is trained and its performance is compared tothe obtained ensemble of earlier models. Also, leak size estimation is performed using Support VectorRegression algorithm.It is observed that the sensor node placement using proposed algorithm provides a better leakage localizationresolution than random deployment of sensor. Furthermore, it is found that leak size estimationusing Support Vector Regression algorithm provides a reasonable accuracy. Also, it is noticed that RandomForest algorithm performs better than the ensemble model except for the low leakage scenario. Thus,it is concluded to estimate the leak size rst, based on this estimation for small leakage case ensemblemodels can be applied while for large leakage case only Random Forest can be used.

  • 22.
    Yuanjia, Gong
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Multi-version Storage: Code Design and Repair in Distributed Storage Systems2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the rapid growth of data volume, data storage has attracted more and more researchinterests in recent years. Distributed storage systems play important roles ofmeeting the demand for data storage in large amounts. That is, data are stored bymultiple storage nodes which are connected together with various network topologies.The main merits of such distributed storage are faster response, higher reliability andbetter scalability. However, due to network failure, link outage or bu↵er overflow, theupdated data might not be received by all storage nodes, resulting in the coexistenceof multiple versions of the file in the system. Thus, the major challenge is consistency,which means that the latest version of the file is accessible to any read request. We aimto study multi-version storage and code design in distributed storage systems, where thelatest version of the file or a version close to the latest version is recoverable. Moreover,compared to previous studies, higher availability can be achieved in our system model,namely, at least one version of the file can be obtained.On the other hand, both storage nodes and links are vulnerable to fail in storage systems.For the sake of reliability demand, the lost data is supposed to be reconstructed.In this thesis, additional storage nodes dedicated to repair (DR storage nodes) are introducedin the repair process. The results show that optimal repair bandwidth withminimal additional storage space can be achieved by introducing a certain number ofDR storage nodes. Subsequently, linear combinations are provided to reduce the communicationcost of repair where the link cost is high. Last but not the least, we showthat the cooperation among surviving nodes and DR storage nodes suffices to completethe repair process successfully even with link failure.

  • 23.
    Mittal, Ashutosh
    KTH, School of Information and Communication Technology (ICT).
    Novel Approach to Optimize Bandwidth Consumption for Video Streaming using Eye Tracking2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Recent leaps in eye tracking technology have made it possible to enable eye tracking as a cheap, reliable and efficient addition to the human computer interaction technologies. This thesis looks into the possibility of utilizing it for client aware video streaming. Increasingly people are consuming high quality video content on wireless network devices, thus there is need to optimize bandwidth consumption for efficient delivery of such high resolution content, both for 2D and 360°videos.This work proposes SEEN (Smart Eye-tracking Enabled Networking), a novel approach to streaming video content using real time eye tracking information. This uses HEVC video tiling techniques to display high and low qualities in the same video frame depending on where the user is looking. The viability of proposed approach is validated using extensive user testing conducted on a Quality of Experience (QoE) testbed which was also developed as part of this thesis. Test results show significant bandwidth savings of up to 71% for 2D videos on standard 4K screens, and up to 83% for 360°videos on Virtual Reality (VR) headsets for acceptable QoE ratings. A comparative study on viewport tracking and eye tracking for VR headsets is also included in the thesis in order to further advocate the necessity of eye tracking.This research was conducted in collaboration with Ericsson, Tobii and KTH under the umbrella project SEEN: Smart Eye-tracking Enabled Networking.

