05425544

Mobility and Capacity Offload for 3G UMTS Femtocells

Farhad Meshkati, Yi Jiang, Lenny Grokop, Sumeeth Nagaraja, Mehmet Yavuz, and Sanjiv Nanda Qualcomm Inc., 5775 Morehouse Dr., San Diego, CA 92121 USA

{fmeshkat, yij, lgrokop, sumeethn, myavuz, snanda}@qualcomm.com

ABSTRACT Femtocells are low-power cellular base stations that are typically deployed indoors in residential, enterprise or hotspots settings. Femtocell deployments provide excellent user experience through better coverage for voice and very high data throughputs. In this paper, we focus on 3G UMTS femtocells and analyze the impact of femtocells on idle-mode mobility and UE battery life. Detailed dynamic simulations are presented to quantify the impact of femtocells on the number of cell searches, cell reselections and location area updates for both femtocell users and macro users. It is shown that femtocells reduce the number of intra-frequency and inter-frequency searches for femtocell users while increasing the number of searches for macro users. In addition, methods for facilitating capacity offload to femtocells are presented. In particular, cell reselection parameter optimization, use of beacons and enhancements of UE search algorithms are described as possible methods for facilitating capacity offload to femtocells. The tradeoffs between capacity offload and UE battery life are also evaluated.

Keywords- Battery life, beacon, capacity, coverage, femtocells, HSPA, idle-mode, mobility, UMTS.

I. INTRODUCTION A femtocell (also called Home NodeB) is a term generally used for a low-power cellular base station that is typically deployed indoors in residential, enterprise or hotspots settings. Femtocell deployments provide excellent user experience through better coverage for voice and very high data throughputs [1]. In addition, cellular operators benefit from reduced infrastructure deployment costs that are otherwise needed for network evolution, including capacity upgrades and coverage improvements. Capacity improvements due to femtocells are due to two reasons. First, users who switch to femtocells receive very high throughputs since they are one of the few users served by the Home NodeB (HNB). Secondly, capacity offload (transfering users from macro to femtocells) helps macro users to achieve higher throughputs since fewer users share the macro network resources. Therefore, enabling capacity offload to femtocells is crucial in improving the overall system capacity. More details about UMTS femtocell coverage performance and capacity can be found in [2]. This paper focuses on methods for facilitating capacity offload to 3G UMTS femtocells and quantifying the

potential impacts on UE battery life. The main focus of this paper is on idle mode UE behavior. In particular, we use a dynamic mobility simulation model to quantify the impact of femtocells on number of intrafrequency searches, interfrequency searches, cell reselections and location area updates. It is shown that femtocells can dramatically reduce the number of cell searches and cell reselection for femtocell users while increasing the numbers for macro users rather mildly. Methods for facilitating capacity offload are also presented and their impact on UE battery life is discussed. A two-frequency deployment scenario is considered where macro and femto users share f1 whereas f2 is used by macro users only. Also, restricted association is assumed which means a femto mobile, or home user equipment (HUE), can only access and get served by the macro NodeBs (MNB) and its own HNB whereas a macro mobile, or macro UE (MUE) can only access and get served by the MNBs. The remainder of the paper is organized as follows. Simulation model and assumptions are described in Section II. Detailed simulation results showing the impact of femtocells on idle-mode mobility and the tradeoff between capacity offload and UE battery life are given in Section III. Methods for facilitating capacity offload to femtocells are described in Section IV. Finally, conclusions are given in Section V. II. SYSTEM SIMULATION MODELS AND ASSUMPTIONS We have developed a detailed path loss model of a dense urban neighborhood using the WinProp software tool by A.W.E. Communications [3]. Within the tool we utilize the dominant path prediction algorithm, which is a computationally efficient ray tracing feature that accounts for reflection, diffraction and penetration of electromagnetic waves off, around, and through media. Using field measurements we have been able to demonstrate the validity and accuracy of the modeling software.

A. Model calibration and accuracy Field measurements were used to aid in the selection of appropriate materials from the WinProp material database, and to get a sense of the accuracy of model. Data were collected in an apartment complex in Rancho Bernardo, CA. A total of 28 measurements were made with transmitter and receiver located in various positions in two neighboring apartments and the surrounding outdoor area. A WinProp model was created based on the apartment complex, and a set of building materials were chosen from the database to give good correlation between predictions and measurements. This material set was then used in the

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE "GLOBECOM" 2009 proceedings.978-1-4244-4148-8/09/$25.00 2009

creation of the dense urban neighborhood. Figure 1 compares the measured and predicted path loss values. The standard deviation of the predictions from the measurements was 3.79 dB, indicating close agreement.

