Resource-on-demand schemes in 802.11 WLANs with non-zero start-up times

Increasing the density of access points is one of the most effective mechanisms to cope with the growing traffic demand in wireless networks. To prevent energy wastage at low loads, a resource-on-demand (RoD) scheme is required to opportunistically (de)activate access points as network traffic varies. While previous publications have analytically modeled these schemes in the past, they have assumed that resources are immediately available when activated, an assumption that leads to inaccurate results and might result in inappropriate configurations of the RoD scheme. In this paper, we analyze a general RoD scenario with N access points and non-zero start-up times. We first present an exact analytical model that accurately predicts performance but has a high computational complexity, and then derive a simplified analysis that sacrifices some accuracy in exchange for a much lower computational cost. To illustrate the practicality of this model, we present the design of a simple configuration algorithm for RoD. Simulation results confirm the validity of the analyses, and the effectiveness of the configuration algorithm

An efficient genetic algorithm for large-scale transmit power control of dense and robust wireless networks in harsh industrial environments

The industrial wireless local area network (IWLAN) is increasingly dense, due to not only the penetration of wireless applications to shop floors and warehouses, but also the rising need of redundancy for robust wireless coverage. Instead of simply powering on all access points (APs), there is an unavoidable need to dynamically control the transmit power of APs on a large scale, in order to minimize interference and adapt the coverage to the latest shadowing effects of dominant obstacles in an industrial indoor environment. To fulfill this need, this paper formulates a transmit power control (TPC) model that enables both powering on/off APs and transmit power calibration of each AP that is powered on. This TPC model uses an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects, to enable accurate yet simple coverage prediction. An efficient genetic algorithm (GA), named GATPC, is designed to solve this TPC model even on a large scale. To this end, it leverages repair mechanism-based population initialization, crossover and mutation, parallelism as well as dedicated speedup measures. The GATPC was experimentally validated in a small-scale IWLAN that is deployed a real industrial indoor environment. It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC. Moreover, sensitivity analysis was performed to reveal the produced interference and the qualification rate of GATPC in function of varying target coverage percentage as well as number and placement direction of dominant obstacles. (C) 2018 Elsevier B.V. All rights reserved

Optimal configuration of a resource-on-demand 802.11 WLAN with non-zero start-up times

Resource on Demand in 802.11 Wireless LANs is receiving an increasing attention, with its feasibility already proved in practice and some initial analytical models available. However, while these models have assumed that access points (APs) start up in zero time, experimentation has showed that this is hardly the case. In this work, we provide a new model to account for this time in the simple case, of a WLAN formed by two APs where the second AP is switched on/off dynamically to adapt to the traffic load and reduce the overall power consumption, and show that it significantly alters the results when compared to the zero start-up time case, both qualitatively and quantitatively. Our findings show that having a non-zero start up time modifies significantly the trade-offs between power consumption and performance that appears on Resource on Demand solutions. Finally, we propose an algorithm to optimize the energy consumption of the network while guaranteeing a given performance bound.The work of J. Ortín was partly supported by the Centro Universitario de la Defensa through project CUD2013-05, Gobierno de Aragon (research group T98) and the European Social Fund (ESF). The work of P. Serrano and C. Donato was partly supported by the European Commission under grant agreement H2020-ICT-2014-2-671563 (Flex5Gware) and by the Spanish Ministry of Economy and Competitiveness under grant agreement TEC2014-58964-C2-1-R (DRONEXT)