  • 24.
    Liu, Liheng
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Performance evaluation of direct air-to-ground communication using new radio (5G)2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Providing mobile broadband (MBB) coverage to passengers in planes (and other yingobjects) has been one of the very important requirements by airline industry for sometime. With the emergence of high-capacity wireless network concepts, there is a renewedeort in dening systems based on 5G (also dened as NR, new radio) for air-to-ground(A2G) communication. When passenger planes have been taken into consideration, a fewhundreds of passengers may need to be supported, thus requiring a high-capacity backhaullink. When 5G is used for such A2G link, beamforming and other advanced physicallayer techniques can be used between the ground stations and ying objects to obtainhigh-data rate and reliable new radio link. This masters thesis work includes link andsystem level evaluations of such NR systems when beamforming, large bandwidth, higherantenna gains, coordination between ground stations, etc., are deployed. The evaluationswere carried out in Ericsson's internal state-of-the-art simulators. The study providesbaseline for system design principles for future A2G system based on NR. Also a properpropagation model for A2G communication has been identied and beamforming solutionwith other related techniques that could be used in A2G scenario have been investigated.

  • 25.
    Kizhakkumkara Muhamad, Raees
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Polar Codes for secure binary Wyner-Ziv source coding2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Source coding, originally envisaged by Claude Shannon in 1948 in his landmarkpaper "A Mathematical Theory of Communication" remained impractical forthe most part of the 20th century. However several advances were made incoding theory of which the latest-Polar Codes introduced by Erdal Arikan in2008 is highly promising. Polar Codes have modest encoding and decoding complexities,while providing a construction that directly leads to the fundamentalbounds obtained by Shannon. We are progressing further into the InformationAge, where high resolution videos are streamed over the Internet and variousdevices gather massive amounts of data while connected to each other in communicationnetworks. Hence the practical implication of an ecient and securesource coding scheme is signicant. In this thesis, we implement a source codingproblem called the Common helper in a Wyner-Ziv Network using polarcodes. Additionally the above construction leads to the lossy compression of aBernoulli Source and might provide an insight on how to develop ecient lossysource compression over a more general network.Source coding, originally envisaged by Claude Shannon in 1948 in his landmarkpaper "A Mathematical Theory of Communication" remained impractical forthe most part of the 20th century. However several advances were made incoding theory of which the latest-Polar Codes introduced by Erdal Arikan in2008 is highly promising. Polar Codes have modest encoding and decoding complexities,while providing a construction that directly leads to the fundamentalbounds obtained by Shannon. We are progressing further into the InformationAge, where high resolution videos are streamed over the Internet and variousdevices gather massive amounts of data while connected to each other in communicationnetworks. Hence the practical implication of an ecient and securesource coding scheme is signicant. In this thesis, we implement a source codingproblem called the Common helper in a Wyner-Ziv Network using polarcodes. Additionally the above construction leads to the lossy compression of aBernoulli Source and might provide an insight on how to develop ecient lossysource compression over a more general network.

  • 26.
    Yang, You
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Privacy-enhancing and Cost-efficient Energy Management for an End-User Smart Grid in the Presence of an Energy Storage2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A smart grid is an energy network which manages the energy generation anddistribution more efficiently following the real-time energy demands of end-usersthrough control and communication technologies. Deploying smart grids canimprove the energy efficiency, enhance the network reliability, and reduce costsof both the energy provider and end-users. However, these benefits come withprivacy challenges. One of such challenges is the smart meter privacy problem.In a smart grid, the smart meter is used to record the real-time energy supplyand to feedback the records to the energy provider. Since the energy is suppliedon the demand, these smart meter records contain the information of energydemand profile of the end-user and therefore it brings the risk of compromisingconsumers’ privacy. Regarding this issue, a rechargeable energy storage canbe used to mitigate this risk by manipulating consumers’ energy consumptionprofile. However, privacy enhancement will lead to increasing the consumers’cost for purchasing energy, which violates the original cost-saving motivation forconsumers. In this work, we investigate the design of a privacy-enhancing andcost-efficient energy management strategy. In detail, dynamic pricing of energyis assumed so that the consumer has the opportunity to utilize the energy storageto reduce the energy cost. Furthermore, the Kullback-Leibler divergence rate isused as privacy measure, and the expected cost-saving rate is also evaluated. Tostudy the trade-off between privacy and cost, the proposed objective functionis a weighted sum of Kullback-Leibler divergence rate and expected cost-savingrate. We first decompose both Kullback-Leibler divergence rate and expectedcost-saving rate in additive forms over a finite horizon. Based on the predefinedbelief states, we express the overall objective function by state-actionpairs and reformulate the energy management design into an Markov decisionprocess (MDP), and the finite horizon optimal solution can be obtained by usingBellman dynamic programming. Finally, in the special case of independent andidentically distributed (i.i.d) demand, we explicitly characterize a stationarypolicy for the infinite horizon average cost by showing this policy can preserve acertain invariance property of the belief state. And we also show this stationarypolicy can achieve an optimal privacy leakage rate.

