15,878 research outputs found

    Cross-layer Optimized Wireless Video Surveillance

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    A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

    Cross-layer Optimized Wireless Video Surveillance

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    A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

    A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions

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    The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet goes far beyond data, audio and video delivery over fixed and mobile networks, and even beyond allowing communication and collaboration among things. It is expected to enable haptic communication and allow skill set delivery over networks. Some examples of potential applications are tele-surgery, vehicle fleets, augmented reality and industrial process automation. Several papers already cover many of the Tactile Internet-related concepts and technologies, such as haptic codecs, applications, and supporting technologies. However, none of them offers a comprehensive survey of the Tactile Internet, including its architectures and algorithms. Furthermore, none of them provides a systematic and critical review of the existing solutions. To address these lacunae, we provide a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet. In addition, we critically review them using a well-defined set of requirements and discuss some of the lessons learned as well as the most promising research directions

    Adaptive Communications for Next Generation Broadband Wireless Access Systems

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    Un dels aspectes claus en el disseny i gestió de les xarxes sense fils d'accés de banda ampla és l'ús eficient dels recursos radio. Des del punt de vista de l'operador, l'ample de banda és un bé escàs i preuat que s´ha d'explotar i gestionar de la forma més eficient possible tot garantint la qualitat del servei que es vol proporcionar. Per altra banda, des del punt de vista del usuari, la qualitat del servei ofert ha de ser comparable al de les xarxes fixes, requerint així un baix retard i una baixa pèrdua de paquets per cadascun dels fluxos de dades entre la xarxa i l'usuari. Durant els darrers anys s´han desenvolupat nombroses tècniques i algoritmes amb l'objectiu d'incrementar l'eficiència espectral. Entre aquestes tècniques destaca l'ús de múltiples antenes al transmissor i al receptor amb l'objectiu de transmetre diferents fluxos de dades simultaneament sense necessitat d'augmentar l'ample de banda. Per altra banda, la optimizació conjunta de la capa d'accés al medi i la capa física (fent ús de l'estat del canal per tal de gestionar de manera optima els recursos) també permet incrementar sensiblement l'eficiència espectral del sistema.L'objectiu d'aquesta tesi és l'estudi i desenvolupament de noves tècniques d'adaptació de l'enllaç i gestió dels recursos ràdio aplicades sobre sistemes d'accés ràdio de propera generació (Beyond 3G). Els estudis realitzats parteixen de la premissa que el transmisor coneix (parcialment) l'estat del canal i que la transmissió es realitza fent servir un esquema multiportadora amb múltiples antenes al transmisor i al receptor. En aquesta tesi es presenten dues línies d'investigació, la primera per casos d'una sola antenna a cada banda de l'enllaç, i la segona en cas de múltiples antenes. En el cas d'una sola antena al transmissor i al receptor, un nou esquema d'assignació de recursos ràdio i priorització dels paquets (scheduling) és proposat i analitzat integrant totes dues funcions sobre una mateixa entitat (cross-layer). L'esquema proposat té com a principal característica la seva baixa complexitat i que permet operar amb transmissions multimedia. Alhora, posteriors millores realitzades per l'autor sobre l'esquema proposat han permès també reduir els requeriments de senyalització i combinar de forma óptima usuaris d'alta i baixa mobilitat sobre el mateix accés ràdio, millorant encara més l'eficiència espectral del sistema. En cas d'enllaços amb múltiples antenes es proposa un nou esquema que combina la selecció del conjunt optim d'antenes transmissores amb la selecció de la codificació espai- (frequència-) temps. Finalment es donen una sèrie de recomanacions per tal de combinar totes dues línies d'investigació, així con un estat de l'art de les tècniques proposades per altres autors que combinen en part la gestió dels recursos ràdio i els esquemes de transmissió amb múltiples antenes.Uno de los aspectos claves en el diseño y gestión de las redes inalámbricas de banda ancha es el uso eficiente de los recursos radio. Desde el punto de vista del operador, el ancho de banda es un bien escaso y valioso que se debe explotar y gestionar de la forma más eficiente posible sin afectar a la calidad del servicio ofrecido. Por otro lado, desde el punto de vista del