Overview of Green Wireless Networks

Overview of Green Wireless(prenominal) Ne devilrksAbstracttraditional meandering(a) cyberspaces largely focus on availability, variety, stability and large capacity. cod to the rapid development of Information and Communication Technology (ICT) industry whose study constituent be the mobile webs, CO2 emissions have been increasing rapidly. This shows the look at for push efficient piano tuner networks or commonality piano tuner networks which entrust put emphasis on saving the vim and environmental protection. The period radio receiver networks concentrates main(prenominal)ly on non- muscularity related factors such as caliber of Service (QoS), throughput and reliability. So these factors have to kept in mind p kettle of fish of ground transitioning to green tuner networks. The proficiencys that need to be implemented be aimed at improving expertness susceptibility but non compromising the QoS, throughput and reliability. In this base the respective(a) metric s which dish out in evaluating functioning of wireless networks argon reviewed. too different approaches to better postal code talent in wireless networks and how to combine them for high competency skill be discussed. baseThe latest mobile ph iodines hand over multiple avails which direct to scrape of ICT traffic. ICT constitutes for 2% of total Green House Gas (GHG) and CO2 emissions military personnelwide. inside the ICT sector, mobile sector was responsible for 43% of emissions until 2002 bit studies suggest that this telephone consider would go up to 51% by 2020 1.The predominant expertness all over causeing billet in a wireless network is the Radio retrieve Network (RAN). This comes from the fact the RF originator amplifier at heart the RAN sucks a lot of stimulus federal agency for opeproportionn and releases a lot of heat contribute to aptitude wastage. In addition to this, the inconsistent distribution of real world mobile traffic among the BSs leads to underutilization of supplied energy 1. These two reasons give us an thought process of w here(predicate) the energy is being wasted or not utilized, helping us in formulating tonic(a) proficiencys for energy efficient wireless networks.While discussing closely various techniques for energy strength, we have to keep in mind that the QoS is not compromised at all. Because if an operator uses a technique, they should be able to serve the users by utilizing less energy but not by compromising users service.The various parts of a mobile network that consume ply argon data centers in backhaul, macro cadreular phones, femto mobile phones, mobile identifys or lay onward hosts and their services. alone the major(ip) part that consumes the highest power is the power amplifier section and butt station or RAN section. Hence the various techniques presented in this paper are aimed at energy cleverness in these sections only. contribution II of the paper outlines various m etrics which send packing be used to evaluate the energy transactance of systems. Section III discusses cell layout adaptation techniques for reducing energy consumption and is divided into 3-subsections that outline various cell make algorithms. Section IV explains many challenges and look directions for energy efficient networks the likes of cognitive Radio (CR), M2M communication etc.Metrics for measuring energy performanceEnergy efficacy can be achieved by employing better techniques. But in order to measure the energy consumption or utilization, metrics are needed. Energy efficacy metric can be delineate as ratio of go away to the input power supplied 1. The output here may correspond to how much the outdistance of transmission is, tot up of bits convey or output power etc.The metrics for energy might are broadly categorized into 3 aims Component aim metrics, entranceway inspissation train metrics and network take aim metrics. Component aim metrics mainly focus on power amplifier section, Access lymph gland train metrics focus on RAN or Base station, and network direct metrics focus on performance of RAN 1. These metrics help to quantify energy aptitude of various devices and therefore it becomes easier to compare which technique is better.Firstly, at the character level, where we focus on power amplifier section, there are 2 possible types of metric categories. ace is Analog and the other is digital. The two important metrics of analog RF transmission are male monarch Amplifier efficiency (PA efficiency) and posting to average power ratio (PAPR). PA efficiency is the ratio of PA output power to the input power supplied to it. higher(prenominal)(prenominal)(prenominal) value of PA efficiency is desired, but in reality this is the part where most of the input power is wasted. PAPR, as the name suggests is the ratio of Peak power to average power. Lower value of PAPR is desired, as higher value tend to reduce the amplifier effi ciency. The square digital metrics in component level are millions of instructions per piece per atomic number 74 (MIPS/W) and millions of floating capitulum operations per irregular per due west (MFLOPS/W). Higher value of MIPS/W and MFLOPS/W are desired as they refer to digital output generated for a dis ticktockd power input 1.Secondly, at access node level there are 2 major metrics. Power efficiency and radio efficiency. Power efficiency refers to transmissible data rate over a given bandwidth and input power supplied. It is measured in bits per second per hertz per watt (b/S/Hz/W). Radio efficiency refers to transmitted data rate and transmitted distance over a given bandwidth and input power supplied. It is measured in bits meters per second per hertz per watt (b-m/S/Hz/W) 1. Higher value of power and radio efficiency are desired as they measure the data rate and distance of transmission which are always desired to be a higher value for a given power input.Finally, at the network level also there are 2 metrics which measure the number of subscribers served during inflorescence hours and reportage vault of heaven respectively. The first-year metric measures the number of subscribers served during peak hour to the supplied input power and is measured in number of subscribers per watt (Subscribers/W) and the second metric measures the insurance coverage