142 research outputs found

    CogCell: Cognitive Interplay between 60GHz Picocells and 2.4/5GHz Hotspots in the 5G Era

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    Rapid proliferation of wireless communication devices and the emergence of a variety of new applications have triggered investigations into next-generation mobile broadband systems, i.e., 5G. Legacy 2G--4G systems covering large areas were envisioned to serve both indoor and outdoor environments. However, in the 5G-era, 80\% of overall traffic is expected to be generated in indoors. Hence, the current approach of macro-cell mobile network, where there is no differentiation between indoors and outdoors, needs to be reconsidered. We envision 60\,GHz mmWave picocell architecture to support high-speed indoor and hotspot communications. We envisage the 5G indoor network as a combination of-, and interplay between, 2.4/5\,GHz having robust coverage and 60\,GHz links offering high datarate. This requires an intelligent coordination and cooperation. We propose 60\,GHz picocellular network architecture, called CogCell, leveraging the ubiquitous WiFi. We propose to use 60\,GHz for the data plane and 2.4/5GHz for the control plane. The hybrid network architecture considers an opportunistic fall-back to 2.4/5\,GHz in case of poor connectivity in the 60\,GHz domain. Further, to avoid the frequent re-beamforming in 60\,GHz directional links due to mobility, we propose a cognitive module -- a sensor-assisted intelligent beam switching procedure -- which reduces the communication overhead. We believe that the CogCell concept will help future indoor communications and possibly outdoor hotspots, where mobile stations and access points collaborate with each other to improve the user experience.Comment: 14 PAGES in IEEE Communications Magazine, Special issue on Emerging Applications, Services and Engineering for Cognitive Cellular Systems (EASE4CCS), July 201

    Wearable Communications in 5G: Challenges and Enabling Technologies

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    As wearable devices become more ingrained in our daily lives, traditional communication networks primarily designed for human being-oriented applications are facing tremendous challenges. The upcoming 5G wireless system aims to support unprecedented high capacity, low latency, and massive connectivity. In this article, we evaluate key challenges in wearable communications. A cloud/edge communication architecture that integrates the cloud radio access network, software defined network, device to device communications, and cloud/edge technologies is presented. Computation offloading enabled by this multi-layer communications architecture can offload computation-excessive and latency-stringent applications to nearby devices through device to device communications or to nearby edge nodes through cellular or other wireless technologies. Critical issues faced by wearable communications such as short battery life, limited computing capability, and stringent latency can be greatly alleviated by this cloud/edge architecture. Together with the presented architecture, current transmission and networking technologies, including non-orthogonal multiple access, mobile edge computing, and energy harvesting, can greatly enhance the performance of wearable communication in terms of spectral efficiency, energy efficiency, latency, and connectivity.Comment: This work has been accepted by IEEE Vehicular Technology Magazin

    A heterogeneous short-range communication platform for internet of vehicles

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    The automotive industry is rapidly accelerating toward the development of innovative industry applications that feature management capabilities for data and applications alike in cars. In this regard, more internet of vehicles solutions are emerging through advancements of various wireless medium access-control technologies and the internet of things. In the present work, we develop a short-range communication–based vehicular system to support vehicle communication and remote car control. We present a combined hardware and software testbed that is capable of controlling a vehicle’s start-up, operation and several related functionalities covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino and Raspberry Pi 3, each of which individually controls certain functions to improve the overall vehicle control. The implementation of the heterogeneous communication module is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 and IEEE 802.15 medium access control technologies. Further, a control module on a smartphone was designed and implemented for efficient management. Moreover, we study the system connectivity performance by measuring various important parameters including the coverage distance, signal strength, download speed and latency. This study covers the use of this technology setup in different geographical areas over various time spans

