ReviewResource management in cellular base stations powered by renewable energy sources
Introduction
Over the past decade concepts such as renewable energy, energy conservation, and energy efficiency have found their way into all technology sectors including the information and communication technology (ICT) sector. The reason for this is twofold; firstly, the rising operating cost of power consumption for the energy intensive systems is being felt all over as technology encompasses every facet of our lives. Secondly, the ICT industry, being the fastest growing sector, realizes its obligation in reducing harmful emissions attributed towards it. Amongst all sub-sectors of ICT, the telecomm sector in general and cellular communication in particular have shown huge potential for improvements in energy efficiency and converting systems on clean (renewable) sources of energy. As a result future communication is not only focused on spectrum management and throughput or quality of service (QoS) anymore. Rather, a new paradigm has come in, i.e., energy efficiency with reduced carbon footprint, called green communication (Al Haj Hassan et al., 2013). Green communication has become a realistic goal for which new ways and means are being explored by the industry (Hassan et al., 2013; Suarez et al., 2012; Feng et al., 2013; Hasan et al., 2011; Mahapatra et al., 2015).
Cellular communication is the fastest growing component of telecom sector in particular and ICT in general (Iqbal et al., 2014; Bian et al., 2013). It is envisaged that the global BS power consumption will grow from 49 TWh in 2007 to 98 TWh by 2020 (Fehske et al., 2011). Improving energy efficiency in cellular networks involves energy reduction of all network elements, such as mobile core network, mobile switching centers, BSs, mobile back haul networks, and mobile terminals (Wu, 2012; Etoh et al., 2008; Ahmed et al., 2016, 2017; Wang et al., 2016; Chamola and Sikdar, 2016a, 2016b; Farooq et al., 2017; Li et al., 2016; Naeem et al., 2014). Amongst the mentioned elements, the BS is the most energy hungry component, consuming approximately 60% of the total energy consumed by cellular network (Chen et al., 2011a), as depicted in Fig. 1. For the BS of a 3G and LTE network this ratio increases to 75–80% (Hassan et al., 2013). Thus, BSs have become the prime focus of research for energy efficiency in cellular communication; especially for installation of RES such as PV arrays and wind turbines.
Green wireless communication can be described as a set of concepts and frameworks put together to improve the energy efficiency of wireless systems. The use of RESs is gaining widespread coverage in all sectors due to the improvements in the photo-voltaic (PV) cells and wind-turbine (WT) related technologies, deep cycle rechargeable batteries, power converters etc. as well as simulation and maintenance softwares (Nema et al., 2009). The hybrid systems comprising conventional and RESs have been shown to significantly decrease the overall cost of the isolated power systems over their total life cycle (Karki and Billinton, 2001). In cellular applications, the main attraction is to power remotely located BSs that are off the grid, thereby saving substantial cost of running the diesel generator and fuel transportation cost. The use of sustainable renewable (green) energy can also help in cutting down the harmful emissions. In fact, research shows that green BSs are equally beneficial in energy cost savings and maximization of energy efficiency in networks that are connected to the grid or off the grid (Wang et al., 2013). Renewable energy provides an opportunity to bridge the energy gap for powering systems such as cellular BSs, for both developing and under developed countries (Kusakana and Vermaak, 2013; Coppez et al., 2011), as well as cut down on harmful GHG emissions.
A list consisting of description of acronyms used in this paper is presented in Table 1.
