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Abstract—Energy efficiency in wireless networks, especially heterogeneous networks (HetNets) have received a lot of attention due to energy crisis and ...
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2012 IEEE Student Conference on Research and Development

Characterizing Energy Efficiency for Heterogeneous Cellular Networks Meysam Nasimi, Fazirulhisyam Hashim and Chee Kyun Ng Department of Computer and Communication Systems Engineering Universiti Putra Malaysia 43400 Serdang Selangor, Malaysia Email: [email protected], {fazirul, mpnck}@eng.upm.edu.my

Abstract—Energy efficiency in wireless networks, especially heterogeneous networks (HetNets) have received a lot of attention due to energy crisis and environmental protection. This emerging trend has motivated the academic and industrial world for new research area, which leads to green networks. In this paper, we provide a brief overview on those studies with an emphasis on introducing some energy efficiency metrics in HetNets such as Energy Consumption Ratio (ECR) and Energy Saving (ES). Since these metrics provide quantified information to compare and assess the efficiency of consumed energy, understanding those metrics can yield insight into the potential energy saving in HetNets. Furthermore, the assessment of potential energy conservation of both energy efficiency metrics will be carried out in different deployment strategies such as macro-micro, macro-relay and micro-relay. The obtained numerical results show that the macro-relay deployment strategy is much energy efficient compared to macro-micro and micro-relay. Therefore, it is concluded that the energy efficiency metrics can be the key measurement for the energy consumption in HetNets.

I. I NTRODUCTION Mobile broadband traffic with the proliferation of mobile terminals, especially smart phones and plethora of alwaysconnected devices have been increasing at the phenomenal rate [1]. This trend is set to continue with the over 100% percent annual growth, which has pushed the limits of energy consumption in cellular networks [2]. Among the energy consumption industry, the Information and Communication Technology (ICT) is playing an active role by representing around 2% of total carbon emissions. As an important part of ICT, wireless communications are responsible for energy saving [3]. In the cellular networks, the base station (BS) accounts for the largest fraction of energy consumption by up to 80%, which comes at a price of a large operational expenditure (OPEX) [4]. Hence, the energy efficient design in cellular networks has become an urgent demand. In fact, the energy efficient improvement can be achieved in two ways. The first way consists of reducing energy consumption in BS through the energy efficient hardware design or optimizing power amplifier. Another way is to bring the network closer to the User Equipments (UE) by reducing the propagation distance between BSs. Nevertheless, the advanced deployment strategies based on small and low power BSs are very promising. Thus, heterogeneous networks (HetNets), which utilizing a diverse set of BS deployment strategies such as macro, pico,

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femto and relay to supplement conventional macro cellular networks, is seemed a way to increase system performance as well as energy efficiency of the cellular networks [5]. In order to verify the energy efficiency in different deployment strategies with different configuration, it is important to assess the metrics of energy efficiency from various perspectives. In this paper, we provide a brief overview on some energy efficiency metrics in HetNets such as Energy Consumption Ratio (ECR) and Energy Saving (ES). The assessment of both energy efficiency metrics will be carried out in different deployment strategies such as macro-pico, macro-femto and macro-relay, and it shows that the co-existence of various cells in HetNets may reduce the total energy consumption of the networks. The obtained numerical results show that the macrorelay deployment strategy is much energy efficient compared to macro-pico and maco-femto. Therefore, it is concluded that the energy efficiency metrics can be the key measurement for the energy consumption in heterogeneous networks. The remainder of the paper is organized as follows. Section II presents an overview of the HetNet, notably its architecture. Section III discuss the effect of different deployment strategies on the energy efficiency and discuss energy efficiency metrics developed for different levels of networks/systems. Section IV presents some numerical results based on energy efficiency metrics for different HetNet scenarios. Finally, Section V concludes the paper. II. A N OVERVIEW OF H ETEROGENEOUS N ETWORKS A. Network Design Concept In general, heterogeneous networks or HetNets are relatively new networks design concept that is able to provide an energyefficient solution to cellular networks. It is based on the idea of a very dense deployment of low-cost and low-power BSs that are substantially smaller than the traditional macro BS. Thus, the HetNets consist of various types of BSs, including macro, micro, pico, femtocell and relays. Fig. 1 illustrates the typical architecture of HetNets and the relative coverage area of each BS. All the BSs may co-exist to form a kind of multi-tier architecture, and would rely on their self-organization functionalities for autonomous operation. In principal, to ensure area coverage in HetNets, umbrella macrocells may be needed, whereas most of the traffic is carried by a large number of smaller BSs.