Efficient energy management in ultra-dense wireless networks

The increase in demand for more network capacity has led to the evolution of wireless networks from being largely Heterogeneous (Het-Nets) to the now existing Ultra-dense (UDNs). In UDNs, small cells are densely deployed with the goal of shortening the physical distance between the base stations (BSs) and the UEs, so as to support more user equipment (UEs) at peak times while ensuring high data rates. Compared to Het-Nets, Ultra-dense networks (UDNs) have many advantages. These include, more network capacity, higher flexibility to routine configurations, and more suitability to achieve load-balancing, hence, fewer blind spots as well as lower call blocking probability. It should be noted that, in practice, due to the high density of deployed small cells in Ultra-Dense Networks, a number of issues, or rather concerns, come with this evolution from Het-Nets. Among these issues include problems with efficient radio resource management, user cell association, inter- and intra-cell interference management and, last but not least, efficient energy consumption. Some of these issues which impact the overall network efficiency are largely due to the use of obsolete algorithms, especially those whose resource allocation is based solely on received signal power (RSSP). In this paper, the focus is solely on the efficient energy management dilemma and how to optimally reduce the overall network energy consumption. Through an extensive literature review, a detailed report into the growing concern of efficient energy management in UDNs is provided in Chapter 2. The literature review report highlights the classification as well as the evolution of some of the Mobile Wireless Technologies and Mobile Wireless Networks in general. The literature review report provides reasons as to why the energy consumption issue has become a very serious concern in UltraDense networks as well as the various techniques and measures taken to mitigate this. It is shown that, due to the increasing Mobile Wireless Systems’ carbon footprint which carries serious negative environmental impact, and the general need to lower operating costs by the network operators, the management of energy consumption increases in priority. By using the architecture of a Fourth Generation Long Term Evolution (4G-LTE) UltraDense Network, the report further shows that more than 65% of the overall energy consumption is by the access network and base stations in particular. This phenomenon explains why most attention in energy efficiency management in UDNs is largely centred on reducing the energy consumption of the deployed base stations more than any other network components like the data servers or backhauling features used. Furthermore, the report also provides detailed information on the methods/techniques, their classification, implementation, as well as a critical analysis of the said implementations in literature. This study proposes a sub-optimal algorithm and Distributed Cell Resource Allocation with a Base Station On/Off scheme that aims at reducing the overall base station power consumption in UDNs, while ensuring that the overall Quality of Service (QoS) for each User Equipment (UE) as specified in its service class is met. The modeling of the system model used and hence formulation of the Network Energy Efficiency (NEE) optimization problem is done viii using stochastic geometry. The network model comprises both evolved Node B (eNB) type macro and small cells operating on different frequency bands as well as taking into account factors that impact NEE such as UE mobility, UE spatial distribution and small cells spatial distribution. The channel model takes into account signal interference from all base stations, path loss, fading, log normal shadowing, modulation and coding schemes used on each UE’s communication channels when computing throughout. The power consumption model used takes into account both static (site cooling, circuit power) and active (transmission or load based) base station power consumption. The formulation of the NEE optimization problem takes into consideration the user’s Quality-of-service (QoS), inter-cell interference, as well as each user’s spectral efficiency and coverage/success probability. The formulated NEE optimization problem is of type Nondeterministic Polynomial time (NP)-hard, due to the user-cell association. The proposed solution to the formulated optimization problem makes use of constraint relaxation to transform the NP-hard problem into a more solvable, convex and linear optimization one. This, combined with Lagrangian dual decomposition, is used to create a distributed solution. After cellassociation and resource allocation phases, the proposed solution in order to further reduce power consumption performs Cell On/Off. Then, by using the computer simulation tools/environments, the “Distributed Resource Allocation with Cell On/Off” scheme’s performance, in comparison to four other resource allocation schemes, is analysed and evaluated given a number of different network scenarios. Finally, the statistical and mathematical results generated through the simulations indicate that the proposed scheme is the closest in NEE performance to the Exhaustive Search algorithm, and hence superior to the other sub-optimal algorithms it is compared to

Reducing the power consumption in LTE-advanced wireless access networks by a capacity based deployment tool

As both the bit rate required by applications on mobile devices and the number of those mobile devices are steadily growing, wireless access networks need to be expanded. As wireless networks also consume a lot of energy, it is important to develop energy-efficient wireless access networks in the near future. In this study, a capacity-based deployment tool for the design of energy-efficient wireless access networks is proposed. Capacity-based means that the network responds to the instantaneous bit rate requirements of the users active in the selected area. To the best of our knowledge, such a deployment tool for energy-efficient wireless access networks has never been presented before. This deployment tool is applied to a realistic case in Ghent, Belgium, to investigate three main functionalities incorporated in LTE-Advanced: carrier aggregation, heterogeneous deployments, and Multiple-Input Multiple-Output (MIMO). The results show that it is recommended to introduce femtocell base stations, supporting both MIMO and carrier aggregation, into the network (heterogeneous deployment) to reduce the network's power consumption. For the selected area and the assumptions made, this results in a power consumption reduction up to 70%. Introducing femtocell base stations without MIMO and carrier aggregation can already result in a significant power consumption reduction of 38%

Analysis, characterization and optimization of the energy efficiency on softwarized mobile platforms

