Building Programmable Wireless Networks: An Architectural Survey

In recent times, there have been a lot of efforts for improving the ossified Internet architecture in a bid to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through co-located data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. The emergence of "programmable wireless networks", that allow greater flexibility, ease of management and configurability, is a step in the right direction to overcome the aforementioned shortcomings of the wireless networks. In this paper, we provide a broad overview of the architectures proposed in literature for building programmable wireless networks focusing primarily on three popular techniques, i.e., software defined networks, cognitive radio networks, and virtualized networks. This survey is a self-contained tutorial on these techniques and its applications. We also discuss the opportunities and challenges in building next-generation programmable wireless networks and identify open research issues and future research directions.Comment: 19 page

Cloud computing for wireless systems

In recent years, wireless technologies are advancing very rapidly causing a strong demand for data processing centers. Currently wireless system processing is done in the same base station, but the deployment of fiber optic networks raises the possibility of moving all that processing to farms of PCs, or Clouds, applying Software Radio concept in all its fullness. With this new paradigm several open questions about how the scheduler or management should be for these new structures arise. One of the available tools, with suitable functionalities, to perform management tasks in cloud arena is OpenStack. Thus, OpenStack, an open source project designed to implement large-scale Clouds, offers a platform to concentrate all processing in a single geographic location. Unfortunately Cloud system was designed to provide services to Internet servers, so this work is aimed at analyzing the feasibility of a Cloud for dealing with signal processing of wireless waveforms and take care of the real-time performance of software-based wireless implementations

Estudio de viabilidad de un SDR Cloud

En la década de los 90, las operadoras hicieron una gran inversión para ofrecer a sus usuarios comunicaciones inalámbricas. Entonces, los usuarios tenían varios dispositivos, cada uno con una única función, un teléfono para hacer llamadas, un ordenador para tener acceso a internet, un dispositivo para GPS, etc. La tecnología ha evolucionado hacia la unión de estos dispositivos hardware en un solo terminal. Actualmente, los usuarios requieren más ancho de banda, lo que obliga a las operadoras a actualizar sus estándares a otros de nueva generación, que proporcionan una mejor eficiencia espectral. Esta evolución se produce a un ritmo frenético y obliga, tanto a usuarios como a operadoras, a adecuar sus dispositivos. Los equipos actuales no se han diseñado para estas adaptaciones con lo que las operadoras han de hacer una gran inversión para remplazar sus equipos, todavía operativos, por otros con el nuevo estándar. Ante esta situación nace el Software Radio, que permite reutilizar estos equipos, adaptándolos a nuevas tecnologías de acceso radio. Software Radio, o Software-Defined Radio (SDR), es un concepto aplicable tanto a terminales móviles como a estaciones base. Este proyecto estudia la viabilidad de una nueva infraestructura de acceso radio para la ciudad de Barcelona, uniendo los conceptos SDR y Cloud Computing para diseñar y gestionar estaciones base de futuro y de esta manera facilitar la compartición de recursos de cómputo y una mayor eficiencia de su uso.English: In the 90's, operators made large investments for providing wireless communications services to capture clients. Users by then had multiple devices, each with a single functionality: a phone to call, a computer to access the Internet, a GPS device for receiving location information, etc. Technology has progressed and today’s gadgets unify these functionalities in a single device. Users still require higher bandwidths. Operators therefore need to upgrade their wireless communications infrastructure to new standards, which provide improved spectral efficiency. The change occurs at a frenetic pace and requires both, users and operators, to replace their devices. The current equipment has been designed for the available systems and services (2G and 3G) with little adaptation possibilities. Operators then need to make major investments for replacing existing equipment to offer new services. The software-defined radio (SDR) concept, on the other hand, allows reusing hardware for implementing new radio access technologies. Software Radio or SDR is a concept applicable to both mobile terminals and base stations. This project studies the viability of a new radio access infrastructure, the SDR Cloud, applied to the city of Barcelona. SDR clouds join SDR and Cloud Computing concepts to design and manage future base stations. They centralize the digital-signal processing part of base station transceivers, facilitating the computing resource sharing for improving the resource efficiencies and system flexibility