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Fig. 1.

2012 IEEE Student Conference on Research and Development

The HetNets architecture consisting macro, micro, pico and femto.

Operationally, the HetNets may share the backhaul infrastructure with the already existing wireless/wired access points. The smaller-cell BSs such as pico and femto can be installed on lampposts, bus stops, corridor, etc. HetNets are envisaged to eliminate the need for costly cell site acquisition and regular maintenance, and therefore consequently reduce capital expenditure (CAPEX) and OPEX while at the same time providing unprecedented network capacities and good quality of service (QoS) to cellular network users.

Fig. 2.

Transmit power (W ) for macro and micro base stations.

B. HetNet Concept in Future Cellular Networks Owing to its potential to reduce the carbon footprint, enhance the system capacity and decreasing the network OPEX and CAPEX), the concept of HetNets has been utilized in the next generation mobile radio access systems, particular in the Long Term Evolution (LTE). Moreover, in LTE-Advanced Release 10, the HetNets deployment has been extensively discussed in addition to traditional well-planned macrocell deployment to further improve the system throughput [6]. In LTE-A, macro evolved Node B (eNB) will be complemented by Low Power Nodes (LPN), such as picocells, femtocells, Remote Radio Heads (RRH) and relay stations. A number of studies has shown that the deployment of such low power eNBs can provide significant advantages to the network, such as capacity improvement, coverage extension, cost reduction and energy efficiency. Due to their relatively smaller transmit power compared to macro eNB, i.e., ranges from 250mW to approximately 2W, they are regarded as more energy efficient. This is apparent in Fig. 2 and Fig. 3 which illustrate the transmit power and total power consumption between LPN and macro-eNBs, respectively. It is worthwhile to highlight that the impact of low power eNBs on the system capacity and energy efficiency have also been investigated in several studies. For example, in [7] the authors investigate the impact of picocell deployment on the network performance and energy saving. The results show the improvement in network capacity and energy efficiency. For the benefit of the readers, Table 1 summarizes the detail of different types of BSs in LTE-A. Note that pico eNBs (PeNBs) are low power BSs, which typically equipped with omni-directional antenna. They are usually deployed indoor

Fig. 3. Homogeneous macro power consumption vs. micro power consumption.

or outdoor and have a radio range of 300m or less. PeNBs have the same backhaul and access features as macro eNBs (MeNBs). Femtocell home eNBs (HeNBs) are small, lowpower, user-deployed cellular BS, which enhances indoor radio coverage for mobile users in home or small office. They are connected to the network operators via broadband connections such as Digital Subscriber Line (DSL) or cable. HeNBs are operated in restricted access known as closed subscriber group (CSG), meaning that only the subscribers of a HeNB are allowed to connect to it. Several studies have demonstrated that HeNBs have the ability to guarantee good QoS and high network capacity as well as lowering the infrastructure, maintenance and operational cost for network operators [8]. Relay nodes (RNs) are low-cost solution to improve coverage at a cell edge which could offer flexibility in backhaul. In [9], it has been shown that the joint deployment of MeNB-RN can achieve the energy saving up to 50%. However, despite of

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TABLE I D IFFERENT TYPE OF BASE STATIONS IN H ET N ET.

