Planning Solar in Energy-managed Cellular Networks

There has been a lot of interest recently on the energy efficiency and environmental impact of wireless networks. Given that the base stations are the network elements that use most of this energy, much research has dealt with ways to reduce the energy used by the base stations by turning them off during periods of low load. In addition to this, installing a solar harvesting sys- tem composed of solar panels, batteries, charge con- trollers and inverters is another way to further reduce the network environmental impact and some research has been dealing with this for individual base stations. In this paper, we show that both techniques are tightly coupled. We propose a mathematical model that captures the synergy between solar installation over a network and the dynamic operation of energy-managed base stations. We study the interactions between the two methods for networks of hundreds of base stations and show that the order in which each method is intro- duced into the system does make a difference in terms of cost and performance. We also show that installing solar is not always the best solution even when the unit cost of the solar energy is smaller than the grid cost. We conclude that planning the solar installation and energy management of the base stations have to be done jointly

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

Powering remote area base stations by renewable energy

Abstract. The number of cellular subscriptions have seen a tremendous growth in the last decade and to provide connectivity for everyone has led to growth in number of base stations (BSs). BSs installed at places where reliable grid power is not available has increased and will continue to increase in the coming years to connect everybody on the globe. Energy and cost efficiency is becoming a criterion of ever increasing importance in the information and communication technology sector. Energy and cost efficiency is especially important for remote areas where providing mobile communication services is inhibited by the economic drawback of low revenue potential. In this thesis, we discuss the role of BS power consumption in the cellular networks in order to investigate approaches to lower the overall power consumption of the cellular network. The thesis covers structure of a BS and the power consumption of its components. Previous works and research approaches proposed to reduce the power consumption of BSs and to what extent they can lower the power requirement are discussed. Reducing the BS power consumption will reduce the operating cost for the networks and ease the deployment of BSs in remote areas. Also discussed are the two key technical features of 5th generation cellular access networks (beam forming through massive multiple input multiple output antenna systems and ultra-lean system design) that are promising in terms of reducing the BS power consumption. Furthermore, we discuss viable sources of renewable energy that can be used to power BSs in the remote areas. An overview of the renewable energy resources that can be used for this purpose (solar and wind energy) and their availability in different regions is discussed. The setups for harnessing solar and wind energy to generate power are presented in this thesis. For different cases requirements of wind and solar energy systems to power the BSs are calculated. Results show that while solar energy alone is a feasible option in regions at low latitude, small solar energy systems of 4–7 kW rated output power can easily power BS during the entire year. But in regions of high latitude using solar energy alone cannot meet the BS power requirement as there are long durations of very low or negligible solar irradiation levels. Furthermore, the energy produced by small wind energy setups at different wind speeds is investigated for the purpose of powering BSs. We discuss the range of windspeed levels for which the energy produced is sufficient to power a BS. Areas with average windspeeds of 5–8 m/s are very suitable for using wind energy as a source of power for BSs. Hybrid energy systems to power BSs and also a few energy storage options to store excess power are also discussed in this thesis

Energy and throughput efficient strategies for heterogeneous future communication networks

As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users

Integration of Small-cells Powered from Renewable Energy in LTE Networks

The carbon footprint of cellular base stations is continuously increasing, due to their large power consumption that accounts for more than 50 % of all of the cellular network infrastructure, and because of the large growth rate experienced by the cellular infrastructure. To address this problem, the work in this thesis investigates the feasibility of powering cellular base stations from harvested renewable energy. In addition, this work studies network architectures where the power consumed in the LTE macro base stations (called eNB) is reduced by integrating small-cells (e.g. micro, pico, and femto cells) into the LTE network, forming what is known as heterogeneous networks. Four different cellular network architectures are implemented: eNB-Micro, Micro only, eNB-Pico, and eNB-Femto. This work studies the performance of the architectures in terms of time operating from renewable energy, and the received signal quality improvement. Simulation results show that the implemented architectures operates from harvested renewable energy up to 93.9 % of the time for the case of the eNB-Femto architecture, and the probability of receiving SINR larger than 10 dB is increased from 0.25 (in the standard homogeneous LTE network) to up to 0.65 in the implemented architectures

Post-peak ICT: graceful degradation for communication networks in an energy constrained future

In recent years, rising energy prices and increasing environmental concerns have boosted research in the so called green ICT and green networking research tracks, aimed at improving the energy efficiency of communications while still offering maximal functionality. In this article we explore a future scenario in which low power networking is no longer optional, but instead becomes a necessity due to fluctuating energy availability. The contribution of this work is twofold. First, we argue why a so called post-peak future scenario, in which we can no longer rely on fossil fuels as our main resource for electricity production, is not unlikely, and what it might entail. Second, we explore the consequences of such a scenario for ICT: How well can current and future infrastructures cope with temporary energy limitations? As an illustration, we present a case study showing the impact of reduced energy availability on a wireless access network

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