B. Dense Urban Neighborhood The neighborhood, roughly 200m x 200m, consists of eight buildings, four 3 story and four 5 story. On each floor there are 10 apartments, six 3-bedroom (1250 sq. ft) and four 1-bedroom (625 sq. ft), making the total number of apartments in the neighborhood 320. The apartments contain a range of materials, selected from the material database included in the WinProp software. The materials were chosen based on comparison with field measurements. Figure 2 depicts the neighborhood and floor layout. The neighborhood is surrounded by generic concrete buildings of varying heights. Lying on the periphery of these buildings are three macro cells, two being co-located at the south-east corner, one in the north-west corner. Femtocells are randomly deployed in apartments with the likelihood of an apartment getting a femtocell being dependent on its macro coverage. This creates a clustering effect where areas of poor coverage have many femtocells and areas of good coverage have few. The location of the femtocell in an apartment is uniformly selected from a set of up to five possible sites. Two of these sites correspond to floor locations, three to desk/table locations. The clustering phenomenon is captured in Figure 3, which shows the deployment for the neighborhood situated at cell edge. The path loss profile, generated by WinProp for a sample femtocell location, is shown in Figure 5.

C. Mobility Routes Three types of neighborhood mobility routes, outdoor, corridor, and in-apartment ones, are used to model the typical idle UE movement patterns through the neighborhood, through buildings, and within apartments. There are four outdoor routes that follow the sidewalks and passageways between buildings and four corridor routes that model a UE walking from the entrance of its building, up several flights of stairs, along the corridor and ending at the entrance of its apartment. The in-apartment routes are divided into two categories. The first category consists of various routes starting from the entrance of the apartment and proceeding to a resting point, such as a nightstand, desk, dining table, or countertop, on which the UE rests for a period of time. These routes capture the behavior of a user returning home and placing their handset in a stationary location. The second category consists of a circuit that the UE periodically traverses, a certain number of times per day. This route captures the behavior of a user whose handset travels around the apartment with them, in their pocket. These routes are illustrated in Figure 3 and Figure 4.

Figure 1: Measured vs. predicted path loss values

(a)

(b)

Figure 2: (a) The dense urban neighborhood model. (b) Floor plan for each building.


Figure 3: Birdseye view of the neighborhood showing femtocell locations, outdoor routes (R1-R4), and corridor routes (R5-R8). The femtocells are color-coded to indicate which floor they lie on. This illustrates the clustering effect areas of poor macro coverage, such as the ground floors of certain apartment buildings, have a greater density of femtocells.

Figure 4: In-apartment routes consist of the UE i) moving along the red line from the entrance to one of the resting locations, ii) traversing the red circuit.

D. Simulation Assumptions A two-frequency deployment scenario is assumed in which f1 is shared by macro and femtos whereas f2 is for macro only. The two frequencies are assumed to be adjacent with an adjacent channel interference ratio (ACIR) of 33dB. We simulate idle cell reselection procedure to determine whether a HUE is camped on its HNB or on a MNB or whether it is moved to another carrier.

Figure 5: Path loss profile for a sample femtocell location

A HUE will switch to another carrier if it is not able to acquire the pilots of the HNB and macro on the shared carrier or if the HUE unsuccessfully attempts to perform an idle cell reselection to a restricted neighbor HNB. Similarly, a MUE will be moved to another carrier if it is not able to acquire the macro pilot or if it unsuccessfully attempts to perform an idle cell reselection to a HNB. A brief description of the 3GPP cell reselection procedure is given below and is also depicted in Figure 6. More details can be found in [4].

1. Every DRX cycle, UE wakes up and measures signal quality (CPICH Ec/No which is the ratio of the received pilot energy to the total received power spectral density at the UE) of the serving cell. Signal quality below a threshold initiates a cell search (intra or inter) procedure:

Squal < Sintrasearch or Squal < Sintersearch (3) where Squal = Qqualmeas Qqualmin captures the quality requirement of the current serving cell and Sintersearch is the inter-frequency threshold. Furthermore, Qqualmeas and Qqualmin denote measured and minimum required CPICH Ec/No respectively. Qqualmin is typically set to -18dB.

