Scalable base station switching framework for green cellular networks

With the recent unprecedented growth in the wireless market, network operators are obliged not only to find new techniques including dense deployment of base stations (BSs) in order to support high data rate services and high user density, but also to reduce the operating costs and energy consumption of various network elements. To solve these challenges, powering down certain BSs during low-traffic periods, so-called BS sleeping, has emerged as an effective green communications paradigm. While BS sleeping offers the potential to significantly lower energy consumption, it also raises many challenges, since when a BS is switched off, this can lead to, for example, coverage holes, sudden degradation in quality of service (QoS), higher transmit power dissipation in off-cell mobile stations (MSs), an inability to rapidly power up/down equipment and finally, a failure to uphold regulatory requirements. In order to realise greener network designs which both maximise energy savings whilst guaranteeing QoS, innovative BS switching mechanisms need to be developed. This thesis presents a novel BS switching framework which improves energy efficiency (EE) in comparison with existing approaches, while guaranteeing the minimum QoS and seamless services. The major technical contributions in this framework are: i) a new BS to relay station (RS) switching model where certain BSs are switched to RS mode rather than being turned off, firstly using a fixed threshold based switching algorithm utilizing temporal traffic diversity, and ii) then subsequently by means of an adaptive threshold by exploiting the inherently asymmetric traffic profile between cells, i.e., by exploiting both the temporal and spatial traffic diversity; iii) a traffic-and-interference-aware BS switching strategy that considers the impact of inter-cell interference in the decision making process to dynamically determine the best BS set to be kept active for improved EE; and finally iv) a novel scalable multimode BS switching model which enables each BS to operate in different power modes i.e., macro/micro/sleep to explore energy savings potential even at higher traffic conditions. The thesis findings conclusively confirm this new BS switching framework provides significant EE improvements from both BS and MS perspectives, under diverse network conditions and represents a notable step towards greener communications

Energy Efficient Cluster Based Routing Protocol for Dynamic and Static Nodes in Wireless Sensor Network

Power consumption is considered one of the most significant challenges in the wireless network sensors (WSNs). In this paper, an investigation of the power consumption is done by making a comparison between static and dynamic WSNs. We have compared the results of the static network with the results of the dynamic network. Static and dynamic wireless Sensor networks have the same architecture (Homogenous) and proposed protocol. Depending on the suggested protocol, the simulation results show that the energy consumption in the static wireless sensor network was less than the dynamic wireless sensor network. However, moving the sensors in the dynamic WSN present real improvement in delivering packets to the base station. In the proposed routing protocol, transmitting data process is done in a hierarchal way. Cheap sensors are introduced and deploy them intensively to improve the QoS in the network. The final results and the conclusion are reported

Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks

Energy sustainable paradigms and methods for future mobile networks: A survey

In this survey, we discuss the role of energy in the design of future mobile networks and, in particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a means to decrease the environmental footprint of 5G technology. To take full advantage of the harvested (renewable) energy, while still meeting the quality of service required by dense 5G deployments, suitable management techniques are here reviewed, highlighting the open issues that are still to be solved to provide eco-friendly and cost-effective mobile architectures. Several solutions have recently been proposed to tackle capacity, coverage and efficiency problems, including: C-RAN, Software Defined Networking (SDN) and fog computing, among others. However, these are not explicitly tailored to increase the energy efficiency of networks featuring renewable energy sources, and have the following limitations: (i) their energy savings are in many cases still insufficient and (ii) they do not consider network elements possessing energy harvesting capabilities. In this paper, we systematically review existing energy sustainable paradigms and methods to address points (i) and (ii), discussing how these can be exploited to obtain highly efficient, energy self-sufficient and high capacity networks. Several open issues have emerged from our review, ranging from the need for accurate energy, transmission and consumption models, to the lack of accurate data traffic profiles, to the use of power transfer, energy cooperation and energy trading techniques. These challenges are here discussed along with some research directions to follow for achieving sustainable 5G systems.Comment: Accepted by Elsevier Computer Communications, 21 pages, 9 figure