Cloud computing for wireless systems

In recent years, wireless technologies are advancing very rapidly causing a strong demand for data processing centers. Currently wireless system processing is done in the same base station, but the deployment of fiber optic networks raises the possibility of moving all that processing to farms of PCs, or Clouds, applying Software Radio concept in all its fullness. With this new paradigm several open questions about how the scheduler or management should be for these new structures arise. One of the available tools, with suitable functionalities, to perform management tasks in cloud arena is OpenStack. Thus, OpenStack, an open source project designed to implement large-scale Clouds, offers a platform to concentrate all processing in a single geographic location. Unfortunately Cloud system was designed to provide services to Internet servers, so this work is aimed at analyzing the feasibility of a Cloud for dealing with signal processing of wireless waveforms and take care of the real-time performance of software-based wireless implementations

Modeling and resource management of SDR Clouds

This TFC models software-defined radio (SDR) processing chains and manages their distributed execution on SDR clouds. We present models of UMTS processing chains for different bit rates. These chains model the digital processing requirements of a transmitter and receiver in the base station. Therefore, we analyze the users multiplexing in WCDMA because it has implications on the computing resources and its correct management. We propose different management strategies, implement one and evaluate its correct functionality. The solution we promote is based on defining a ghost function that captures the data flow dependencies between the chip-level and bit-level processing part of WCDMA. The chip-level processing chain processes signals of multiple users, whereas the bit-level processing chain processes a single user’s signal. The simulations are executed with an appropriate user load, which is part of our investigation. For the development of this TFC we are provided of a mapping algorithm for the computing resource management in a simulation environment. This algorithm runs a trellis evaluating the costs of the different paths during the mapping process of the signal processing blocks of a processing chain to the distributed computing resources of the multiprocessors platform

