VR gaming is an emerging market with relatively new technology when compared to PC and console gaming. Streamed VR gaming is when the VR game is being streamed from another device to the VR headset. This experiment will show how the VR hardware and software performs under network constraints such as RTT and packet loss for streamed VR gaming specifically. User QoE (quality of experience) will be gathered and compiled into MOS (mean opinion score) for later use in graphs to determine negative trends. All collected data will also be sent to the Infovista technical team so they can make theoretical models on how user QoE is affected by network conditions. This thesis will show how the QoS (quality of service) factors, such as latency and packet loss, impact the users overall QoE and the VR headsets FPS. Before the subjective experiment could begin a testbed was chosen and setup, a VR game was decided on, and a streaming service was tested on. During the experiment the game Serious Sam VR: The Last Hope was played and NVIDIA’s CloudXR streaming service was used. The testbed setup consisted of two PCs, one router, one access point, a tablet used for user reviews, and a VR headset with two handheld controllers. The software program ALTRUIST was used for managing the user data and applying the desired network conditions such as latency. Each user experiment tested 28 different network conditions with varying values of RTT (round trip time), Packet loss, RTT with packet loss, and RTT with random jitter. 30 users were gathered for the actual experiment where the Calendly application was used to manage the user appointments. The results consisted of objective and subjective data gathered during the experiments. From the objective data it could be determined that RTT primarily affects the FPS in the VR headset. Packet loss affected the FPS but to a minor degree compared to RTT. RTT of 175 ms received an average FPS of 53 while 24% packet loss yielded approximately 65 FPS. Random jitter had close to no impact on the FPS according to the results. The subjective data suggests that RTT of 75 ms and below yields a good user MOS and RTT of 175 ms gives an acceptable user MOS at 3 out of 5. Packet loss of 6% and below gives a good user MOS while 12% and above results in poor MOS. RTT with random jitter performs average to poorly with Standard deviation of 3 and above, for low RTT values. For future experiments it is advisableto use ALTRUIST or a similar software to help the researcher during the experiment.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / Ericsson Brasil / Uma nova geraÃÃo de sistemas de comunicaÃÃes sem fio, 5a GeraÃÃo (5G), à prevista para 2020. Para a 5G, à esperado o surgimento de diversos serviÃos baseados em comunicaÃÃes mÃquina à mÃquina em diferentes Ãreas, como assistÃncia mÃdica, seguranÃa e redes de mediÃÃo inteligente. Cada um com diferentes requerimentos de taxa de transmissÃo, latÃncia, capacidade de processamento, eficiÃncia energÃtica, etc. Independente do serviÃo, os clientes precisam ficar satisfeitos. Isto està impondo uma mudanÃa de paradigmas em direÃÃo à priorizaÃÃo do usuÃrio como fator mais importante no gerenciamento de redes sem fio. Com esta mudanÃa, criou-se o conceito de qualidade de experiÃncia (do inglÃs, Quality of Experience (QoE)), que descreve de forma subjetiva como o serviÃo à percebido pelo usuÃrio. A QoE normalmente à avaliada por uma nota entre 1 e 5, chamada nota mÃdia de opiniÃo (do inglÃs, Mean Opinion Score (MOS)). Neste contexto, conceitos de QoE podem ser considerados com diferentes objetivos, como: aumentar a vida Ãtil de baterias, melhorar a seleÃÃo para acesso à rede e aprimorar a alocaÃÃo dos recursos de rÃdio (do inglÃs, Radio Resource Allocation (RRA)). Com relaÃÃo à RRA, nesta dissertaÃÃo consideram-se requerimentos de QoE na gestÃo dos recursos disponÃveis em um sistema de comunicaÃÃes sem fio, como espectro de frequÃncia e potÃncia de transmissÃo. Mais especificamente, estuda-se um problema de assinalamento de recursos de rÃdio e de alocaÃÃo de potÃncia que objetiva maximizar a mÃnima MOS do sistema sujeito a satisfazer um nÃmero mÃnimo de usuÃrios prÃ-estabelecido. Inicialmente, formula-se um novo problema de otimizaÃÃo considerando restriÃÃes quanto à potÃncia de transmissÃo e quanto à fraÃÃo de usuÃrios que deve ser satisfeita, o que à um importante tÃpico do ponto de vista das operadoras. Este à um problema nÃo linear e de difÃcil soluÃÃo. Ele à entÃo reformulado como um problema linear inteiro e misto, que pode ser resolvido de forma Ãtima usando algoritmos conhecidos de otimizaÃÃo. Devido à complexidade da soluÃÃo Ãtima obtida, propÃe-se uma heurÃstica chamada em inglÃs de Power and Resource Allocation Based on Quality of Experience (PRABE). O mÃtodo proposto à avaliado por meio de simulaÃÃes e os resultados obtidos mostram que sua performance à superior à de outros existentes, sendo prÃxima à da Ãtima. / A new generation of wireless networks, the 5th Generation (5G), is predicted for beyond 2020. For the 5G, it is foreseen an emerging huge number of services based on Machine-Type Communications (MTCs) in different fields, such as, health care, smart metering and security. Each one of them requiring different throughput rates, latency, processing capacity, energy efficiency, etc. Independently of the service type, the customers still need to get satisfied, which is imposing a shift of paradigm towards incorporating the user as the most important factor in wireless network management. This shift of paradigm drove the creation of the Quality of Experience (QoE) concept, which describes the service quality subjectively perceived by the users. QoE is generally evaluated by a Mean Opinion Score (MOS) ranging from 1 to 5. In this context, QoE concepts can be considered with different objectives, such as, increasing battery life, optimizing handover decision, enhancing access network selection and improving Radio Resource Allocation (RRA). Regarding the RRA, in this masterâs thesis we consider QoE requirements when managing the limited available resources of a communication system, such as frequency spectrum and transmit power. More specifically, we study a radio resource assignment and power allocation problem that aims at maximizing the minimum MOS of the users in a system subject to attaining a minimum number of satisfied users. Initially, we formulate a new optimization problem taking into account constraints on the total transmit power and on the fraction of users that must be satisfied, which is an important topic from an operatorâs point of view. The referred problem is non-linear and hard to solve. However, we get to transform it into a simpler form, a Mixed Integer Linear Problem (MILP), that can be optimally solved using standard numerical optimization methods. Due to the complexity of obtaining the optimal solution, we propose a heuristic solution to this problem, called Power and Resource Allocation Based on Quality of Experience (PRABE). We evaluate the proposed method by means of simulations and the obtained results show that it outperforms some existing algorithms, as well as it performs close to the optimal solution.