Nodes

Tx Power

Coverage

Access

Backhaul

MeNB

46 dBm

Few km

open

S1

PeNB

23-30 dB

< 300 m

open

X2

HeNB

< 23 dBm

< 50 m

CSG

DSL

Relay

30 dBm

300 m

open

Wireless

these benefits introduced by HetNets, the interference problem between macrocells and LPNs are one of the major concerns, which could degrade the network capacity and energy. III. E NERGY E FFICIENT VIA H ETEROGENEOUS N ETWORKS A. HetNet Deployment Strategies Recently, several researches have been performed to study the energy efficiency of radio access networks, and their suitability to address the requirements of future wireless networks (such as LTE and LTE-A). In this context, a research direction towards green communication has become an important trend in both academia and industry. As recently pointed out in [5], macro BS sites are the most energy-intensive component of cellular networks, which consume more than 80% power of the power in mobile networks. For this reason, most of the studies mainly concentrate on the power consumption of the resulting HetNets. For example, Fig. 3 shows the total power consumption of typical macrocell and microcell. The relation between power consumption and energy efficiency is more evident in some energy efficiency metrics where energy efficiency is measured as the ratio of network capacity to the power consumption [10]. Therefore, decreasing power consumption give rise to energy efficiency. Recent literature has widely analyzed the performance and optimization of energy efficiency in HetNets [4], [7] - [11]. They have considered different deployment strategies, namely macro-micro, macro-pico, macro-femto and macro-relay. In the following, we briefly discuss their works. 1) Macro-Micro: In [12] they have investigated the impact of random micro site deployment with varying density in different traffic load conditions. They have considered the ratio of cell throughput and total power consumption as the energy efficiency metric which is measured in bits per Joule. System level simulation has shown that for high traffic demand, twelve micro sites double the network energy efficiency by enhancing the area spectral efficiency. They confirmed that efficiency gain about 20% can be achieved when transmit power at a macro site has adjusted to covering 95% of cell. 2) Macro-Pico: In [7] the energy efficiency in two-tier HetNets, mixed macro-picocell topology was studied, and it was confirmed that such joint deployment could maximize the overall energy efficiency. In addition, network energy consumption and energy efficiency for joint macro-pico deployments have analyzed in [13] over a period of eight years. Their analysis has shown the 30% reduction in energy

consumption and high deployment of the pico site can carry 16% more traffic compared to a pure macro site. 3) Macro-Femto: [11] studied macro-femto deployment with considering the sleep mode during low traffic demand periods. Energy calculation and throughput simulation show the 36% energy saving only penalizes throughput in a 10%. Moreover, the relationships between system power consumption and average transmission bandwidth for combined macrofemto architecture has investigated in [14]. The results show that, for a certain density of femtocell, when more users have femtocells installed, the system power consumption decreases by different degrees. The optimal femtocell adoption ratio range is 20% to 60%. 4) Macro-Relay: In [15] they consider macro-relay deployment in LTE-A. It was stated that joint deployment is energy efficient compared to pure macrocell networks. For macrorelay deployment, result show that it can provide reductions up to 58% in energy. In [9], the authors investigate the overall energy gain with considering same metrics but with different scenario such as different traffic load and applying a sleep scheme. It was shown that the most significant energy reduction gain of up to 50% was observed in HetNets deployment. B. Energy Efficiency Metrics In order to evaluate the energy efficiency of the HetNets, it is important to measure the energy efficiency accurately. In this regard, energy efficiency metrics need to be defined in such a way that it can provide quantified information for comparing and assessing energy efficiency for different HetNets deployment. In general, energy efficiency metrics of communication systems can be classified into three main categories, namely, component level, access node level and network level metrics [16]. 1) Component Level: Component level metrics correspond to high-level systems where equipment is deployed (such as power amplifier, transceiver system, cooling equipment, DSP etc). In the component level, lots of attention have been devoted to the power amplifier efficiency metric, which mainly because of the large energy waste by this element. For example, Power Amplifier (PA) efficiency, which is a ratio of output to input power. Furthermore, at this layer, we may include the Energy Consumption Gain (ECG) [17] which can be useful for comparing two different systems. In general, the ECG can be defined as the ratio of the energy consumed by the baseline and the one consumed by the system under test. The ECG can be characterized as follows, ECG =

Eb Ea

(1)

where Eb is the baseline energy consumption and Ea is the consumed energy by the system under test. This metric can be easily manipulated to compare the energy consumption for homogeneous and heterogeneous deployment,

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ECG =

Ehom Ehet

(2)

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Fig. 4. Energy saving achieved by deploying sleep mode in HetNet, with different traffic load values.

which are represented by Ehom and Ehet , respectively. 2) Access Node Level: Access node or equipment level metrics are used to assess the performance of individual equipment in the network. Several metrics have been introduced in order to quantify the efficiency at the access node level. For example, the energy consumption rating (ECR) is proposed by ETSI [10], which refers to the energy used for transmitting a piece of information. The ECR can be characterized as follows, ECR =

energy consumption throughput

(Joule/bit).

(3)

Other metrics like spectral efficiency, power efficiency, and deployment efficiency are also widely accepted as a key indicator to determine energy efficient cellular networks. For example, spectral efficiency is used within the 3GPP to compare various physical layer energy related parameters. 3) Network Level: Network level metrics can be used to evaluate the performance of equipment as well as capacity and coverage of the network. Specifically, network level metrics addresses the cellular radio access network (RAN) performance. For instance, Area Power Consumption (APC) is introduced by [18] to evaluate the power consumption of the network relative to its size. The APC can be defined as,

Fig. 5. An ECGop , ECGem and ERGtot for different heterogeneous deployments.