usuario, la calidad del servicio ha de ser comparable al ofrecido por las redes fijas, requiriendo así un bajo retardo y una baja tasa de perdida de paquetes para cada uno de los flujos de datos entre la red y el usuario. Durante los últimos años el número de técnicas y algoritmos que tratan de incrementar la eficiencia espectral en dichas redes es bastante amplio. Entre estas técnicas destaca el uso de múltiples antenas en el transmisor y en el receptor con el objetivo de poder transmitir simultáneamente diferentes flujos de datos sin necesidad de incrementar el ancho de banda. Por otro lado, la optimización conjunta de la capa de acceso al medio y la capa física (utilizando información de estado del canal para gestionar de manera óptima los recursos) también permite incrementar sensiblemente la eficiencia espectral del sistema.El objetivo de esta tesis es el estudio y desarrollo de nuevas técnicas de adaptación del enlace y la gestión de los recursos radio, y su posterior aplicación sobre los sistemas de acceso radio de próxima generación (Beyond 3G). Los estudios realizados parten de la premisa de que el transmisor conoce (parcialmente) el estado del canal a la vez que se considera que la transmisión se realiza sobre un sistema de transmisión multiportadora con múltiple antenas en el transmisor y el receptor. La tesis se centra sobre dos líneas de investigación, la primera para casos de una única antena en cada lado del enlace, y la segunda en caso de múltiples antenas en cada lado. Para el caso de una única antena en el transmisor y en el receptor, se ha desarrollado un nuevo esquema de asignación de los recursos radio así como de priorización de los paquetes de datos (scheduling) integrando ambas funciones sobre una misma entidad (cross-layer). El esquema propuesto tiene como principal característica su bajo coste computacional a la vez que se puede aplicar en caso de transmisiones multimedia. Posteriores mejoras realizadas por el autor sobre el esquema propuesto han permitido también reducir los requisitos de señalización así como combinar de forma óptima usuarios de alta y baja movilidad. Por otro lado, en caso de enlaces con múltiples antenas en transmisión y recepción, se presenta un nuevo esquema de adaptación en el cual se combina la selección de la(s) antena(s) transmisora(s) con la selección del esquema de codificación espacio-(frecuencia-) tiempo. Para finalizar, se dan una serie de recomendaciones con el objetivo de combinar ambas líneas de investigación, así como un estado del arte de las técnicas propuestas por otros autores que combinan en parte la gestión de los recursos radio y los esquemas de transmisión con múltiples antenas.In Broadband Wireless Access systems the efficient use of the resources is crucial from many points of views. From the operator point of view, the bandwidth is a scarce, valuable, and expensive resource which must be exploited in an efficient manner while the Quality of Service (QoS) provided to the users is guaranteed. On the other hand, a tight delay and link quality constraints are imposed on each data flow hence the user experiences the same quality as in fixed networks. During the last few years many techniques have been developed in order to increase the spectral efficiency and the throughput. Among them, the use of multiple antennas at the transmitter and the receiver (exploiting spatial multiplexing) with the joint optimization of the medium access control layer and the physical layer parameters.In this Ph.D. thesis, different adaptive techniques for B3G multicarrier wireless systems are developed and proposed focusing on the SS-MC-MA and the OFDM(A) (IEEE 802.16a/e/m standards) communication schemes. The research lines emphasize into the adaptation of the transmission having (Partial) knowledge of the Channel State Information for both; single antenna and multiple antenna links. For single antenna links, the implementation of a joint resource allocation and scheduling strategy by including adaptive modulation and coding is investigated. A low complexity resource allocation and scheduling algorithm is proposed with the objective to cope with real- and/or non-real- time requirements and constraints. A special attention is also devoted in reducing the required signalling. However, for multiple antenna links, the performance of a proposed adaptive transmit antenna selection scheme jointly with space-time block coding selection is investigated and compared with conventional structures. In this research line, mainly two optimizations criteria are proposed for spatial link adaptation, one based on the minimum error rate for fixed throughput, and the second focused on the maximisation of the rate for fixed error rate. Finally, some indications are given on how to include the spatial adaptation into the investigated and proposed resource allocation and scheduling process developed for single antenna transmission