  • 27.
    Hemlin Billström, Adam
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Huss, Fabian
    Video Integrity through Blockchain Technology2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The increasing capabilities of today’s smartphones enables users to live stream video directly from their mobile device. One increasing concern regarding videos found online is their authenticity and integrity. From a consumer standpoint, it is very hard to distinguish and discern whether or not a video found on online can be trusted, if it was the original version, or if has been taken out of context. This thesis will investigate a method which tries to apply video integrity to live streamed media.

    The main purpose of this thesis was to design and evaluate a proof of concept prototype which will apply data integrity while simultaneously recording videos through an Android device. Additionally, the prototype has an online verification platform which verifies the integrity of the recorded video. Blockchain is a technology with the inherent ability to store data in a chronological chained link of events: establishing an irrefutable database. Using cryptographic hashes together with blockchain: an Android device can generate cryptographic hashes of the data content from a video recording, and consequently transmit these hashes to a blockchain. The same video is deconstructed in the web client creating hashes that can subsequently be compared with the ones found in the blockchain.

    A resulting prototype system provides some of the desired functions. However, the prototype is limited in that it does not have the ability to sign the hashes produced. It has also been limited in that it does not employ HTTPS for communication, and the verification process needs to be optimized to make it usable for real applications.

  • 28.
    Zhu, Hui
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Design of Optimal Energy Flow Control with Privacy-Cost Trade-Off in Smart Grids2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    As a promising field, the development of smart grid has drawn more and more attention from many countries. A smart meter plays a significant role in a smart grid. It replaces the traditional electricity meter with the ability to frequently transmit instantaneous energy consumptions of the consumer to theenergy provider of the smart grid. From the view of electricity suppliers, it isbeneficial for planning, controlling and billing. However, from consumers’ perspective, the high-resolution energy record may lead to privacy problem, which means the consumers’ behaviour can be revealed by analysing the smart meter readings. In this thesis project, we will focus on the privacy leakage problem of the smart meter. We study the problem of optimal privacy-cost trade-off in a smart grid equipped with an energy provider, an alternative energy source, a smart meter,and an energy control unit. The privacy leakage is modelled as unauthorized detections of the consumer’s behaviours based on the smart meter readings of energy supplies from the energy provider. The control strategy is designed to manage the energy inflows to satisfy the instantaneous energy demands of the consumer and also to optimally trade off the privacy risk and energy cost. To evaluate the privacy risk, we use a Bayesian detection-operational privacy metric. Different scenarios are considered for which we show that their optimization problems can be reduced to linear programmings. Therefore, based on this observation, we propose optimal control strategy design algorithms to solve the optimization problems efficiently.

  • 29.
    Fanny, Roche
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Evaluation of Audio FeatureExtraction Techniques to ClassifySynthesizer Sounds2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    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.

  • 30.
    Deniaux, Tiphanie
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Investigate more robust featuresfor Speech Recognition usingDeep Learning2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    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.