In this thesis, the impact of packet losses on the quality of received videos sent across a network that exhibit normal network perturbations such as jitters, delays, packet drops etc has been examined. Dynamic behavior of a normal network has been simulated using Linux and the Network Emulator (NetEm). Peoples’ perceptions on the quality of the received video were used in rating the qualities of several videos with differing speeds. In accordance with ITU’s guideline of using Mean Opinion Scores (MOS), the effects of packet drops were analyzed. Excel and Matlab were used as tools in analyzing the peoples’ opinions which indicates the impacts that different loss rates has on the transmitted videos. Statistical methods used for evaluation of data are mean and variance. We conclude that people have convergence of opinions when losses become extremely high on videos with highly variable scene changes

This thesis contains description of the present methods and algoritms for measuring the quality of telephone call on the PBX Asterisk. Further develop the concept of a system for measuring and implementing the call embbeded system VOIPAC PXA270M. Based on theoretical analysis is carried out discussions between C, Java and PHP,which results in the selection of appropriate programming language suitable for implementation in embedded system. The concept is realized by creating an application written in a particular programming language. Part of this work is verification created application using experimental measurments of telecommunications system. The results of experimental measurements are discussed in the final evaluation.

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. / Den nuvarande mobiltelefonimarknaden kännetecknas av svag tillväxt av nya kunder men ett ökat nyttjande bland existerande kunder av företagens tjänster. Kundlojalitet har blivit en avgörande faktor för att uppnå en stark marknadsposition. Kundernas upplevda kvalitet utav mobiltjänsterna behöver upprätthållas på en hög nivå för att tillfredställa denna lojalitet. Att applicera en upplevad kvalitet (QoE) metod i en radio resurs kan vara ett medel till att förbättra kundernas upplevda kvalitet av mobiltj änsten. För att undersöka ifall en sådan tjänst är lönsam är det dock nödvändigt att en lönsamhetskalkyl genomförs, där investeringskostnad och systemets driftkostnad vägs mot eventuella intäkter. En lönsamhetsbedömning av QoE-baserad resursallokering krävs som grund för mobiloperatören att förutse deras potentiella fördelar med QoE-baserad resursschemaläggning. Denna uppsats undersöker lönsamheten av att implementera QoE i termer av förlorade intäkter, jämfört med proportionell rättvis (PF) schemaläggning, i att leverera en videoströmservice. I QoE-baserad RRM användes buffertprocentandel som användes av användarna i resursallokeringsprocessen.  De två olika systemen simulerades genom att använda olika antal basstationer i mobilnätverkskonfigurationen. Användarnöjdhet kvantifierades genom att låta användarna betygsätta tjänsten, detta värde användes därefter till att uppskatta hur många av kunderna som sannolikt ej skulle återanvända tjänsten. En lönsamhetskalkyl genomfördes genom att prediktera förlorade intäkter med avseende på kunderna som ej skulle återanvända tjänsten. Resultaten från simulerings- och lönsamhetsberäkningen visade att även om QoE erbjuder en högre kundnöjdhet av tjänsten och tillfredsställelse för er basstationer, så leder inte en QoE-implementering till signikanta fördelar för nätverket i termer av förlorade intäkter och investeringskostnader jämfört med ett PF schemaläggare. Detta indikerar att om ett företags mål är att höja kundlojaliteten, då skall företaget applicera en PF schemaläggare istället för QoE.