Radio and computing resource management in SDR clouds

The aim of this thesis is defining and developing the concept of an efficient management of radio and computing resources in an SDR cloud. The SDR cloud breaks with today's cellular architecture. A set of distributed antennas are connected by optical fibre to data processing centres. The radio and computing infrastructure can be shared between different operators (virtualization), reducing costs and risks, while increasing the capacity and creating new business models and opportunities. The data centre centralizes the management of all system resources: antennas, spectrum, computing, routing, etc. Specially relevant is the computing resource management (CRM), whose objective is dynamically providing sufficient computing resources for a real-time execution of signal processing algorithms. Current CRM techniques are not designed for wireless applications. We demonstrate that this imposes a limit on the wireless traffic a CRM entity is capable to support. Based on this, a distributed management is proposed, where multiple CRM entities manage a cluster of processors, whose optimal size is derived from the traffic density. Radio resource management techniques (RRM) also need to be adapted to the characteristics of the new SDR cloud architecture. We introduce a linear cost model to measure the cost associated to the infrastructure resources consumed according to the pay-per-use model. Based on this model, we formulate the efficiency maximization power allocation problem (EMPA). The operational costs per transmitted bit achieved by EMPA are 6 times lower than with traditional power allocation methods. Analytical solutions are obtained for the single channel case, with and without channel state information at the transmitter. It is shown that the optimal transmission rate is an increasing function of the product of the channel gain with the operational costs divided by the power costs. The EMPA solution for multiple channels has the form of water-filling, present in many power allocation problems. In order to be able to obtain insights about how the optimal solution behaves as a function of the problem parameters, a novel technique based on ordered statistics has been developed. This technique allows solving general water-filling problems based on the channel statistics rather than their realization. This approach has allowed designing a low complexity EMPA algorithm (2 to 4 orders of magnitude faster than state-of-the-art algorithms). Using the ordered statistics technique, we have shown that the optimal transmission rate behaviour with respect to the average channel gains and cost parameters is equivalent to the single channel case and that the efficiency increases with the number of available channels. The results can be applied to design more efficient SDR clouds. As an example, we have derived the optimal ratio of number of antennas per user that maximizes the efficiency. As new users enter and leave the network, this ratio should be kept constant, enabling and disabling antennas dynamically. This approach exploits the dynamism and elasticity provided by the SDR cloud. In summary, this dissertation aims at influencing towards a change in the communications system management model (typically RRM), considering the introduction of the new infrastructure model (SDR cloud), new business models (based on Cloud Computing) and a more conciliatory view of an efficient resource management, not only focused on the optimization of the spectrum usage.El objetivo de esta tesis es de nir y desarrollar el concepto de gesti on e ciente de los recursos de radio y computaci on en un SDR cloud. El SDR cloud rompe con la estructura del sistema celular actual. Un conjunto de antenas distribuidas se conectan a centros de procesamiento mediante enlaces de comunicaci on de bra optica. La infraestructura de radio y procesamiento puede ser compartida entre distintos operadores (virtualizacion), disminuyendo costes y riesgos, aumentando la capacidad y abriendo nuevos modelos y oportunidades de negocio. La centralizaci on de la gesti on del sistema viene soportada por el centro de procesamiento, donde se realiza una gesti on de todos los recursos del sistema: antenas, espectro, computaci on, enrutado, etc. Resulta de especial relevancia la gesti on de los recursos de computaci on (CRM) cuyo objetivo es el de proveer, din amicamente, de su cientes recursos de computaci on para la ejecuci on en tiempo real de algoritmos de procesado del señal. Las t ecnicas actuales de CRM no han sido diseñadas para aplicaciones de comunicaciones. Demostramos que esta caracter stica impone un l ímite en el tr áfi co que un gestor CRM puede soportar. En base a ello, proponemos una gesti on distribuida donde m ultiples entidades CRM gestionan grupos de procesadores, cuyo tamaño optimo se deriva de la densidad de tr áfi co. Las t ecnicas actuales de gesti on de recursos radio (RRM) tambi en deben ser adaptadas a las caracter sticas de la nueva arquitectura SDR cloud. Introducimos un modelo de coste lineal que caracteriza los costes asociados al consumo de recursos de la infraestructura seg un el modelo de pago-por-uso. A partir de este modelo, formulamos el problema de asignaci on de potencia de m axima e ciencia (EMPA). Mediante una asignaci on EMPA, los costes de operaci on por bit transmitido son del orden de 6 veces menores que con los m etodos tradicionales. Se han obtenido soluciones anal ticas para el caso de un solo canal, con y sin informacion del canal disponible en el transmisor, y se ha demostrado que la velocidad optima de transmisi on es una funci on creciente del producto de la ganancia del canal por los costes operativos dividido entre los costes de potencia. La soluci on EMPA para varios canales satisface el modelo "water- lling", presente en muchos tipos de optimizaci on de potencia. Con el objetivo de conocer c omo esta se comporta en funci on de los par ametros del sistema, se ha desarrollado una t ecnica nueva basada en estadí sticas ordenadas. Esta t ecnica permite solucionar el problema del water- lling bas andose en la estadí stica del canal en vez de en su realizaci on. Este planteamiento, despu es de profundos an alisis matem aticos, ha permitido desarrollar un algoritmo de asignaci on de potencia de baja complejidad (2 a 4 ordenes de magnitud m as r apido que el estado del arte). Mediante esta t ecnica, se ha demostrado que la velocidad optima de transmisi on se comporta de forma equivalente al caso de un solo canal y que la e ciencia incrementa a medida que aumentan el numero de canales disponibles. Estos resultados pueden aplicarse a diseñar un SDR cloud de forma m as e ciente. A modo de ejemplo, hemos obtenido el ratio optimo de n umero de antenas por usuario que maximiza la e ciencia. A medida que los usuarios entran y salen de la red, este ratio debe mantenerse constante, a fin de mantener una efi ciencia lo m as alta posible, activando o desactivando antenas din amicamente. De esta forma se explota completamente el dinamismo ofrecido por una arquitectura el astica como el SDR cloud. En de nitiva, este trabajo pretende incidir en un cambio del modelo de gesti on de un sistema de comunicaciones (t ípicamente RRM) habida cuenta de la introducci on de una nueva infraestructura (SDR cloud), nuevos modelos de negocio (basados en Cloud Computing) y una visi on m as integradora de la gesti on e ciente de los recursos del sistema, no solo centrada en la optimizaci on del uso del espectro