  • 31.
    Sonal, Manish
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Machine Learning for PAPR Distortion Reduction in OFDM Systems2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The purpose of the project is to investigate the possibility of using modern machine learning to model nonlinear analog devices like the Power Amplifier (PA), and study the feasibility of using such models in wireless systems design. Orthogonal frequency division multiplexing (OFDM) is one of the most prominent modulation technique used in several standards like 802.11a,802.11n, 802.11ac and more. Telecommunication systems like LTE, LTE/Aand WiMAX are also based on OFDM. Nevertheless, OFDM system shows high peak to average power (PAPR) in time domain because it comprises of many subcarriers added via inverse fast Fourier transform(IFFT). HighPAPR results in an increased symbol error rate, while degrading the efficiency of the PA. Digital predistortion (DPD) still suffers from high symbol error rate (SER) and reduced PA efficiency, when there is an increase in peak back off(PBO). A receiver based nonlinearity distortion reduction approach can be justified by the fact that base stations have high computation power. A iterative-decision-feedback mitigation technique can be implemented as a receiver side compensation assuming memoryless PA nonlinearities. For successful distortion reduction the iterative-decision based technique required the knowledge of the transmitter PA. The author proposes to identify the nonlinear PA model using machine learning techniques like nonlinear regression and deep learning. The results show promising improvement in SER reduction with small PA model learning time.

  • 32.
    Wen, Guanren
    KTH, School of Electrical Engineering (EES).
    Optimal Power Allocation and Ergodic Capacity in Cognitive Radio Network2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Cognitive radio network allows the secondary users (SUs) in a secondary communication network (SCN) coexist with priority users in a priority communication network (PCN). The interference caused by SCN to PCN is required to be rational and not affected the quality of server within the PCN to each priority users (PUs). In this paper, we study the optimal power allocation method to achieve the maximum ergodic capacity of both PU fading channel and SU fading channel under different power constraints. The interference power constraints at PU and the transmit power constraints at SU are considered, and the power constraints is distinguished as the peak power constraint and average power constraint. Different combinations of power constraints are analyzed under the particular system and channel fading model. This paper shows that in different scenarios the optimal power of SCN do exist to reach the maximum ergodic capacity of the entire system including SCN and PCN.

  • 33.
    Al-Saadeh, Osama
    KTH, School of Information and Communication Technology (ICT).
    Performance of In-Band Full-Duplex for 5G Wireless Networks2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In-band full duplex is a new duplexing scheme that allows radio nodes to transmit and receive, utilizing the same frequency and time resources. The implementation of in-band full duplex was not feasible in practice, due to the effect of self-interference. But then, advances in signal processing made it possible to reduce this effect. However, the system level performance of in-band full duplex has not been investigated thoroughly.Through computer simulations, we investigate the performance of in-band full duplex, for indoor 5G small cell wireless networks. We examine the performance of in-band full duplex in comparison to dynamic and static time division duplexing. Additionally, we analyze the performance of the duplexing schemes with two interference mitigation techniques, namely beamforming and interference cancellation.Our results indicate that for highly utilized wireless networks, in-band full duplex should be combined with beamforming and interference cancellation, in order to achieve a performance gain over traditional duplexing schemes. Only then, in-band full duplex is considered advantageous, at any network utilization, and any downlink to uplink traffic demand proportion. Our results also suggest that in order to achieve a performance gain with in-band full duplex in both links, the transmit power of the access points should be comparable to the transmit power of the mobile stations.

  • 34.
    Ye, Qianyun
    KTH, School of Information and Communication Technology (ICT).
    2.4-GHz Wireless Network Based Multi-Tag Access System2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Machine-to-Machine technology has been intensively researched recently which is believed to take the role of leading ICT industry development. Wireless Sensor Networks provide solution to integrate numerous numbers of machines who require features include low power, low cost, and flexible, which can be fulfilled by applying Zigbee technique.

    This thesis devotes an effort into Wireless Sensor Network development that a Multi- Tag System operating on 2.4-GHz wireless network is developed. A theoretical study about ZigBee protocol and its bottom layers IEEE 802.15.4 standard is provided to lay a foundation of the design work. The thesis also includes a practical usage of low cost TI CC2530 Systom-on-Chip, together with the illustration of software development inside the chip. The design work provides GUI Platform for users to register themselves into the network and central monitoring platform to track all users within the area. Both GUI platforms are developed based on VB IDE.