Scaling up virtual MIMO systems

Multiple-input multiple-output (MIMO) systems are a mature technology that has been incorporated into current wireless broadband standards to improve the channel capacity and link reliability. Nevertheless, due to the continuous increasing demand for wireless data traffic new strategies are to be adopted. Very large MIMO antenna arrays represents a paradigm shift in terms of theory and implementation, where the use of tens or hundreds of antennas provides significant improvements in throughput and radiated energy efficiency compared to single antennas setups. Since design constraints limit the number of usable antennas, virtual systems can be seen as a promising technique due to their ability to mimic and exploit the gains of multi-antenna systems by means of wireless cooperation. Considering these arguments, in this work, energy efficient coding and network design for large virtual MIMO systems are presented. Firstly, a cooperative virtual MIMO (V-MIMO) system that uses a large multi-antenna transmitter and implements compress-and-forward (CF) relay cooperation is investigated. Since constructing a reliable codebook is the most computationally complex task performed by the relay nodes in CF cooperation, reduced complexity quantisation techniques are introduced. The analysis is focused on the block error probability (BLER) and the computational complexity for the uniform scalar quantiser (U-SQ) and the Lloyd-Max algorithm (LM-SQ). Numerical results show that the LM-SQ is simpler to design and can achieve a BLER performance comparable to the optimal vector quantiser. Furthermore, due to its low complexity, U-SQ could be consider particularly suitable for very large wireless systems. Even though very large MIMO systems enhance the spectral efficiency of wireless networks, this comes at the expense of linearly increasing the power consumption due to the use of multiple radio frequency chains to support the antennas. Thus, the energy efficiency and throughput of the cooperative V-MIMO system are analysed and the impact of the imperfect channel state information (CSI) on the system’s performance is studied. Finally, a power allocation algorithm is implemented to reduce the total power consumption. Simulation results show that wireless cooperation between users is more energy efficient than using a high modulation order transmission and that the larger the number of transmit antennas the lower the impact of the imperfect CSI on the system’s performance. Finally, the application of cooperative systems is extended to wireless self-backhauling heterogeneous networks, where the decode-and-forward (DF) protocol is employed to provide a cost-effective and reliable backhaul. The associated trade-offs for a heterogeneous network with inhomogeneous user distributions are investigated through the use of sleeping strategies. Three different policies for switching-off base stations are considered: random, load-based and greedy algorithms. The probability of coverage for the random and load-based sleeping policies is derived. Moreover, an energy efficient base station deployment and operation approach is presented. Numerical results show that the average number of base stations required to support the traffic load at peak-time can be reduced by using the greedy algorithm for base station deployment and that highly clustered networks exhibit a smaller average serving distance and thus, a better probability of coverage

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Energy Management in LTE Networks

Wireless cellular networks have seen dramatic growth in number of mobile users. As a result, data requirements, and hence the base-station power consumption has increased significantly. It in turn adds to the operational expenditures and also causes global warming. The base station power consumption in long-term evolution (LTE) has, therefore, become a major challenge for vendors to stay green and profitable in competitive cellular industry. It necessitates novel methods to devise energy efficient communication in LTE. Importance of the topic has attracted huge research interests worldwide. Energy saving (ES) approaches proposed in the literature can be broadly classified in categories of energy efficient resource allocation, load balancing, carrier aggregation, and bandwidth expansion. Each of these methods has its own pros and cons leading to a tradeoff between ES and other performance metrics resulting into open research questions. This paper discusses various ES techniques for the LTE systems and critically analyses their usability through a comprehensive comparative study