    Machine Learning-Enabled Resource Allocation for Underlay Cognitive Radio Networks

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    Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources and the way they are regulated. Considering that the radio spectrum is a natural limited resource, supporting the ever increasing demands for higher capacity and higher data rates for diverse sets of users, services and applications is a challenging task which requires innovative technologies capable of providing new ways of efficiently exploiting the available radio spectrum. Consequently, dynamic spectrum access (DSA) has been proposed as a replacement for static spectrum allocation policies. The DSA is implemented in three modes including interweave, overlay and underlay mode [1]. The key enabling technology for DSA is cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems. Unlike conventional radio which is restricted to only operate in designated spectrum bands, a CR has the capability to operate in different spectrum bands owing to its ability in sensing, understanding its wireless environment, learning from past experiences and proactively changing the transmission parameters as needed. These features for CR are provided by an intelligent software package called the cognitive engine (CE). In general, the CE manages radio resources to accomplish cognitive functionalities and allocates and adapts the radio resources to optimize the performance of the network. Cognitive functionality of the CE can be achieved by leveraging machine learning techniques. Therefore, this thesis explores the application of two machine learning techniques in enabling the cognition capability of CE. The two considered machine learning techniques are neural network-based supervised learning and reinforcement learning. Specifically, this thesis develops resource allocation algorithms that leverage the use of machine learning techniques to find the solution to the resource allocation problem for heterogeneous underlay cognitive radio networks (CRNs). The proposed algorithms are evaluated under extensive simulation runs. The first resource allocation algorithm uses a neural network-based learning paradigm to present a fully autonomous and distributed underlay DSA scheme where each CR operates based on predicting its transmission effect on a primary network (PN). The scheme is based on a CE with an artificial neural network that predicts the adaptive modulation and coding configuration for the primary link nearest to a transmitting CR, without exchanging information between primary and secondary networks. By managing the effect of the secondary network (SN) on the primary network, the presented technique maintains the relative average throughput change in the primary network within a prescribed maximum value, while also finding transmit settings for the CRs that result in throughput as large as allowed by the primary network interference limit. The second resource allocation algorithm uses reinforcement learning and aims at distributively maximizing the average quality of experience (QoE) across transmission of CRs with different types of traffic while satisfying a primary network interference constraint. To best satisfy the QoE requirements of the delay-sensitive type of traffics, a cross-layer resource allocation algorithm is derived and its performance is compared against a physical-layer algorithm in terms of meeting end-to-end traffic delay constraints. Moreover, to accelerate the learning performance of the presented algorithms, the idea of transfer learning is integrated. The philosophy behind transfer learning is to allow well-established and expert cognitive agents (i.e. base stations or mobile stations in the context of wireless communications) to teach newly activated and naive agents. Exchange of learned information is used to improve the learning performance of a distributed CR network. This thesis further identifies the best practices to transfer knowledge between CRs so as to reduce the communication overhead. The investigations in this thesis propose a novel technique which is able to accurately predict the modulation scheme and channel coding rate used in a primary link without the need to exchange information between the two networks (e.g. access to feedback channels), while succeeding in the main goal of determining the transmit power of the CRs such that the interference they create remains below the maximum threshold that the primary network can sustain with minimal effect on the average throughput. The investigations in this thesis also provide a physical-layer as well as a cross-layer machine learning-based algorithms to address the challenge of resource allocation in underlay cognitive radio networks, resulting in better learning performance and reduced communication overhead
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