Mención Internacional en el título de doctorLa inminente 5ª generación de sistemas móviles (5G) está a punto de revolucionar la industria, trayendo una nueva arquitectura orientada a los nuevos mercados verticales y servicios. Debido a esto, el 5G Infrastructure Public Private Partnership (5G-PPP) ha especificado una lista de Indicadores de Rendimiento Clave (KPI) que todo sistema 5G tiene que soportar, por ejemplo incrementar por 1000 el volumen de datos, de 10 a 100 veces m´as dispositivos conectados o consumos energéticos 10 veces inferiores. Con el fin de conseguir estos requisitos, se espera expandir los despligues actuales usando mas Puntos de Acceso (PoA) incrementando así su densidad con múltiples tecnologías inalámbricas. Esta estrategia de despliegue masivo tiene una contrapartida en la eficiencia energética, generando un conflicto con el KPI de reducir por 10 el consumo energético. En este contexto, la comunidad investigadora ha propuesto nuevos paradigmas para alcanzar los requisitos impuestos para los sistemas 5G, siendo materializados en tecnologías como Redes Definidas por Software (SDN) y Virtualización de Funciones de Red (NFV). Estos nuevos paradigmas son el primer paso hacia la softwarización de los despliegues móviles, incorporando nuevos grados de flexibilidad y reconfigurabilidad de la Red de Acceso Radio (RAN). En esta tesis, presentamos primero un análisis detallado y caracterización de las redes móviles softwarizadas. Consideramos el software como la base de la nueva generación de redes celulares y, por lo tanto, analizaremos y caracterizaremos el impacto en la eficiencia energética de estos sistemas. La primera meta de este trabajo es caracterizar las plataformas software disponibles para Radios Definidas por Software (SDR), centrándonos en las dos soluciones principales de código abierto: OpenAirInterface (OAI) y srsLTE. Como resultado, proveemos una metodología para analizar y caracterizar el rendimiento de estas soluciones en función del uso de la CPU, rendimiento de red, compatibilidad y extensibilidad de dicho software. Una vez hemos entendido qué rendimiento podemos esperar de este tipo de soluciones, estudiamos un prototipo SDR construido con aceleración hardware, que emplea una plataformas basada en FPGA. Este prototipo está diseñado para incluir capacidad de ser consciente de la energía, permiento al sistema ser reconfigurado para minimizar la huella energética cuando sea posible. Con el fin de validar el diseño de nuestro sistema, más tarde presentamos una plataforma para caracterizar la energía que será empleada para medir experimentalmente el consumo energético de dispositivos reales. En nuestro enfoque, realizamos dos tipos de análisis: a pequeña escala de tiempo y a gran escala de tiempo. Por lo tanto, para validar nuestro entorno de medidas, caracterizamos a través de análisis numérico los algoritmos para la Adaptación de la Tasa (RA) en IEEE 802.11, para entonces comparar nuestros resultados teóricos con los experimentales. A continuación extendemos nuestro análisis a la plataforma SDR acelerada por hardware previamente mencionada. Nuestros resultados experimentales muestran que nuestra sistema puede en efecto reducir la huella energética reconfigurando el despligue del sistema. Entonces, la escala de tiempos es elevada y presentamos los esquemas para Recursos bajo Demanda (RoD) en despliegues de red ultra-densos. Esta estrategia está basada en apagar/encender dinámicamente los elementos que forman la red con el fin de reducir el total del consumo energético. Por lo tanto, presentamos un modelo analítico en dos sabores, un modelo exacto que predice el comportamiento del sistema con precisión pero con un alto coste computacional y uno simplificado que es más ligero en complejidad mientras que mantiene la precisión. Nuestros resultados muestran que estos esquemas pueden efectivamente mejorar la eficiencia energética de los despliegues y mantener la Calidad de Servicio (QoS). Con el fin de probar la plausibilidad de los esquemas RoD, presentamos un plataforma softwarizada que sigue el paradigma SDN, OFTEN (OpenFlow framework for Traffic Engineering in mobile Network with energy awareness). Nuestro diseño está basado en OpenFlow con funcionalidades para hacerlo consciente de la energía. Finalmente, un prototipo real con esta plataforma es presentando, probando así la plausibilidad de los RoD en despligues reales.The upcoming 5th Generation of mobile systems (5G) is about to revolutionize the industry, bringing a new architecture oriented to new vertical markets and services. Due to this, the 5G-PPP has specified a list of Key Performance Indicator (KPI) that 5G systems need to support e.g. increasing the 1000 times higher data volume, 10 to 100 times more connected devices or 10 times lower power consumption. In order to achieve these requirements, it is expected to expand the current deployments using more Points of Attachment (PoA) by increasing their density and by using multiple wireless technologies. This massive deployment strategy triggers a side effect in the energy efficiency though, generating a conflict with the “10 times lower power consumption” KPI. In this context, the research community has proposed novel paradigms to achieve the imposed requirements for 5G systems, being materialized in technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). These new paradigms are the first step to softwarize the mobile network deployments, enabling new degrees of flexibility and reconfigurability of the Radio Access Network (RAN). In this thesis, we first present a detailed analysis and characterization of softwarized mobile networking. We consider software as a basis for the next generation of cellular networks and hence, we analyze and characterize the impact on the energy efficiency of these systems. The first goal of this work is to characterize the available software platforms for Software Defined Radio (SDR), focusing on the two main open source solutions: OAI and srsLTE. As result, we provide a methodology to analyze and characterize the performance of these solutions in terms of CPU usage, network performance, compatibility and extensibility of the software. Once we have understood the expected performance for such platformsc, we study an SDR prototype built with hardware acceleration, that employs a FPGA based platform. This prototype is designed to include energy-awareness capabilites, allowing the system to be reconfigured to minimize the energy footprint when possible. In order to validate our system design, we later present an energy characterization platform that we will employ to experimentally measure the energy consumption of real devices. In our approach, we perform two kind of analysis: at short time scale and large time scale. Thus, to validate our approach in short time scale and the energy framework, we have characterized though numerical analysis the Rate Adaptation (RA) algorithms in IEEE 802.11, and then compare our theoretical results to the obtained ones through experimentation. Next we extend our analysis to the hardware accelerated SDR prototype previously mentioned. Our experimental results show that our system can indeed reduce the energy footprint reconfiguring the system deployment. Then, the time scale of our analysis is elevated and we present Resource-on-Demand (RoD) schemes for ultradense network deployments. This strategy is based on dynamically switch on/off the elements that form the network to reduce the overall energy consumption. Hence, we present a analytic model in two flavors, an exact model that accurately predicts the system behaviour but high computational cost and a simplified one that is lighter in complexity while keeping the accuracy. Our results show that these schemes can effectively enhance the energy efficiency of the deployments and mantaining the Quality of Service (QoS). In order to prove the feasibility of RoD, we present a softwarized platform that follows the SDN paradigm, the OFTEN (Open Flow framework for Traffic Engineering in mobile Networks with energy awareness) framework. Our design is based on OpenFlow with energy-awareness functionalities. Finally, a real prototype of this framework is presented, proving the feasibility of the RoD in real deployments.FP7-CROWD (2013-2015) CROWD (Connectivity management for eneRgy Optimised Wireless Dense networks).-- H2020-Flex5GWare (2015-2017) Flex5GWare (Flexible and efficient hardware/software platforms for 5G network elements and devices).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Gramaglia , Marco.- Secretario: José Nuñez.- Vocal: Fabrizio Giulian