Network resource allocation policies with energy transfer capabilities

During the last decades, mobile network operators have witnessed an exponential increase in the traffic demand, mainly due to the high request of services from a huge amount of users. The trend is of a further increase in both the traffic demand and the number of connected devices over the next years. The traffic load is expected to have an annual growth rate of 53% for the mobile network alone, and the upcoming industrial era, which will connect different types of devices to the mobile infrastructure including human and machine type communications, will definitely exacerbate such an increasing trend. The current directions anticipate that future mobile networks will be composed of ultra dense deployments of heterogeneous Base Stations (BSs), where BSs using different transmission powers coexist. Accordingly, the traditional Macro BSs layer will be complemented or replaced with multiple overlapping tiers of small BSs (SBSs), which will allow extending the system capacity. However, the massive use of Information and Communication Technology (ICT) and the dense deployment of network elements is going to increase the level of energy consumed by the telecommunication infrastructure and its carbon footprint on the environment. Current estimations indicates that 10% of the worldwide electricity generation is due to the ICT industry and this value is forecasted to reach 51% by 2030, which imply that 23% of the carbon footprint by human activity will be due to ICT. Environmental sustainability is thus a key requirement for designing next generation mobile networks. Recently, the use of Renewable Energy Sources (RESs) for supplying network elements has attracted the attention of the research community, where the interest is driven by the increased efficiency and the reduced costs of energy harvesters and storage devices, specially when installed to supply SBSs. Such a solution has been demonstrated to be environmentally and economically sustainable in both rural and urban areas. However, RESs will entail a higher management complexity. In fact, environmental energy is inherently erratic and intermittent, which may cause a fluctuating energy inflow and produce service outage. A proper control of how the energy is drained and balanced across network elements is therefore necessary for a self-sustainable network design. In this dissertation, we focus on energy harvested through solar panels that is deemed the most appropriate due to the good efficiency of commercial photovoltaic panels as well as the wide availability of the solar source for typical installations. The characteristics of this energy source are analyzed in the first technical part of the dissertation, by considering an approach based on the extraction of features from collected data of solar energy radiation. In the second technical part of the thesis we introduce our proposed scenario. A federation of BSs together with the distributed harvesters and storage devices at the SBS sites form a micro-grid, whose operations are managed by an energy management system in charge of controlling the intermittent and erratic energy budget from the RESs. We consider load control (i.e., enabling sleep mode in the SBSs) as a method to properly manage energy inflow and spending, based on the traffic demand. Moreover, in the third technical part, we introduce the possibility of improving the network energy efficiency by sharing the exceeding energy that may be available at some BS sites within the micro-grid. Finally, a centralized controller based on supervised and reinforcement learning is proposed in the last technical part of the dissertation. The controller is in charge of opportunistically operating the network to achieve efficient utilization of the harvested energy and prevent SBSs blackout.Durante las últimas décadas, los operadores de redes móviles han sido testigos de un aumento exponencial en la demanda de tráfico, principalmente debido a la gran solicitud de servicios de una gran cantidad de usuarios. La tendencia es un aumento adicional tanto en la demanda de tráfico como en la cantidad de dispositivos conectados en los próximos años. Se espera que la carga de tráfico tenga una tasa de crecimiento anual del 53% solo para la red móvil, y la próxima era industrial, que conectará diferentes tipos de dispositivos a la infraestructura móvil, definitivamente exacerbará tal aumento. Las instrucciones actuales anticipan que las redes móviles futuras estarán compuestas por despliegues ultra densos de estaciones base (BS) heterogéneas. En consecuencia, la capa tradicional de Macro BS se complementará o reemplazará con múltiples niveles superpuestos de pequeños BS (SBS), lo que permitirá ampliar la capacidad del sistema. Sin embargo, el uso masivo de la Tecnología de la Información y la Comunicación (TIC) y el despliegue denso de los elementos de la red aumentará el nivel de energía consumida por la infraestructura de telecomunicaciones y su huella de carbono en el medio ambiente. Las estimaciones actuales indican que el 10% de la generación mundial de electricidad se debe a la industria de las TIC y se prevé que este valor alcance el 51% para 2030, lo que implica que el 23% de la huella de carbono por actividad humana se deberá a las TIC. La sostenibilidad ambiental es, por lo tanto, un requisito clave para diseñar redes móviles de próxima generación. Recientemente, el uso de fuentes de energía renovables (RES) para suministrar elementos de red ha atraído la atención de la comunidad investigadora, donde el interés se ve impulsado por el aumento de la eficiencia y la reducción de los costos de los recolectores y dispositivos de almacenamiento de energía, especialmente cuando se instalan para suministrar SBS. Se ha demostrado que dicha solución es ambiental y económicamente sostenible tanto en áreas rurales como urbanas. Sin embargo, las RES conllevarán una mayor complejidad de gestión. De hecho, la energía ambiental es inherentemente errática e intermitente, lo que puede causar una entrada de energía fluctuante y producir una interrupción del servicio. Por lo tanto, es necesario un control adecuado de cómo se drena y equilibra la energía entre los elementos de la red para un diseño de red autosostenible. En esta disertación, nos enfocamos en la energía cosechada a través de paneles solares que se considera la más apropiada debido a la buena eficiencia de los paneles fotovoltaicos comerciales, así como a la amplia disponibilidad de la fuente solar para instalaciones típicas. Las características de esta fuente de energía se analizan en la primera parte técnica de la disertación, al considerar un enfoque basado en la extracción de características de los datos recopilados de radiación de energía solar. En la segunda parte técnica de la tesis presentamos nuestro escenario propuesto. Una federación de BS junto con los cosechadores distribuidos y los dispositivos de almacenamiento forman una microrred, cuyas operaciones son administradas por un sistema de administración de energía a cargo de controlar el presupuesto de energía intermitente y errático de las RES. Consideramos el control de carga como un método para administrar adecuadamente la entrada y el gasto de energía, en función de la demanda de tráfico. Además, en la tercera parte técnica, presentamos la posibilidad de mejorar la eficiencia energética de la red al compartir la energía excedente que puede estar disponible en algunos sitios dentro de la microrred. Finalmente, se propone un controlador centralizado basado en aprendizaje supervisado y de refuerzo en la última parte técnica de la disertación. El controlador está a cargo de operar la red para lograr una utilización eficiente de energía y previene el apagón de SB