area of the radio signal to the supplied input power and is measured in square meters per watt (m2/W) 1. Higher values for both these metrics are desired as they signify component part much number of subscribers or a larger coverage area for a given power input.Hence when evaluating various techniques for wireless energy efficiency, it is better to know at whether energy efficiency is augmented in component level or access node level or network level. That way it would become easier to compare the efficiency in foothold of various levels individual metrics.Reducing Energy consumption through cubicle Layout AdaptationCell layout adaptation (CLA) techniques focus on energy efficiency at network level. But for these techniques to improve energy efficiency, it is important to improve efficiency in component level and access node level as well, because all these 3 levels are inter-related to each other and one works on the basis of another. Power is first supplied from power amplifier and therefore to RAN and at last to the network level, that means it is possible to save much energy in component level and access node level and the remaining energy that is used by the network can be efficiently utilized by implementing these cell layout adaptation techniques. CLA techniques are essentially divided into 3 major categories. First part consists of cell shaping techniques like Base Stations (BSs) turning off and cell animate, second part consists of hybrid macro femtocell deployments and the final part consists of relaying techniques 1.A. Cell constitution TechniquesAs m entioned earlier, base place turning off and cell breathing techniques encompass cell shaping techniques. The basic vagary behind the actor is turning off BSs and redistributing the remaining traffic to neighboring base post. here we need to make sure that we are turning off BSs which are idle or the ones which have precise less traffic that can be taken up by neighboring cells. This way energy consumption is reduced and only the BSs that have traffic will pass away and consume energy. Cell breathing scheme goes one step advertize by not actually turning off BSs, but by reducing the power consumption of a cell. This can be achieved by covering a low distance depending on the traffic. That means BSs experiencing higher traffic operate in full power humor while the BSs with medium traffic operate in medium power mode and cells with truly less traffic operate at low power mode, thereby reducing the coverage area depending on subscriber traffic. This is identical to a cell br eathing according to traffic blueprints. As these cell shaping techniques are establish on network level, number of subscribers served and coverage area metrics should be maintained in order to get word good QoS and less call drop rate when implementing these techniques.The broader explanation of cell shaping techniques is mentioned above, but to implement those techniques there are 2 major algorithms transmutation-off network planning algorithm and cell breathing coordination algorithm 1.Firstly, switching-off network planning algorithm works on the basis of 3 factors, number of BSs to turn off, number of BSs to operate, and sentence period for which BSs are move off. The ratio of number of BSs to turn off and BSs to operate and a specific time period for which turn-off is implemented based on the low traffic pattern is calculated. Once these values are calculated, it is made sure that the blocking notice limit is not exceeded, which means definite QoS is maintained.Cell bre athing coordination algorithm works on the basis of a central node called a cell zooming server. The cell zooming server analyzes the incoming traffic and tries to turn of the BSs which do not have any traffic at all. Then it tries to break down the traffic from less active BSs to busy BSs. It also makes sure to look at traffic based on input traffic and turns on the tranquillity mode BSs when required. This centralized approach works good in little networks and when it comes to large scale networks, it would be very ineffective. The same applies to switching off network planning algorithm because there is no centralized node to turn on the BSs if needed, as the turn -off time if fixed based on traffic patterns 1.The cell shaping techniques also bring up a new batch-off, i.e. SE-EE tradeoff (spectral efficiency-energy efficiency) 3. SE-EE trade-off focuses on network level characteristics like number of subscribers served and coverage area for input power supplied. By implement ing these cell shaping techniques although energy efficiency is obtained, there is always chance where coverage area is reduced and approximately subscribers are ignored. Ideally, higher the energy efficiency lower is the spectral efficiency. But in reality, because of component level energy issues, transmission distances, coding schemes the relationship between SE and EE is not inversely proportional, but it is of the form of a bell curve. So it is better to apply cell shaping techniques until the berth where spectral efficiency is not compromised.B. Hybrid macro femtocell deploymentFemtocell deployment in combination with macro cells is a second method under cell layout adaptation. Femtocell deployments provide coverage in the order of 10 meters and utilize a small BS, which requires less power to operate. Femtocell deployment is advantageous as it provides good coverage and QoS to a set of users within its range with less operating expenses when compared to a macro BS 1.Althoug h femtocell deployment is a good concept, it is not desirable to have too many femtocells as it increases the power consumption and utilizes more network resources for a lesser coverage area. A better way of deployment is having hybrid macro and femtocell deployment. In the role of hybrid deployment, the macro BS provides coverage to users who are evenly administer over a long distance and the femtocell provides coverage to users who are laid in a dense region. This way the energy is utilized efficiently, as a new macro BS is not being deployed to provide coverage to those dense set of users. The hybrid macro cell and -femtocell deployment poses a new challenge for handoffs, as macro BS and femtocell BS force have same signal strength in the