2,263 research outputs found

    Downlink Performance of a Multi-Carrier MIMO System in a Bursty Traffic Cellular Network

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    A Comparison of Scheduling Strategies for MIMO Broadcast Channel with Limited Feedback on OFDM Systems

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    We consider a multiuser downlink transmission from a base station with multiple antennas (MIMO) to mobile terminals (users) with a single antenna, using orthogonal frequency division multiplexing (OFDM). Channel conditions are reported by a feedback from users with limited rate, and the base station schedules transmissions and beamforms signals to users. We show that an important set of schedulers using a general utility function can be reduced to a scheduler maximizing the weighted sum rate of the system. For this case we then focus on scheduling methods with many users and OFDM subcarriers. Various scheduling strategies are compared in terms of achieved throughput and computational complexity and a good tradeoff is identified in greedy and semiorthogonal user selection algorithms. In the greedy selection algorithm, users are selected one by one as long as the throughput increases, while in the semiorthogonal approach users are selected based on the channel correlation. An extension of these approaches from a flat-fading channel to OFDM is considered and simplifications that may be useful for a large number of subcarriers are presented. Results are reported for a typical cellular transmission of the long-term evolution (LTE) of 3GPP

    Scheduling in 5G networks : Developing a 5G cell capacity simulator.

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    La quinta generación de comunicaciones móviles (5G) se está convirtiendo en una realidad gracias a la nueva tecnología 3GPP (3rd Generation Partnership Project) diseñada para cumplir con una amplia gama de requerimientos. Por un lado, debe poder soportar altas velocidades y servicios de latencia ultra-baja, y por otro lado, debe poder conectar una gran cantidad de dispositivos con requerimientos laxos de ancho de banda y retardo. Esta diversidad de requerimientos de servicio exige un alto grado de flexibilidad en el diseño de la interfaz de radio. Dado que la tecnología LTE (Long Term Evolution) se diseñó originalmente teniendo en cuenta la evolución de los servicios de banda ancha móvil, no proporciona suficiente flexibilidad para multiplexar de manera óptima los diferentes tipos de servicios previstos por 5G. Esto se debe a que no existe una única configuración de interfaz de radio capaz de adaptarse a todos los diferentes requisitos de servicio. Como consecuencia, las redes 5G se están diseñando para admitir diferentes configuraciones de interfaz de radio y mecanismos para multiplexar estos diferentes servicios con diferentes configuraciones en el mismo espectro disponible. Este concepto se conoce como Network Slicing y es una característica clave de 5G que debe ser soportada extremo a extremo en la red (acceso, transporte y núcleo). De esta manera, las Redes de Acceso (RAN) 5G agregarán el problema de asignación de recursos para diferentes servicios al problema tradicional de asignación de recursos a distintos usuarios. En este contexto, como el estándar no describe cómo debe ser la asignación de recursos para usuarios y servicios (quedando libre a la implementación de los proveedores) se abre un amplio campo de investigación. Se han desarrollado diferentes herramientas de simulación con fines de investigación durante los últimos años. Sin embargo, como no muchas de estas son libres, fáciles de usar y particularmente ninguna de las disponibles soporta Network Slicing a nivel de Red de Acceso, este trabajo presenta un nuevo simulador como principal contribución. Py5cheSim es un simulador simple, flexible y de código abierto basado en Python y especialmente orientado a probar diferentes algoritmos de scheduling para diferentes tipos de servicios 5G mediante una implementación simple de la funcionalidad RAN Slicing. Su arquitectura permite desarrollar e integrar nuevos algoritmos para asignación de recursos de forma sencilla y directa. Además, el uso de Python proporciona suficiente versatilidad para incluso utilizar herramientas de Inteligencia Artificial para el desarrollo de nuevos algoritmos. Este trabajo presenta los principales conceptos de diseño de las redes de acceso 5G que se tomaron como base para desarrollar la herramienta de simulación. También describe decisiones de diseño e implementación, seguidas de las pruebas de validación ejecutadas y sus principales resultados. Se presentan además algunos ejemplos de casos de uso para mostrar el potencial de la herramienta desarrollada, proporcionando un análisis primario de los algoritmos tradicionales de asignación de recursos para los nuevos tipos de servicios previstos por la tecnología. Finalmente se concluye sobre la contribución de la herramienta desarrollada, los resultados de los ejemplos incluyendo posibles líneas de investigación junto con posibles mejoras para futuras versiones.The fifth generation of mobile communications (5G) is already becoming a reality by the new 3GPP (3rd Generation Partnership Project) technology designed to solve a wide range of requirements. On the one hand, it must be able to support high bit rates and ultra-low latency services, and on the other hand, it should be able to connect a massive amount of devices with loose band width and delay requirements. Such diversity in terms of service requirements demands a high degree of flexibility in radio interface design. As LTE (Long Term Evolution) technology was originally designed with Mobile Broadband (MBB) services evolution in mind it does not provide enough flexibility to multiplex optimally the different types of services envisioned by 5G. This is because there is not a unique radio interface configuration able to fit all the different service requirements. As a consequence, 5G networks are being designed to support different radio interface configurations and mechanisms to multiplex these different services with different configurations in the same available spectrum. This concept is known as Network Slicing, and isa 5G key feature which needs to be supported end to end in the network (Radio Access, Transport and Core Network). In this way 5G Radio Access Networks (RAN) will add the resource allocation for different services problem to the user resource allocation traditional one. In this context, as both users and services scheduling is being left to vendor implementation by the standard, an extensive field of research is open. Different simulation tools have been developed for research purposes during the last years. However, as not so many of them are free, easy to use, and particularly none of the available ones supports Network Slicing at RAN level, this work presents a new simulator as its main contribution. Py5cheSim is a simple, flexible and open-source simulator based on Pythonand specially oriented to test different scheduling algorithms for 5G different types of services through a simple implementation of RAN Slicing feature. Its architecture allows to develop and integrate new scheduling algorithms in a easy and straight forward way. Furthermore, the use of Python provides enough versatility to even use Machine Learning tools for the development of new scheduling algorithms. The present work introduces the main 5G RAN design concepts which were taken as a baseline to develop the simulation tool. It also describes its design and implementation choices followed by the executed validation tests and its main results. Additionally this work presents a few use cases examples to show the developed tool’s potential providing a primary analysis of traditional scheduling algorithms for the new types of services envisioned by the technology. Finally it concludes about the developed tool contribution, the example results along with possible research lines and future versions improvements