Cooperative Uplink Inter-Cell Interference (ICI) Mitigation in 5G Networks

In order to support the new paradigm shift in fifth generation (5G) mobile communication, radically different network architectures, associated technologies and network operation algorithms, need to be developed compared to existing fourth generation (4G) cellular solutions. The evolution toward 5G mobile networks will be characterized by an increasing number of wireless devices, increasing device and service complexity, and the requirement to access mobile services ubiquitously. To realise the dramatic increase in data rates in particular, research is focused on improving the capacity of current, Long Term Evolution (LTE)-based, 4G network standards, before radical changes are exploited which could include acquiring additional spectrum. The LTE network has a reuse factor of one; hence neighbouring cells/sectors use the same spectrum, therefore making the cell-edge users vulnerable to heavy inter cell interference in addition to the other factors such as fading and path-loss. In this direction, this thesis focuses on improving the performance of cell-edge users in LTE and LTE-Advanced networks by initially implementing a new Coordinated Multi-Point (CoMP) technique to support future 5G networks using smart antennas to mitigate cell-edge user interference in uplink. Successively a novel cooperative uplink inter-cell interference mitigation algorithm based on joint reception at the base station using receiver adaptive beamforming is investigated. Subsequently interference mitigation in a heterogeneous environment for inter Device-to-Device (D2D) communication underlaying cellular network is investigated as the enabling technology for maximising resource block (RB) utilisation in emerging 5G networks. The proximity of users in a network, achieving higher data rates with maximum RB utilisation (as the technology reuses the cellular RB simultaneously), while taking some load off the evolved Node B (eNodeB) i.e. by direct communication between User Equipment (UE), has been explored. Simulation results show that the proximity and transmission power of D2D transmission yields high performance gains for D2D receivers, which was demonstrated to be better than that of cellular UEs with better channel conditions or in close proximity to the eNodeB in the network. It is finally demonstrated that the application, as an extension to the above, of a novel receiver beamforming technique to reduce interference from D2D users, can further enhance network performance. To be able to develop the aforementioned technologies and evaluate the performance of new algorithms in emerging network scenarios, a beyond the-state-of-the-art LTE system-level-simulator (SLS) was implemented. The new simulator includes Multiple-Input Multiple-Output (MIMO) antenna functionalities, comprehensive channel models (such as Wireless World initiative New Radio II i.e. WINNER II) and adaptive modulation and coding schemes to accurately emulate the LTE and LTE-A network standards

Resource management for software-defined radio clouds

Software-defined radio (SDR) clouds combine SDR concepts with cloud computing technology for designing and managing future base stations. They provide a scalable solution for the evolution of wireless communications. The authors focus on the resource management implications and propose a hierarchical approach for dynamically managing the real-time computing constraints of wireless communications systems that run on the SDR cloud

Resource management for software-defined radio clouds

Software-defined radio (SDR) clouds combine SDR concepts with cloud computing technology for designing and managing future base stations. They provide a scalable solution for the evolution of wireless communications. The authors focus on the resource management implications and propose a hierarchical approach for dynamically managing the real-time computing constraints of wireless communications systems that run on the SDR cloud