    The Multi-Tag Access System is suitable for attendee control functionality in big-scale conference, events, and lecture, which is also a prototype expecting more functionality to be added in the future.

  • 35.
    Shahrivar, Damon
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Accurate and fast taxonomic profiling of microbial communities2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the advent of next generation sequencing there has been an explosion

    of the size of data that needs to be processed, where next generation

    sequencing yields basepairs of DNA in the millions. The rate at

    which the size of data increases supersedes Moores law therefore there is

    a huge demand for methods to nd meaningful labels of sequenced data.

    Studies of microbial diversity of a sample is one such challenge in the eld

    of metagenomics. Finding the distribution of a bacterial community has

    many uses for example, obesity control. Existing methods often resort to

    read-by-read classication which can take several days of computing time

    in a regular desktop environment, excluding genomic scientists without

    access to huge clusters of computational units.

    By using sparsity enforcing methods from the general sparse signal processing

    eld (such as compressed sensing), solutions have been found to

    the bacterial community composition estimation problem by a simultaneous

    assignment of all sample reads to a pre-processed reference database.

    The inference task is reduced to a general statistical model based on

    kernel density estimation techniques that are solved by existing convex

    optimization tools. The objective is to o er a reasonably fast community

    composition estimation method. This report proposes, clustering as

    a means of aggregating data to improve existing techniques run-time and

    biological delity. Use of convex optimization tools to increase the accuracy

    of mixture model parameters are also explored and tested. The

    work is concluded by experimentation on proposed improvements with

    satisfactory results.

    The use of Dirichlet mixtures is explored as a parametric model of

    the sample distribution where it is deemed that the Dirichlet is a good

    choice for aggregation of k-mer feature vectors but the use of Expectation

    Maximization is unt for parameter estimation of bacterial 16s rRNA

    samples.

    Finally, a semi-supervised learning method found on distance based

    classication of taxa has been implemented and tested on real biological

    data with high biological delity.

  • 36.
    SVENNÉRUS, EMANUEL
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Compressive Sensing applied on a Video Signal2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Compressive Sensing has attracted a lot of attention over the last decade

    within the areas of applied mathematics, computer science and electrical

    engineering because of it suggesting that we can sample a signal under the

    limit that traditional sampling theory provides. By then using dierent recovery

    algorithms we are able to, theoretically, recover the complete original

    signal even though we have taken very few samples to begin with. It has

    been proven that these recovery algorithms work best on signals that are

    highly compressible, meaning that the signals can have a sparse representation

    where the majority of the signal elements are close to zero. In this

    thesis we implement some of these recovery algorithms and investigate how

    these perform practically on a real video signal consisting of 300 sequential

    image frames. The video signal will be under sampled, using compressive

    sensing, and then recovered using two types of strategies,

    - One where no time correlation between successive frames is assumed, using

    the classical greedy algorithm Orthogonal Matching Pursuit (OMP) and a

    more robust, modied OMP called Predictive Orthogonal Matching Pursuit

    (PrOMP).

    - One newly developed algorithm, Dynamic Iterative Pursuit (DIP), which

    assumes and utilizes time correlation between successive frames.

    We then performance evaluate and compare these two strategies using the

    Peak Signal to Noise Ratio (PSNR) as a metric. We also provide visual

    results.

    Based on investigation of the data in the video signal, using a simple model

    for the time correlation and transition probabilities between dierent signal

    coecients in time, the DIP algorithm showed good recovery performance.

    The main results showed that DIP performed better and better over time

    and outperformed the PrOMP up to a maximum of 6 dB gain at half of the

    original sampling rate but performed slightly below the PrOMP in a smaller

    part of the video sequence where the correlation in time between successive

    frames in the original video sequence suddenly became weaker.

