Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

A practical framework for energy-efficient node activation in heterogeneous LTE networks

This paper presents a framework to activate and deactivate micro nodes in a heterogeneous multi-cell LTE network, based on load and energy efficiency consideration. The framework exploits historical data (i.e., per-macro-cell load curves) to select a set of candidate switch-on/switch-off instants of micro cells, assuming a limited number of state changes is allowed in a day. The switching instants are instead determined online, by taking into account the actual traffic as well as the load curves. Moreover, intercell interference is fully accounted for. Our simulations show that this framework allows a multi-cell network to sustain peak-hour load when necessary, and to reconfigure to a minimum coverage baseline whenever feasible, thus saving power (up to 25% in our scenarios). Moreover, the framework is robust, meaning that deviations of the actual traffic with respect to the prediction offered by the load curves can easily be handled

RF Energy Harvesting Wireless Communication: RF Environment, Device Hardware and Practical Issues

Radio frequency (RF) based wireless power transfer provides an attractive solution to extend the lifetime of power-constrained wireless sensor networks. Through harvesting RF energy from surrounding environments or dedicated energy sources, low-power wireless devices can be self-sustaining and environment-friendly. These features make the RF energy harvesting wireless communication (RF-EHWC) technique attractive to a wide range of applications. The objective of this article is to investigate the latest research activities on the practical RF-EHWC design. The distribution of RF energy in the real environment, the hardware design of RF-EHWC devices and the practical issues in the implementation of RF-EHWC networks are discussed. At the end of this article, we introduce several interesting applications that exploit the RF-EHWC technology to provide smart healthcare services for animals, wirelessly charge the wearable devices, and implement 5G-assisted RF-EHWC

Grand challenges in IoT and sensor networks

No abstract available

Fine-grained performance analysis of massive MTC networks with scheduling and data aggregation

Abstract. The Internet of Things (IoT) represents a substantial shift within wireless communication and constitutes a relevant topic of social, economic, and overall technical impact. It refers to resource-constrained devices communicating without or with low human intervention. However, communication among machines imposes several challenges compared to traditional human type communication (HTC). Moreover, as the number of devices increases exponentially, different network management techniques and technologies are needed. Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators not only collect data but also implement scheduling mechanisms to cope with scarce network resources. This thesis provides an overview of the most common IoT applications and the network technologies to support them. We describe the most important challenges in machine type communication (MTC). We use a stochastic geometry (SG) tool known as the meta distribution (MD) of the signal-to-interference ratio (SIR), which is the distribution of the conditional SIR distribution given the wireless nodes’ locations, to provide a fine-grained description of the per-link reliability. Specifically, we analyze the performance of two scheduling methods for data aggregation of MTC: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). The results show the fraction of users in the network that achieves a target reliability, which is an important aspect to consider when designing wireless systems with stringent service requirements. Finally, the impact on the fraction of MTDs that communicate with a target reliability when increasing the aggregators density is investigated

Ultra-Dense Mobile Networks: Optimal Design and Communications Strategies

This thesis conducts an extensive analysis within the mobile telecommunications sub-field of the ultra-dense mobile networks, in which a massive deployment of network’s pieces of equipment is assumed. Future cache-enabled mobile networks are expected to meet most of the generated content demands directly at the edge, where each node has the availability to proactively store a set of contents in a local memory. This thesis makes several important contributions. The research being presented in this thesis proposes new analytical expressions to modeling the performance associated to the network’s edge. Base-stations’ idling technologies are also investigated to temporarily turn off some network nodes, saving energy and, in some circumstances, improving the overall performance by contributing less interference at the network’s edge. On the other hand, making use of fewer base-stations however reduces the amount of available resources at the network’s edge. A trade-off is investigated, which balances among interference saturation and available resources to increase the average user’s quality of experience. In this work, we treat the edge node density as a variable of the problem. This greatly increases the difficulty of obtaining analytical expressions, but also offers a direct access for optimizing the users’ average performance and network’s energy consumptions. An energy-focused performance metric is subsequently proposed, with the intention to highlight an interesting duality within the same network’s tier, which can transition from a better efficient to a more performing state, according to the energy expenses from the operators. Nonetheless, under an ultra-dense scenario, line-of-sight wireless links between the user and the nodes become more likely. The introduction of a main component of the multi-path propagated copies of a signal involves analytical complications. A feasible approximation is proposed and validated through a set of computer simulations. The scalability of the proposed technique allows to generalise existing results in the literature