Objective non-intrusive speech quality assessment aimed to emulate and correlate with human judgement has received more attention over the years. It is a difficult problem due to three reasons: data scarcity, noisy human judgement, and a potential uneven distribution of bias of mean opinion scores (MOS). In this paper, we introduce the Latent Mean-Opinion-Score Network (LaMOSNet) that leverage on individual judge’s scores to increase the data size, and new ideas to deal with both noisy and biased labels. We introduce a methodology called Optimistic Judge Estimation as a way to reduce bias in MOS in a clear way. We also implement stochastic gradient noise and mean teacher, ideas from noisy image classification, to further deal with noisy and uneven bias distribution of labels. We achieve competitive results on VCC2018 modeling MOS, and state-of-the-art modeling only listener dependent scores. / Objektiv referensfri ljudkvalitétsbedömning ämnad att härma och korrelera med mänsklig bedömning har fått mer uppmärksamhet med åren. Det är ett svårt problem på grund av tre anledningar: brist på data, varians i mänsklig bedömning, och en potentiell ojämn fördelning av bias av medel bedömningsvärde (mean opinion score, MOS). I detta papper introducerar vi Latent Mean-Opinion-Score Network (LaMOSNet) som tar nytta av individuella bedömmares poäng för att öka datastorleken, och nya idéer för att handskas med både varierande och partisk märkning. Jag introducerar en metodologi som kallas Optimistisk bedömmarestimering, ett sätt att minska partiskheten i MOS på ett klart sätt. Jag implementerar också stokastisk gradient variation och medellärare, idéer från opålitlig bild igenkänning, för att ännu mer hantera opålitliga märkningar. Jag får jämförelsebara resultat på VCC2018 när jag modellerar MOS, och state-of-the-art när jag modellerar enbart beömmarnas märkning.

Modern methods of speech synthesis are not suitable for restoration of song signals due to lack of vitality and intonation in the resulted sounds. The aim of presented work is to synthesize melismas met in Lithuanian folk songs, by applying Artificial Neural Networks. An analytical survey of rather a widespread literature is presented. First classification and comprehensive discussion of melismas are given. The theory of dynamic systems which will make the basis for studying melismas is presented and finally the relationship for modeling a melisma with nonlinear and dynamic systems is outlined. Investigation of the most widely used Linear Prediction Coding method and possibilities of its improvement. The modification of original Linear Prediction method based on dynamic LPC frame positioning is proposed. On its basis, the new melisma synthesis technique is presented. Developed flexible generalized melisma model, based on two Artificial Neural Networks – a Multilayer Perceptron and Adaline – as well as on two network training algorithms – Levenberg- Marquardt and the Least Squares error minimization – is presented. Moreover, original mathematical models of Fortis, Gruppett, Mordent and Trill are created, fit for synthesizing melismas, and their minimal sizes are proposed. The last chapter concerns experimental investigation, using over 500 melisma records, and corroborates application of the new mathematical models to melisma synthesis of one performer.

Modern methods of speech synthesis are not suitable for restoration of song signals due to lack of vitality and intonation in the resulted sounds. The aim of presented work is to synthesize melismas met in Lithuanian folk songs, by applying Artificial Neural Networks. An analytical survey of rather a widespread literature is presented. First classification and comprehensive discussion of melismas are given. The theory of dynamic systems which will make the basis for studying melismas is presented and finally the relationship for modeling a melisma with nonlinear and dynamic systems is outlined. Investigation of the most widely used Linear Prediction Coding method and possibilities of its improvement. The modification of original Linear Prediction method based on dynamic LPC frame positioning is proposed. On its basis, the new melisma synthesis technique is presented. Developed flexible generalized melisma model, based on two Artificial Neural Networks – a Multilayer Perceptron and Adaline – as well as on two network training algorithms – Levenberg- Marquardt and the Least Squares error minimization – is presented. Moreover, original mathematical models of Fortis, Gruppett, Mordent and Trill are created, fit for synthesizing melismas, and their minimal sizes are proposed. The last chapter concerns experimental investigation, using over 500 melisma records, and corroborates application of the new mathematical models to melisma synthesis of one performer.