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REPORT
ON
GREEN NETWORKS
Submitted to:                                Submitter by:
Abstract
Energy harvesting (EH) is well under way in the realm of autonomous wireless networked systems to become a transforming technology. The potential to operate long term, steadily and intelligently in a variety of applications has attracted both academic and industry's interest. However, the road to the ultimate network is full of potholes: the ambient energy is intermittent, limited energy storage capacity and the size and complexity of devices. The energy consumption of the entire system must be captured in order to quantify the wireless network's energy efficiency. Due to its ability to satisfy the exponential rise of mobile data traffic and the growing need for enhanced service quality and user experience on mobile applications, small cell networks have received much attention in the last few of years. However, due to the complexity of network planning and optimization as well as the high costs associated for construction and operation, a large deployment of small cell networks has not yet occu
ed. Particularly all small cell base stations are challenging to deliver grid power in an economical method. In order to satisfy the capacity and coverage for next-generation Wireless networks, dense deployment of small cell base stations will enhance the electricity costs and result in substantial ca
on emissions. In addition, smaller cell traffic has been seen as a possible option to meet enormous traffic increase in future heterogeneous cellular networks (HCNs). However, the dense deployment of tiny cells has led to increased concerns about the excessive consumption of ca
on-based grid energy in HCNs. It is therefore necessary to harness grid and green energy sources in tiny cell grids, which are a viable option for energy harvesting technology. This research will address these concerns by discussing recent
eakthroughs in energy management technologies, doing a thorough research of energy collection of small cell networks and examining essential areas, such as feasibility analysis, networking and network operating concerns.
Introduction
The growth of mobile devices, such as smartphones and tablets, boosts the explosion of data traffic in the wireless environment. Cellular networks confront hurdles in this respect, namely, the provision of huge network capacity, better cell coverage and better user experience. The use of heterogeneous little cells that are substantially subordinate to macrocells enables traffic to discharge via small cells to ease traffic congestion in macrocells in a cost-effective way.[5] Through the proximity of mobile users to radio connectivity systems the discharge of traffic through small cells can benefit by raising the performance and improving the coverage and thus play a crucial role in the support of various applications in future cellular networks [6].
Although the enormous volume of traffic and linked devices give new chances to improve wireless networks, this expansion is crucial for energy (EC) and greenhouse gas emissions. A cost-effective and energy-efficient network paradigm for tackling these difficulties is the small cell network (SCN). The space reuse of radio resources at a new level, which will then increase the spectrum efficiency and user experience of the area, is
ought to bear by SCN's densely-used smaller cell base stations (SCBSs). Because of the traffic offload advantages, the latest specification for the Third-Generation Partnership Project (3GPP) proposes a paradigm that allows a mobile user to communicate with a macrocell (known as the master cell) and simultaneously offload data through a small cell (called as the slave cell) via a smaller cell phone by means of two different radio interfaces.[7] DC offers flexible and dynamic routing of traffic between the small and macro cells, which enhances user service quality (QoS) and resource efficiency. The extensive installations of small heterogenous cells (e.g., femtocells, picocells and Wi-Fi hotspots) have, however, prompted growing concern about excessively high energy usage, particularly for the enormous use of grid-based ca
on. The key concern then is how to efficiently reduce grid power use for the offloading of traffic into heterogeneous communication networks (HCNs) and also provide mobile users with sufficient QoS. Various research endeavors to explore the effective downloading of and the caching of data in small cells were undertaken. Recent technological advances, including energy harvesting (EH), local energy share (ES) [9,10] and wireless power transfer (WPT) [11,12] have been contributing on on-grid power supplies, enabling hy
id energy supply to support small cell phones and mobile users that delivers sustainable and green traffic offloading. EH-capability communication networks were extensively researched in recent years but no systematic study has been ca
ied out so far as how EH techniques may be efficiently used in SCNs. In this research we undertake an in-depth investigation on small cellular energy harvesting and explore crucial elements, including an examination of viability, network deployment, and concerns of network operation.
Traffic Overloading Architecture
The traffic offloading architecture that leverages state-of-the art energy technologies (i.e., EH, ES and WPT) provides the intelligent energy management (SEM) module to connect energy management with traffic discharge.
One of H-key CRAN's tasks since its inception is the construction of wireless communication networks that are environmentally sustainable and cost-effective. With a worldwide coordination capacity of H-CRANs, several interesting strategies may be employed for energy-efficient transmissions in such scenarios, such as joint processing/allotment, transport load offloading, energy balance, self-organization and adaptive network deployment. Unfortunately, the EE network usually increases at the cost of other metrics, such as SE, fairness and delay, which are all just as vital as EE, however, to ensure the quality of service offered to consumers (QoS). In other words, trade-offs include EE-SE, EE-fairness and EE-delays. Therefore, it is important to examine these performance gaps in H-CRANs to lay down guidelines to balance network EE and the user's requirements of QoS flexibly. The green developments of HCRANs and notably with the view of EE-S, EE-fairness and EE-delay trading instead of the indexes themselves compared to prior studies on system architecture or radio resource management (RRM), particularly with regard to EE & SE. We will organize the rest of this report as follows to achieve our objectives. In the next section, the architecture of the H-CRANs is first simply reviewed and their features used to offer three possible green H-CRANs strategies.
The traffic offloading design through tiny cells integrating EH and ES capabilities. In particular, each small macrocell has a hy
id power supply including: grid power supply from external utilities, EH power supplies from EH and ES power supply through local energy...