The topic of energy efficiency in cellular networks is very vast given the large number of perspectives available for research. Not only academia but industry as well as government and non-government organizations are exploring the realm of energy efficiency in wireless communications (Bianzino et al., 2012). In green cellular networks, the main objective is to maximize the use of renewable energy, for which research has focused on energy consumption strategies, resource management strategies and performance analysis of demonstration systems (Humar et al., 2011). In modeling a cellular network supported by RES, the objective is to determine the most advantageous network characteristics such as density of BSs, topology of BSs/RESs, sleep algorithms, BS interconnection, multi-cell cooperation etc. Powering the BSs with RES systems of manageable size is a challenging task especially when it aims to minimize the overall network energy cost without compromising the user QoS (Marsan et al., 2013). The research on energy efficiency in cellular communication has been carried out from different perspectives, which can be broadly categorized into five categories:
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Energy efficiency metrics and consumption models: Green spectrum management for mobile operators (Holland et al., 2010), is an area that deals with the quantification of energy consumption and formulation of energy models similar to real time scenarios. The quantification of energy is not only done at system level but also over life span of technology to come up with accurate metrics for energy measurement (Chen et al., 2010a).
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Energy efficient hardware and technologies: Another area of interest is the hardware that can be made more energy efficient by improving design and technology, e.g., the power amplifier (PA) is a big candidate for improvement in energy efficiency. It also includes software improvements such as cross-layer and energy storage optimization.
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Energy efficient architectures: Energy efficiency in wireless networks can also be achieved through different network architectures, such as cost effective deployment strategies of heterogeneous networks (HetNets) (Johansson, 2007), multi-cell cooperation, cell zooming or using low-power micro base stations compared to today's high-power macro BS schemes etc. (Tombaz et al., 2011; Fehske et al., 2009). Power consumption can be reduced using multi-hop transmission in cellular networks (Song et al., 2004) or self-organized energy efficient cellular networks (Samdanis et al., 2010).
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Energy efficient resource management: Management of both radio and energy resources is vast topic of research from the point of energy efficiency (Budzisz et al., 2014). Radio resource management involves efficient spectrum management and user traffic management. For example, authors in (Ghazzai et al., 2013) have demonstrated that it is possible to save energy by optimizing the sleep cycle of a BS. Sum-rate maximization and cost minimization are similar objectives (Wang et al., 2013). Energy resource management involve schemes such as energy cooperation and optimization of different energy sources (Oh et al., 2013). Multi-radio access network technologies (Multi-RAT) management and novel paradigms for delay tolerant services are also some resource management techniques. Authors in (Xiong et al., 2011) present a trade-off between energy and spectral efficiency in downlink orthogonal frequency-division multiple access (OFDMA) networks.
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Incorporation of renewable energy sources (RESs): An upcoming paradigm for energy efficiency is the incorporation of RESs such as solar and wind, particularly on the BSs. In (Han and Ansari, 2013a), authors have proposed a scheme to optimize the utilization of green (solar) energy during the peak traffic hours, i.e., day time, when solar energy is available.
This reveals that there are many ways of achieving energy efficiency in a BS including improving efficiency of the hardware, improving the network protocols, improving the system architecture and network deployment tailored to traffic requirements, and using low-power micro BSs compared to today's high-power macro BS schemes (Tombaz et al., 2011). However, this paper deals with work mainly related to renewable energy based designs and strategies because of the increased interest of research community in energy efficiency and reduction in emissions. Theoretical modeling as well as software simulations carried out by the researchers in verifying the trade-offs between energy efficiency of RES enabled BSs and other performance parameters (Chen et al., 2011b).