  • 37.
    Zhang, Jue
    KTH, School of Electrical Engineering (EES).
    Coordinated Multipoint Schemes with Suitable Cooperation Thresholds for Ultra Dense Networks2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Both data traffic and number of subscriptions have enormously increased inmobile network in recent years. Moreover, there will be an even faster growthin the future. A promising way to satisfy a significantly increasing demand infuture radio access network is by using so called Ultra Dense Networks (UDNs)which deploy a large number of base stations compared to the number of activeusers.Radio spectrum is a finite resource and therefore has to be shared by multipleusers. This sharing of radio spectrum inevitably causes interference betweenthe users. In this study, the interference management performance of differentresource allocation schemes in different network density is studied, which is froma traditional network density to ultra dense network.Except for traditional frequency reuse scheme and reuse partitioning scheme,Coordinated Multi Point (CoMP) schemes have been chosen in the work. Different CoMP techniques such as the universal frequency reuse (UFR) and coop-erative frequency reuse (CFR) are tested to find the best network performancein terms of average users data throughput and cell rate.Besides, after measuring these CoMP schemes which are designed for highbase station density, the optimal scheme is found to be a potential methodadopted by ultra-dense network.

  • 38.
    Forssell, Henrik
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Energy Efficiency of Heterogeneous LTE Networks2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    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.

  • 39.
    He, Xi
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Indoor positioning in wireless lighting control system2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Wireless lighting control system is considered as an infrastructure for o ering

    positioning based lighting control service. The luminaires in the system are

    equipped with wireless sensors and the wireless sensor transmission for illumi-

    nation control in the lighting control system are used to do indoor positioning.

    Specically, received signal strength indicator (RSSI) values from these sensor

    transmissions are collected at the smartphone. A simple RSSI-based indoor

    positioning algorithm is proposed in this report. By combining with accelerom-

    eter sensor data, the user location zone can be determined. Then a user may

    be able to control associated luminaires based on its location zone. The pro-

    posed indoor positioning method is evaluated via experiments in a room with

    wireless sensor nodes at ceiling and simulations based on a large indoor lighting

    oce space model. Experimental and simulation results show that the proposed

    indoor positioning method can be used to localize a user.

  • 40.
    Casamitjana Diaz, Adria
    KTH, School of Electrical Engineering (EES), Communication Theory.
    New insights on speech signal modeling in a Bayesian framework approach2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Speech signal processing is an old research topic within the communication theory community. The continously increasing telephony market brought special attention to the discipline during the 80’s and 90’s, specially in speech coding and speech enhancement, where the most significant contributions were made. More recently, due to the appearance of novel signal processing techniques, the standard methods are being questioned. Sparse representation of signals and compessed sensing made significant contributions to the discipline, through a better representation of signals and more efficient processing techniques. In this thesis, standard speech modeling techniques are revisited. Firstly, a representation of the speech signal through the line spectral frequencies (LSF) is presented, with a extended stability analysis. Moreover, a new Bayesian framework to time-varying linear prediction (TVLP) is shown, with the analysis of different methods. Finally, a theoretical basis for speech denoising is presented and analyzed. At the end of the thesis, the reader will have a broader view of the speech signal processing discipline with new insights that can improve the standard methodology.

  • 41.
    Wu, Hanwei
    KTH, School of Electrical Engineering (EES).
    Object Ranking for Mobile 3D Visual Search2015Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    In this thesis, we study object ranking in mobile 3D visual search. The conventional methods of object ranking achieve ranking results based on the appearance of objects in images captured by mobile devices while ignoring the underlying 3D geometric information. Thus, we propose to use the method of mobile 3D visual search to improve the ranking by using the underlying 3D geometry of the objects. We develop an algorithm of fast 3D geometric verication to re-rank the objects at low computational complexity. In that scene, the geometry of the objects such as round corners, sharp edges, or planar surfaces as well as the appearance of objects will be considered for 3D object ranking.