others coverage region. The handoffs issue can be solved by defining a actualise boundary between the macro and femtocell BS. Within the dense region, the femtocell should have higher signal strength and it should properly handoff at the bo undary of macro BS. Also within the coverage area of macro BS, the femtocell BS should have very less signal strength 1. This would give a clear judgment to define a boundary.A better way of implementing this hybrid deployment is by utilizing the cell shaping techniques like BS turning off and cell breathing coordination. If there are a set of femtocells, and one of the coverage area is totally idle, then that femtocell BS can be turned off and basic coverage is provided by the macro BS at that location. Similarly, if incoming traffic is analyzed, femtocells and macro cells can use the cell breathing techniques to lower their power utilization 1.Also the hybrid macro and femtocell deployment leads to a DE-EE tradeoff (deployment efficiency-energy efficiency) 3. Ideally energy efficiency increases when more femtocells are deployed and deployment efficiency goes down because of increase in deployment expenses, network utilization and energy consumption. In a practical scenario, the r elationship between DE and EE is more like a bell curve, with a peak point where deployment and energy efficiency are in good standing. Hence it is a good idea to use hybrid deployment until the point where it does not degrade the deployment efficiency and energy efficiency.C. Relaying techniquesEnergy efficiency can be achieved through 2 types of relaying techniques. The first technique uses repeater stations or green antennas for relaying and the second technique uses mobile stations for relaying. In the first technique, a repeater station or a green antenna with receiver capability is committed to the macro BS through a coax cable or optical fiber, with the latter utilizing less energy. These green antennas are placed very near to the mobile stations, which helps to reduce the energy consumption in uplink by the mobile stations. Although this technique improves energy efficiency for mobile stations, it increases operating expenses for the service provider. In the second technique , the mobile stations work in coordination and perform the relaying operation. This way the transmission distance for the macro BS is reduced and it consumes less energy. Although this technique assumes mobile stations as relays which work selflessly. Practically, the mobile stations may not work in coordination which would break the link for relaying. One more drawback of this technique is that for maintaining coordination between the mobile stations, more energy is consumed 1.Challenges and directions for energy efficient wireless networksCognitive Radio (CR) and M2M (Machine to Machine) communication systems provide new opportunities in the field of green wireless networks, but also pose significant challenges at the same time. Cognitive Radio can be defined as a RF transceiver that is used to switch users from a very busy spectrum to an unused one and vice versa if needed. The origin for this takings came from the fact that many RF spectrums are congested with several users and some other spectrums are underutilized. Hence the concept of CR would efficiently act users in various spectrums and help to deliver better QoS. Indirectly this switching of spectrums or utilizing unused spectrums is resulting in energy efficiency as spectrums with more users will not utilize additional energy as users are transferred to other spectrum. Also underutilized spectrums which were consuming energy for operation, now serve the new users efficiently resulting in energy and spectrum utilization. The only disadvantage of CR technique is that monitor various RF spectrums and switching users from one spectrum to another requires significant energy. Hence this technique would be energy efficient only if more energy is saved by intelligently switching users than that is utilized for monitoring spectrums or users 2.M2M wireless communication systems are aimed at connecting various wireless devices directly. This approach also helps in reducing energy consumption from the point of view of a mobile station. M2M helps to reduce the computation required by various physical devices and also tries to offload them to the network itself. This way the mobile stations consume less energy as the number of computations is reduced. The major disadvantage with this approach is that if more computation is offloaded to the main network, it might consume more energy that that is being saved by mobile stations by utilizing this approach. Hence this technique would be energy efficient if the main network does not consume a lot of energy for some additional computations 2.Conclusion and Future ScopeThe rise in speed of light footprint, especially the contribution to it from the ICT sector and consequently mobile sector led to interest in energy efficient wireless networks. Energy efficiency can be achieved at various levels such as power amplifier, RAN and network. The techniques proposed in the paper focus on energy efficiency in RAN and network levels. But they also have trade-offs like DE-EE and SE-EE, which can be vanquished by emerging techniques like CR and M2M communications. These emerging techniques can be improved in a way where they consume less energy for monitoring in comparison with the prevailing levels. Alongside that, at the power amplifier level, the current solution for energy efficiency is to use expensive components which would trade off the gains achieved by energy savings. Hence a future research direction would be addressing energy efficiency at power amplifier level and improving CR and M2M techniques.VI. References1 Luis .S, Nuaymi .L, and Bonnin .J, An overview and classification of research approaches in green wireless networks. Eurasip journal on wireless communications and networking 2012.1 (2012) pp.1-18.2 Xiaofei .W, et al. A survey of green mobile networks Opportunities and challenges. Mobile Networks and Applications 17.1 (2012) pp.4-20.3 Yan Chen Shunqing Zhang Shugong Xu Li, G.Y., Fundamental trade-offs on green wir eless networks, in Communications Magazine, IEEE , vol.49, no.6, pp.30-37, June 2011.