    Contributions to IEEE 802.11-based long range communications

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    The most essential part of the Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages between the connected things and the Internet. Since the conception of the IoT, a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery-driven devices, spread over a wide area. In order to support the IoT paradigm, IEEE 802.11ah is an Internet of Things enabling technology, where the efficient management of thousands of devices is a key function. This is one of the most promising and appealing standards, which aims to bridge the gap between traditional mobile networks and the demands of the IoT. To this aim, IEEE 802.11ah provides the Restricted Access Window (RAW) mechanism, which reduces contention by enabling transmissions for small groups of stations. Optimal grouping of RAW stations requires an evaluation of many possible configurations. In this thesis, we first discuss the main PHY and MAC layer amendments proposed for IEEE 802.11ah. Furthermore, we investigate the operability of IEEE 802.11ah as a backhaul link to connect devices over possibly long distances. Additionally, we compare the aforementioned standard with previous notable IEEE 802.11 amendments (i.e. IEEE 802.11n and IEEE 802.11ac) in terms of throughput (with and without frame aggregation) by utilizing the most robust modulation schemes. The results show an improved performance of IEEE 802.11ah (in terms of power received at long range while experiencing different packet error rates) as compared to previous IEEE 802.11 standards. Additionally, we expose the capabilities of future IEEE 802.11ah in supporting different IoT applications. In addition, we provide a brief overview of the technology contenders that are competing to cover the IoT communications framework. Numerical results are presented showing how the future IEEE 802.11ah specification offers the features required by IoT communications, thus putting forward IEEE 802.11ah as a technology to cater the needs of the Internet of Things paradigm. Finally, we propose an analytical model (named e-model) that provides an evaluation of the RAW onfiguration performance, allowing a fast adaptation of RAW grouping policies, in accordance to varying channel conditions. We base the e-model in known saturation models, which we adapted to include the IEEE 802.11ah’s PHY and MAC layer modifications and to support different bit rate and packet sizes. As a proof of concept, we use the proposed model to compare the performance of different grouping strategies,showing that the e-model is a useful analysis tool in RAW-enabled scenarios. We validate the model with existing IEEE 802.11ah implementation for ns-3.La clave del concepto Internet de las cosas (IoT) es que utiliza un sistema de comunicación inalámbrica, el cual actúa como puente para la entrega de datos y mensajes de control entre las "cosas" conectadas y el Internet. Desde la concepción del IoT, se han desarrollado gran cantidad de aplicaciones y tecnologías prometedoras que cambiarán distintos aspectos de nuestra vida diaria.Sin embargo, las tecnologías de redes computacionales inalámbricas existentes carecen de la capacidad de soportar las características del IoT, como las grandes cantidades de envío y recepción de datos desde múltiples dispositivos distribuidos en un área amplia, donde los dispositivos IoT funcionan con baterías. Para respaldar el paradigma del IoT, IEEE 802.11ah, la cual es una tecnología habilitadora del Internet de las cosas, para el cual la gestión eficiente de miles de dispositivos es una función clave. IEEE 802.11ah es uno de los estándares más prometedores y atractivos, desde su concepción orientada para IoT, su objetivo principal es cerrar la brecha entre las redes móviles tradicionales y la demandada por el IoT. Con este objetivo en mente, IEEE 802.11ah incluye entre sus características especificas el mecanismo de ventana de acceso restringido (RAW, por sus siglas en ingles), el cual define un nuevo período de acceso al canal libre de contención, reduciendo la misma al permitir transmisiones para pequeños grupos de estaciones. Nótese que para obtener una agrupación óptima de estaciones RAW, se requiere una evaluación de las distintas configuraciones posibles. En esta tesis, primero discutimos las principales mejoras de las capas PHY y MAC propuestas para IEEE 802.11ah. Además, investigamos la operatividad de IEEE 802.11ah como enlace de backhaul para conectar dispositivos a distancias largas. También, comparamos el estándar antes mencionado con las notables especificaciones IEEE 802.11 anteriores (es decir, IEEE 802.11n y IEEE 802.11ac), en términos de rendimiento (incluyendo y excluyendo la agregación de tramas de datos) y utilizando los esquemas de modulación más robustos. Los resultados muestran mejores resultados en cuanto al rendimiento de IEEE 802.11ah (en términos de potencia recibida a largo alcance, mientras se experimentan diferentes tasas de error de paquetes de datos) en comparación con los estándares IEEE 802.11 anteriores.Además, exponemos las capacidades de IEEE 802.11ah para admitir diferentes aplicaciones de IoT. A su vez, proporcionamos una descripción general de los competidores tecnológicos, los cuales contienden para cubrir el marco de comunicaciones IoT. También se presentan resultados numéricos que muestran cómo la especificación IEEE 802.11ah ofrece las características requeridas por las comunicaciones IoT, presentando así a IEEE 802.11ah como una tecnología que puede satisfacer las necesidades del paradigma de Internet de las cosas.Finalmente, proponemos un modelo analítico (denominado e-model) que proporciona una evaluación del rendimiento utilizando la característica RAW con múltiples configuraciones, el cual permite una rápida adaptación de las políticas de agrupación RAW, de acuerdo con las diferentes condiciones del canal de comunicación. Basamos el e-model en modelos de saturación conocidos, que adaptamos para incluir las modificaciones de la capa MAC y PHY de IEEE 802.11ah y para poder admitir diferentes velocidades de transmisión de datos y tamaños de paquetes. Como prueba de concepto, utilizamos el modelo propuesto para comparar el desempeño de diferentes estrategias de agrupación, mostrando que el e-model es una herramienta de análisis útil en escenarios habilitados para RAW. Cabe mencionar que también validamos el modelo con la implementación IEEE 802.11ah existente para ns-3

    Modelling and Analysis of Performance Characteristics in a 60 Ghz 802.11ad Wireless Mesh Backhaul Network for an Urban 5G Deployment

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    With the widespread deployment of 5G gaining pace, there is increasing interest in deploying this technology beyond traditional Mobile Network Operators (MNO) into private and community scenarios. These deployments leverage the flexibility of 5G itself to support private networks that sit alongside or even on top of existing public 5G. By utilizing a range of virtualisation and slicing techniques in the 5G Core (5GC) and heterogeneous Radio Access Networks (RAN) at the edge, a wide variety of use cases can be supported by 5G. However, these non-typical deployments may experience different performance characteristics as they adapt to their specific scenario. In this paper we present the results of our work to model and predict the performance of millimeter wave (mmWave) backhaul links that were deployed as part of the Liverpool 5G network. Based on the properties of the 802.11ad protocol and the physical characteristics of the environment, we simulate how each link will perform with different signal-to-noise ratio (SNR) and Packet Error Rate (PER) values and verify them against real-world deployed links. Our results show good convergence between simulated and real results and provide a solid foundation for further network planning and optimization
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