Fast Cell Discovery in mm-wave 5G Networks with Context Information

The exploitation of mm-wave bands is one of the key-enabler for 5G mobile radio networks. However, the introduction of mm-wave technologies in cellular networks is not straightforward due to harsh propagation conditions that limit the mm-wave access availability. Mm-wave technologies require high-gain antenna systems to compensate for high path loss and limited power. As a consequence, directional transmissions must be used for cell discovery and synchronization processes: this can lead to a non-negligible access delay caused by the exploration of the cell area with multiple transmissions along different directions. The integration of mm-wave technologies and conventional wireless access networks with the objective of speeding up the cell search process requires new 5G network architectural solutions. Such architectures introduce a functional split between C-plane and U-plane, thereby guaranteeing the availability of a reliable signaling channel through conventional wireless technologies that provides the opportunity to collect useful context information from the network edge. In this article, we leverage the context information related to user positions to improve the directional cell discovery process. We investigate fundamental trade-offs of this process and the effects of the context information accuracy on the overall system performance. We also cope with obstacle obstructions in the cell area and propose an approach based on a geo-located context database where information gathered over time is stored to guide future searches. Analytic models and numerical results are provided to validate proposed strategies.Comment: 14 pages, submitted to IEEE Transaction on Mobile Computin

Interference-aware coordinated power allocation in autonomous Wi-Fi environment

Self-managed access points (APs) with growing intelligence can optimize their own performances but pose potential negative impacts on others without energy ef ciency. In this paper, we focus on modeling the coordinated interaction among interest-independent and self-con gured APs, and conduct the power allocation case study in the autonomous Wi-Fi scenario. Speci cally, we build a `coordination Wi-Fi platform (CWP), a public platform for APs interacting with each other. OpenWrt-based APs in the physical world are mapped to virtual agents (VAs) in CWP, which communicate with each other through a standard request-reply process de ned as AP talk protocol (ATP).With ATP, an active interference measurement methodology is proposed re ecting both in-range interference and hidden terminal interference, and the Nash bargaining-based power control is further formulated for interference reductions. CWP is deployed in a real of ce environment, where coordination interactions between VAs can bring a maximum 40-Mb/s throughput improvement with the Nash bargaining-based power control in the multi-AP experiments