P Wi = (αPtx + β). L

(5)

where α accounts for the scaling factor of transmission power Ptx , β is the fixed power consumed independently on the transmission power, and L represents the traffic load in the network. Note that both α and β may have different values depending on the type of base station. In this paper, we use the power model parameters in [5] where αma = 22.6, βma = 412.4, αmi = 5.5 and βmi = 32. Note that αma and βma represent parameters for the macro base station, whereas αmi and βmi are for micro base station. We consider three types of load, namely high, medium and low, where the L values are given by 90%, 50% and 20%, respectively. Next, let us denote by EC the network energy consumption, EC =

N BS X i=1

Z

H

P Wi (t)dt

(6)

0

IV. P RELIMINARY R ESULTS AND D ISCUSSIONS

where P Wi (t) is the power consumption of the ith base station at time H, and NBS indicates the total number of base stations of the HetNet deployment. We compute power consumption for two distinct modes. The first one is referred to as full function mode, where in this mode we assume that all base stations are working on full load (i.e., during the traffic peak). Obviously, this mode represent the worst case scenario, which drives the energy consumption to the maximum. The second mode is called sleep mode, where the energy consumption ECslp is computed when some of the macro base stations are off (i.e., P Wj (t) = 0). Now, by considering both the sleep mode scheme and full function mode, we may derive the energy saving metric as,

In this section, we investigate two energy efficiency metrics, focusing mostly on the previously mentioned equipment level metrics. Our computation is based on networks parameters used in [9] and [19]. First, we denote P Wi as the total power consumption of a base station, which can be characterized by linear power consumption model [20],

EC − ECslp × 100 [%]. (7) EC where EC and ECslp represent full function and sleep modes, respectively. Fig. 4 illustrates the energy saving based on considering the energy consumption in sleep mode and full function mode. The result implies the energy saving can be obtained by employing sleep mode where cells are completely

AP C =

Ps As

(W/m2 )

(4)

where Ps is the power consumption of macro base stations and LPNs, whereas As is the total area of the network in km2 .

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ES =

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switched off (P Wj (t) = 0). The percentage of energy saving in HetNets consisting macro and pico BSs in full, middle and low load are 43%, 50% and 55%, respectively. Meanwhile the Energy Consumption Gain (ECG) metric can be defined as the ratio of the operational power for homogeneous pure macro network and HetNets. The authors in [15] have introduced embodied energy as a part of total energy consumption, which correspond to the energy consumption during the whole life cycle of a product. The percentage ECGs of the operational powers and embodied energies of two networks are given by, ECGop =

(ρop )hom × 100 [%] (ρop )het

(8)

ECGem =

(Eem )hom × 100 [%] (Eem )het

(9)

where (ρop )hom and (ρop )het are the total operational power for homogeneous and heterogeneous networks in watt (W), while (Eem )hom and (Eem )het are the total embodied energies for homogeneous and heterogeneous networks in Joule (W/S). Moreover, Energy Reduction Gain (ERG) metric which can be derived from eq. (8) and (9), is used to compare the amount of energy saving based on homogeneous (macro-only) and heterogeneous deployment,  ERG =

(ρop + Eem )hom − (ρop + Eem )het (ρop + Eem )hom

 × 100[%].

(10) Fig. 5 depicts an energy consumption gain and energy reduction gain for different HetNets deployments, such as macro-micro, macro-relay and micro-relay. It can be observed that the joint macro-relay HetNets obtain the highest ERG by 63%, compared to macro-micro (28%) and micro-relay (32%). From our analysis, we found that the main reason behind this phenomena is because of the low transmit power of the relay (i.e., approximately 2W). V. C ONCLUSION This paper has identified the key benefit of HetNets from the energy efficiency perspective. It stresses that the energy efficiency metrics needed to be taken for assessing system efficiency. Two key metrics have been identified that quantify energy consumption performance such that ES and ERG. The ES metric is applied to the macro-micro joint deployment with adopting the sleep mode at different traffic load. The obtained numerical results show that energy saving between 43% and 55% can be achieved. The ERG metric is applied to HetNets with different deployment strategies such as macromicro, macro-relay and micro-relay to investigate the potential energy gains. This is found that the most significant energy gain with ERG of 63% in macro-relay has been observed. Therefore, it is concluded that the energy efficiency can be achieved in HetNets by deploying the appropriated metrics.

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