    Multi-cell Coordination Techniques for DL OFDMA Multi-hop Cellular Networks

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    The main objective of this project is to design coordinated spectrum sharing and reuse techniques among cells with the goal of mitigating interference at the cell edge and enhance the overall system capacity. The performance of the developed algorithm will be evaluated in an 802.16m (WiMAX) environment. In conventional cellular networks, frequency planning is usually considered to keep an acceptable signal-to-interference-plus noise ratio (SINR) level, especially at cell boundaries. Frequency assignations are done under a cell-by-cell basis, without any coordination between them to manage interference. Particularly this approach, however, hampers the system spectral efficiency at low reuse rates. For a specific reuse factor, the system throughput depends highly on the mobile station (MS) distribution and the channel conditions of the users to be served. If users served from different base stations (BS) experience a low level of interference, radio resources may be reused, applying a high reuse factor and thus, increasing the system spectral efficiency. On the other side, if the served users experience large interference, orthogonal transmissions are better and therefore a lower frequency reuse factor should be used. As a consequence, a dynamic reuse factor is preferable over a fixed one. This work addresses the design of joint multi-cell resource allocation and scheduling with coordination among neighbouring base stations (outer coordination) or sectors belonging to the same one (inner coordination) as a way to achieve flexible reuse factors. We propose a convex optimization framework to address the problem of coordinating bandwidth allocation in BS coordination problems. The proposed framework allows for different scheduling policies, which have an impact on the suitability of the reuse factor, since they determine which users have to be served. Therefore, it makes sense to consider the reuse factor as a result of the scheduling decision. To support the proposed techniques the BSs shall be capable of exchanging information with each other (decentralized approach) or with some control element in the back-haul network as an ASN gateway or some self-organization control entity (centralized approach)

    Downlink transmission in multi-carrier systems with reduced feedback

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    System Level Analysis of LTE-Advanced:with Emphasis on Multi-Component Carrier Management

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