    On the other hand, we also investigate flaws of conventional vocabulary trees and improve the ranking results by introducing a credibility value to the TF-IDF scheme. By combining novel vocabulary trees and fast 3D geometric verification, we can improve the recall-datarate performance as well as the subjective ranking results for mobile 3D visual search.

  • 42.
    Hedenskog, Filip
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Robust MIMO Precoding on Real-World Measured Channels2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    It is well known that multi-input multi-output (MIMO) wireless communication systemsthat employ precoding techniques are capable of meeting the high expectations of modernand future wireless communication standards. In order to fully utilize these techniques, thecommunication system typically requires information of the channel, commonly referred toas channel state information (CSI). In practice, the CSI at the transmitter (CSIT) is oftennot perfect which addresses the need for robust precoding designs, that can mitigate theeffects of precoding with imperfect CSIT. By modeling the imperfect CSIT as deterministic,it can be assumed that the estimated channel, as represented by the CSIT, belongs to aconvex uncertainty set. With this approach, the problem of finding a robust precoding designcan be formulated as a convex maximin problem, where the solution optimizes the systemperformance for the worst channel that belongs to the uncertainty set. How the uncertaintyset is modeled impacts the performance of the communication system, which calls for theevaluation of several robust precoding designs. While different characteristics of the convexuncertainty sets has been evaluated for MIMO flat-fading channels represented by i.i.d. zero-mean, unit variance Gaussian elements, it is of interest to apply the theory of worst-caserobust precoding designs on real-world measured MIMO channels.More concisely, this project investigates MIMO precoding designs with deterministic im-perfect CSIT for real-world measured channels that utilizes orthogonal frequency divisionmultiplexing (OFDM) schemes. The worst-case received signal-to-noise ratio (SNR) will bepresented as a result of using MIMO precoding designs on real-world channels, and the effectof the choice of model parameters and characteristics of the chosen uncertainty set will bevisualized and discussed. Furthermore, orthogonal space-time block code (OSTBC) transmis-sion designs will be employed to measure the worst case symbol error rate (SER) as a tool toevaluate the system performance in different scenarios. The results will be compared to thatwhen the channel is composed of i.i.d. zero-mean, unit variance Gaussian elements and forthe case when the channel is based on the Kronecker model.The results indicate that a further analysis of how the Kronecker model behaves in termsof capacity is required in order to draw accurate conclusions regarding the implementation ofrobust precoding strategies when each pair of antennas are correlated. Also, it is essential todevelop a framework that offers methods on how to accurately model the uncertainty set sothat it can represent errors that originates from both quantization errors, estimation errorsand outdated estimates.

  • 43.
    ABBASI, MUHAMMAD MOHSIN
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Solving Sudoku by Sparse Signal Processing2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Sudoku is a discrete constraints satisfaction problem which is modeled as an underdetermined linear

    system. This report focuses on applying some new signal processing approaches to solve sudoku and

    comparisons to some of the existing approaches are implemented. As our goal is not meant for

    sudoku only in the long term, we applied approximate solvers using optimization theory methods. A

    Semi Definite Relaxation (SDR) convex optimization approach was developed for solving sudoku. The

    idea of Iterative Adaptive Algorithm for Amplitude and Phase Estimation (IAA-APES) from array

    processing is also being used for sudoku to utilize the sparsity of the sudoku solution as is the case in

    sensing applications. LIKES and SPICE were also tested on sudoku and their results are compared with

    l1-norm minimization, weighted l1-norm, and sinkhorn balancing. SPICE and l1-norm are equivalent

    in terms of accuracy, while SPICE is slower than l1-norm. LIKES and weighted l1-norm are equivalent

    and better than SPICE and l1-norm in accuracy. SDR proved to be best when the sudoku solutions are

    unique; however the computational complexity is worst for SDR. The accuracy for IAA-APES is

    somewhere between SPICE and LIKES and its computation speed is faster than both.

  • 44.
    Ashraf, Umer Zeeshan
    KTH, School of Information and Communication Technology (ICT).