An overview of green mobile network is presented in (Han and Ansari, 2014), where incorporation of renewable energy at the BS site or at the grid end, and its implication has been discussed, with a brief description of the energy efficiency schemes employed in such scenarios. A survey on green mobile networking from the perspectives of network operators and mobile users is presented in (Ismail et al.,), with discussion on power consumption models and energy efficiency techniques including the use of renewable energy. The survey of methods of achieving reduction in energy consumption at cellular BS by using renewable energy sources has been discussed quite elaborately in (Hasan et al., 2011). From futuristic point of view, they have described cognitive radio networks and cooperative techniques for achieving energy efficiency in cellular networks. Authors also described the metrics used to measure energy efficiency in wireless networks. However, the configuration and other dynamics of an RES enabled BS have not been described. Serrano et al. (2012), work has reviewed different wireless technologies (such as WLAN, WMAN and PAN, etc.) to highlight main reasons of energy inefficiency and the research done to overcome these so far. Their specific contribution is in terms of the quantitative analysis of the savings made in the proposed solutions. Green cellular networks are not the area of research in their work. Authors in (Li et al., 2011b), have discussed energy efficient transmission techniques, mainly focusing on relaying techniques, multi hop techniques and multiple input multiple output (MIMO) techniques. Also, cooperative transmission techniques and energy efficient signaling information has been discussed from future research point of view. Use of renewable energy for energy conservation is not the prime focus area. Researchers in (Feng et al., 2013), while reviewing energy efficiency in cellular networks have mainly investigated radio resource management strategies that reduces energy consumption of networks. The relationship between energy efficiency metrics and their trade offs is also discussed. Particularly, authors have analyzed the role of HetNets deployments and cooperative communication mechanisms in improving the energy efficiency of networks. However, the role of grid in energy efficiency of BSs as explored by researchers, has not been covered in this work. The survey in (Al Haj Hassan et al., 2013) explores the RES enabled BS similar to what we have done. It starts by characterizing salient features of a RES enabled BS such as type of BS, energy storage, and power control unit. Then it discusses different techniques in cellular architecture such as HetNets. Finally the authors describe some algorithms dedicated for energy management in RES enabled BS. However, the paper lacks the depth in exploring all three said areas and the role of smart grid (a promising technology) is not discussed in connection with green BSs. In (Hassan et al., 2013), authors have briefly described the objectives and constraints of hybrid energy based cellular systems and then presented a case study in which they propose an energy management algorithm to reduce the electricity consumption cost by employing PV array as a RES. Simulation results verify the advantage of RES in cutting down electricity consumption cost, as demonstrated by other research work presented in this paper. Another note worthy survey on energy efficiency in green cellular networks has been carried out in (De Domenico et al., 2014). Once again the green paradigm has been used to describe all energy efficient techniques, however, renewable energy assisted cellular BSs is not the main focus of this paper. The paper discusses energy consumption and cost models for macro/micro BSs, back haul and RAN controller followed by the classification of various energy efficiency metrics and trade offs w.r.t coverage, spectral efficiency, and end user performance. Finally the paper classifies energy efficiency schemes on the basis of their operations in time scale, i.e., short, medium and long time frame mechanism. (Suarez et al., 2012).
Most of the existing surveys cover energy efficiency in wireless systems in general and not specifically in cellular communication networks. Others that do focus on cellular networks use the green paradigm to describe all types of energy efficiency mechanisms including renewable energy incorporation. Thus their treatment of the topic is broad and not focused on renewable energy alone. Few that do focus on renewable energy enabled cellular BSs and networks have not covered all aspects in depth as we have, as depicted in Table 2. Moreover, our survey is optimization oriented and almost all aspects of optimization of energy efficiency in green BS have been discussed. Most importantly, the dynamics of an RES enabled BS, including sizing and configuration, and the upcoming energy management strategies have been discussed with their problem formulations to give a deeper insight to the reader.
The research into renewable energy enabled BSs has been categorized into two distinct areas as depicted in Fig. 2, i.e., Green Base Stations and Green Cellular Networks. Fig. 2 also shows the classification of these BSs as per power grid connectivity. A BS in urban and populated areas is mostly connected to the grid, i.e., on-grid, whereas, those deployed in remote or inhabitable areas are off the grid. The distinct research areas pertaining to single BS includes optimization of RES system configuration, energy storage, energy sources, and radio resource optimization. Optimal utilization of battery/storage-device is particularly required in a stand alone BS. The second category of research work relates to the green cellular networks that have RES-enabled BSs. In the case of cellular configuration the dynamics are different as the BSs can manipulate the cellular energy consumption in conjunction to each other through strategies such as multi-cell cooperation, sleep mechanism, energy cooperation, etc. In this case, introduction of smart grid provides some viable energy management options such as energy cooperation. In most research articles, theoretical modeling of relevant parameters of a BS is often carried out prior to subjecting them to different optimization techniques. These models can be categorized as following:
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Configuration model describes the capacity and size of the PV array panels and the wind turbines. The configuration of the renewable systems depends on the availability of other resources like utility and DG, but mostly the wind and solar irradiation of the site. Thus BSs have mostly been configured for either PV panels or wind turbines or hybrid of the two (Paudel et al., 2011).
