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

Emerging Edge Computing Technologies for Distributed Internet of Things (IoT) Systems

The ever-increasing growth in the number of connected smart devices and various Internet of Things (IoT) verticals is leading to a crucial challenge of handling massive amount of raw data generated from distributed IoT systems and providing real-time feedback to the end-users. Although existing cloud-computing paradigm has an enormous amount of virtual computing power and storage capacity, it is not suitable for latency-sensitive applications and distributed systems due to the involved latency and its centralized mode of operation. To this end, edge/fog computing has recently emerged as the next generation of computing systems for extending cloud-computing functions to the edges of the network. Despite several benefits of edge computing such as geo-distribution, mobility support and location awareness, various communication and computing related challenges need to be addressed in realizing edge computing technologies for future IoT systems. In this regard, this paper provides a holistic view on the current issues and effective solutions by classifying the emerging technologies in regard to the joint coordination of radio and computing resources, system optimization and intelligent resource management. Furthermore, an optimization framework for edge-IoT systems is proposed to enhance various performance metrics such as throughput, delay, resource utilization and energy consumption. Finally, a Machine Learning (ML) based case study is presented along with some numerical results to illustrate the significance of edge computing.Comment: 16 pages, 4 figures, 2 tables, submitted to IEEE Wireless Communications Magazin

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

A Study on Cross-Carrier Scheduler for Carrier Aggregation in Beyond 5G Networks

Carrier Aggregation (CA) allows the network and User Equipment (UE) to aggregate carrier frequencies in licensed, unlicensed, or Shared Access (SA) bands of the same or different spectrum bands to boost the achieved data rates. This work aims to provide a detailed study on CA techniques for 5G New Radio (5G NR) networks while elaborating on CA deployment scenarios, CA-enabled 5G networks, and radio resource management and scheduling techniques. We analyze cross-carrier scheduling schemes in CA-enabled 5G networks for Downlink (DL) resource allocation. The requirements, challenges, and opportunities in allocating Resource Blocks (RBs) and Component Carriers (CCs) are addressed. The study and analysis of various multi-band scheduling techniques are made while maintaining that high throughput and reduced power usage must be achieved at the UE. Finally, we present CA as the critical enabler to advanced systems while discussing how it meets the demands and holds the potential to support beyond 5G networks, followed by discussing open issues in resource allocation and scheduling techniques.This work was supported by FCT/MCTES through national funds and, when applicable, cofounded EU funds under the project UIDB/50008/2020, ORCIP (22141-01/SAICT/2016), COST CA 20120 INTERACT, SNF Scientific Exchange - AISpectrum (project 205842) and TeamUp5G. TeamUp5G has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391.info:eu-repo/semantics/publishedVersio

Increased energy efficiency in LTE networks through reduced early handover

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Long Term Evolution (LTE) is enormously adopted by several mobile operators and has been introduced as a solution to fulfil ever-growing Users (UEs) data requirements in cellular networks. Enlarged data demands engage resource blocks over prolong time interval thus results into more dynamic power consumption at downlink in Basestation. Therefore, realisation of UEs requests come at the cost of increased power consumption which directly affects operator operational expenditures. Moreover, it also contributes in increased CO2 emissions thus leading towards Global Warming. According to research, Global Information and Communication Technology (ICT) systems consume approximately 1200 to 1800 Terawatts per hour of electricity annually. Importantly mobile communication industry is accountable for more than one third of this power consumption in ICT due to increased data requirements, number of UEs and coverage area. Applying these values to global warming, telecommunication is responsible for 0.3 to 0.4 percent of worldwide CO2 emissions. Moreover, user data volume is expected to increase by a factor of 10 every five years which results in 16 to 20 percent increase in associated energy consumption which directly effects our environment by enlarged global warming. This research work focuses on the importance of energy saving in LTE and initially propose bandwidth expansion based energy saving scheme which combines two resource blocks together to form single super RB, thereby resulting in reduced Physical Downlink Control Channel Overhead (PDCCH). Thus, decreased PDCCH overhead helps in reduced dynamic power consumption up to 28 percent. Subsequently, novel reduced early handover (REHO) based idea is proposed and combined with bandwidth expansion to form enhanced energy ii saving scheme. System level simulations are performed to investigate the performance of REHO scheme; it was found that reduced early handover provided around 35% improved energy saving while compared to LTE standard in 3rd Generation Partnership Project (3GPP) based scenario. Since there is a direct relationship between energy consumption, CO2 emissions and vendors operational expenditure (OPEX); due to reduced power consumption and increased energy efficiency, REHO subsequently proven to be a step towards greener communication with lesser CO2 footprint and reduced operational expenditure values. The main idea of REHO lies in the fact that it initiate handovers earlier and turn off freed resource blocks as compare to LTE standard. Therefore, the time difference (Transmission Time Intervals) between REHO based early handover and LTE standard handover is a key component for energy saving achieved, which is estimated through axiom of Euclidean geometry. Moreover, overall system efficiency is investigated through the analysis of numerous performance related parameters in REHO and LTE standard. This led to a key finding being made to guide the vendors about the choice of energy saving in relation to radio link failure and other important parameters