Impact of Random Deployment on Operation and Data Quality of Sensor Networks

Several applications have been proposed for wireless sensor networks, including habitat monitoring, structural health monitoring, pipeline monitoring, and precision agriculture. Among the desirable features of wireless sensor networks, one is the ease of deployment. Since the nodes are capable of self-organization, they can be placed easily in areas that are otherwise inaccessible to or impractical for other types of sensing systems. In fact, some have proposed the deployment of wireless sensor networks by dropping nodes from a plane, delivering them in an artillery shell, or launching them via a catapult from onboard a ship. There are also reports of actual aerial deployments, for example the one carried out using an unmanned aerial vehicle (UAV) at a Marine Corps combat centre in California -- the nodes were able to establish a time-synchronized, multi-hop communication network for tracking vehicles that passed along a dirt road. While this has a practical relevance for some civil applications (such as rescue operations), a more realistic deployment involves the careful planning and placement of sensors. Even then, nodes may not be placed optimally to ensure that the network is fully connected and high-quality data pertaining to the phenomena being monitored can be extracted from the network. This work aims to address the problem of random deployment through two complementary approaches: The first approach aims to address the problem of random deployment from a communication perspective. It begins by establishing a comprehensive mathematical model to quantify the energy cost of various concerns of a fully operational wireless sensor network. Based on the analytic model, an energy-efficient topology control protocol is developed. The protocol sets eligibility metric to establish and maintain a multi-hop communication path and to ensure that all nodes exhaust their energy in a uniform manner. The second approach focuses on addressing the problem of imperfect sensing from a signal processing perspective. It investigates the impact of deployment errors (calibration, placement, and orientation errors) on the quality of the sensed data and attempts to identify robust and error-agnostic features. If random placement is unavoidable and dense deployment cannot be supported, robust and error-agnostic features enable one to recognize interesting events from erroneous or imperfect data