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Energy storage model is defined in terms of battery parameters such as capacity (AH), battery charging losses, charging rate, the system load, etc. In addition, RESs often taken as a stationary stochastic process, where the objective is to maximize green energy utilization at each stage, while meeting the network's QoS requirements.
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Energy consumption model is comprised of two components, i.e., (1) a static component related to equipment having constant power consumption and (2) a dynamic component related to energy consumption in power amplifier, attributed to traffic load. Estimation of present energy consumption and future energy arrival as well as balancing various energy sources (solar, wind, grid etc) is fundamental optimization problem in energy consumption models.
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Traffic/channel model describes user traffic as a function of data arrival rate of the user(s) at the BS and the data service rate provided by the BS. Channel model is described by channel's signal to interference and noise ratio (SINR) and is defined as a function of transmission power, channel gain, and channel's noise.
The rest of the paper is organized as follows. Section 2 gives an overview of the RES enabled network and BS in terms of its energy dynamics, renewable energy systems modeling and optimization. Section 3 discusses energy optimization strategies for a green (RES enabled) BS, while Section 4 discusses energy conservation schemes for green cellular networks, with a summary at the end of both parts. Conclusions and future research directions are drawn in Section 5.
Section snippets
An overview of green cellular network/BS
The emerging paradigm of RES enabled cellular networks in smart grid involves different technologies that makes green communication possible. The advances being made in technologies related to renewable energy systems, LTE-A (5G) networks and smart grids make it possible to design and implement green communication networks as demonstrated by research conducted in green LTE networks (Hassan et al., 2013; Marsan et al., 2013; Ghazzai et al., 2013; Ghazzai et al.,; Elshabrawy and Mourad, 2014; Ng
Resource management in green cellular base station
In this section, we explore the research carried out in an RES enabled BS from different perspectives. Incorporation of RESs into a cellular BS is viable not only from climate change point of view but also from energy efficiency perspective (Grangeat et al., 2010). In developing countries, rural population is often outside grid connectivity. In such scenarios, wind and solar energy can effectively supplement the DG and can be a useful alternative to fuel based power. Optimization of an RES
Resource management in green cellular networks
Green cellular networks are networks that aim to conserve energy, be energy efficient and reduce emissions. With encouraging results for a BS powered by RES, research extended to green cellular network. The advantages reaped for a green BS in terms of energy efficiency and energy cost minimization can yield even better prospects for green networks (Carreno and Nuaymi, 2013). As with a single BS, the challenge here is also to overcome the unsustainable nature of RES while meeting the
Conclusion and future work
The futuristic wireless technologies of 5G are going to bring dramatic performance improvements in terms of data rates, network capacity, latency, cost and coverage (Soldani and Manzalini, 2015). In order to achieve these desired goals, technological improvements are underway at all tiers as well as the search for new innovative solutions. Densification and diversification of the radio access network will requite new models to make them economical and energy efficient such as dynamic and
Faran Ahmed is currently an Associate Professor at College of Aeronautical Engineering (CAE). He completed his undergraduate studies in Avionics Engineering from CAE, NED University, Karachi in 1989. He holds Master's degree in Electronics Communications, from NWFP Univ of Engg Tech, Peshawar, Pakistan. He is currently working towards his PhD from COMSATS Institute of Information Technology, Wah Campus, Pakistan. His current research interest includes Wireless Communication with Renewable
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Faran Ahmed is currently an Associate Professor at College of Aeronautical Engineering (CAE). He completed his undergraduate studies in Avionics Engineering from CAE, NED University, Karachi in 1989. He holds Master's degree in Electronics Communications, from NWFP Univ of Engg Tech, Peshawar, Pakistan. He is currently working towards his PhD from COMSATS Institute of Information Technology, Wah Campus, Pakistan. His current research interest includes Wireless Communication with Renewable Energy commonly known as Green Communication.
Muhammad Naeem received the BS (2000) and MS (2005) degrees in Electrical Engineering from the University of Engineering and Technology, Taxila, Pakistan. He received his PhD degree (2011) from Simon Fraser University, BC, Canada. From 2012 to 2013, he was a Postdoctoral Research Associate with WINCORE Lab. at Ryerson University, Toronto, ON, Canada. Since August 2013, he has been an assistant professor with the Department of Electrical Engineering, COMSATS Institute of IT, Wah Campus, Pakistan and Research Associate with WINCORE Lab. at Ryerson University. From 2000 to 2005, he was a senior design engineer at Comcept (pvt) Ltd. At the design department of Comcept (pvt) Ltd, Dr. Naeem participated in the design and development of smart card based GSM and CDMA pay phones. Dr. Naeem is also a Microsoft Certified Solution Developer (MCSD). His research interests include optimization of wireless communication systems, non-convex optimization, resource allocation in cognitive radio networks and approximation algorithms for mixed integer programming in communication systems. Dr. Naeem has been the recipient of NSERC CGS scholarship.
Waleed Ejaz (S′12–M′14–SM′16) received the Ph.D. degree in information and communication engineering from Sejong University, South Korea. He is currently a Senior Research Fellow with the Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada. His current research interests include Internet of Things, energy harvesting, 5G cellular networks, and mobile cloud computing.
Muhammad Iqbal was born on October 15, 1976 in Multan. He got B.Sc. Electrical Engineering degree in 1999 from University of Engineering and Technology, Lahore. After completing B.Sc. Electrical Engineering, he served in the state owned telecommunication company for more than seven years. In 2007 he completed his MS Telecommunication Engineering from the University of Engineering and Technology, Peshawar. After completing PhD by July, 2011 from Beijing University of Posts and Telecommunications, P.R. China, he rejoined COMSATS and till this date working as Assistant Professor, Electrical Engineering Department, CIIT, Wah Campus. His research interests include signal and information processing, wireless communication, smart grid and applied optimization.
Alagan Anplagan received the B.A.Sc. M.A.Sc. and Ph.D. degrees in Electrical Engineering from the University of Toronto, Canada. He joined the Department of Electrical and Computer Engineering at Ryerson University in 2001 and was promoted to Full Professor in 2010. Dr. Anpalagan directs a research group working on radio resource management (RRM) and radio access & networking (RAN) areas within the WINCORE Lab. His current research interests include cognitive radio resource allocation and management, wireless cross layer design and optimization, cooperative communication, M2M communication, small cell networks, and green communications technologies. Dr. Anpalagan serves as Associate Editor for the IEEE Communications Surveys & Tutorials (2012-), IEEE Communications Letters (2010–13) and Springer Wireless Personal Communications (2009-), and past Editor for EURASIP Journal of Wireless Communications and Networking (2004–2009). He also served as Guest Editor for two EURASIP SI in Radio Resource Management in 3G+ Systems (2006) and Fairness in Radio Resource Management for Wireless Networks (2008) and, MONET SI on Green Cognitive and Cooperative Communication and Networking (2012),. He co-authored of three edited books, Design and Deployment of Small Cell Networks, Cambridge University Press (2014), Routing in Opportunistic Networks, Springer (2013), Handbook on Green Information and Communication Systems, Academic Press (2012). Dr. Anpalagan served as TPC Co-Chair of: IEEE WPMC′12 Wireless Networks, IEEE PIMRC′11 Cognitive Radio and Spectrum Management, IEEE IWCMC′11 Workshop on Cooperative and Cognitive Networks, IEEE CCECE′04/08 and WirelessCom'05 Symposium on Radio Resource Management. He is a registered Professional Engineer in the province of Ontario, Canada.