2. UE measures the signal quality of neighboring cells and checks suitability criterion:

Squal > 0, (4)

where, Squal = Qqualmeas Qqualmin Pcompensation. Typically, Pcompensation is set to 0.

3. UE ranks all cells that fulfill the suitability criterion. The ranking criteria for the serving cell is given by

Rs = Qmeass + Qhysts, (5)

where, Qhysts is the hysteresis applied to the serving cell on CPICH Ec/No. The ranking criteria for the neighboring cells is:

Rn = Qmeasn Qoffsets,n, (6)


The values Qhysts, and Qoffsets,n are sent on the downlink of the serving cell.

4. The highest ranked neighboring cell is selected. UE checks if the highest ranked cell is better than the serving cell for a time interval of Treselection (system information block (SIB) 3/ SIB 4 of the serving cell).

5. UE reads SIBs of the highest ranked cell and checks the suitability criteria for campingparameters are taken from SIB of the highest ranked cell.

6. UE performs Location Area Update (LAU) on the newly selected cell if the location area of the new cell is different from the one earlier. On receiving LAU Accept, the LAU procedure continues with the Core Network, On the other hand, on receiving LAU Reject, the UE performs the following:

i) Adds Location Area Code (LAC) of the cell to its forbidden list of LACs.

ii) UE status is set to roaming not allowed

iii) Stored information cell selection is performed to find a suitable cell.

7. In the next DRX cycle, if the highest ranked cell is in UEs list of forbidden LACs, the frequency is banned for up to 300 seconds.

Table 1 summarizes the idle cell reselection parameters used in our analysis. These parameters are set such that priority is given to HNBs over MNBs when a UE is performing idle cell reselection. However, a minimum CPICH Ec/No (also called CPICH Ec/Io) of -12dB is enforced for HNBs so that idle cell reselection to a HNB happens only when the HNB signal quality is good. The Sintrasearch and Sintersearch parameters for HNB are assumed to be 2dB and 2dB (corresponding to -16dB and -16dB CPICH Ec/No thresholds) so that HUEs stick to HNBs while at home. The macro Sintrasearch and Sintersearch settings are simulation parameters which are varied to quantify their impact on capacity offload and UE battery life.

Table 1 Parameters for idle cell reselection procedure

HNB cells: 3dBMacro cells: 5 dB

HNB cells: -50 dBMacro cells: 3dB


Qhyst+Qoffset

SIB11Qqualmin

Sintersearch

Sintrasearch

Qqualmin -18 dB-18 dB-18 dB

SIB3

F1F2F1

HNB cells: -12 dBMacro cells: not

needed


needed

Macro

Not needed

HNBSIB/Parameter

HNB cells: 3dBMacro cells: 5 dB



Qhyst+Qoffset

SIB11Qqualmin

Sintersearch

Sintrasearch

Qqualmin -18 dB-18 dB-18 dB

SIB3

F1F2F1


needed

S_intra_macro


needed

Macro

Not needed

S_inter_femtoS_intra_femto

HNBSIB/Parameter

S_intra_macro

S_inter_macro S_inter_macro

PLMN Search

Cell Resel

Location registration

Y

N 1Different LA?

AcceptedCause #15 or #13

YN

1Y

N

Ecp/Io Meas

Y

N

threshold. Also, the percentage of UEs that perform inter-frequency search decreases as Sinter decreases. There is no

Intra-frequency search events

0

20

40

60

80

100

120

Withoutfemocells

Withfemtocells

but nofemtocell

at ownhome

Withfemtocells

and afemtocell

at ownhome

Perc

enta

ge o

f UEs

per

form

ing

cell

sear

ch a

t a

give

n D

RX c

ycle

Sintra/Sinter=12/12 dB




Figure 7: Intra-frequency cell search events in three scenarios, without femtocells deployed, with femtocells deployed but no femtocell in own home, with femtocells deployed and a femtocell in own home for different macro Sintra/Sinter thresholds.

Inter-frequency search events

0

20

40

60

80

100

120

Withoutfemocells

Withfemtocel ls

but nofemtocell

at ownhome

Withfemtocel ls

and afemtocel l

at ownhome

Perc

enta

ge o

f UEs

per

form

ing

cell

sear

ch a

t a

give

n D

RX c

ycle Sintra/Sinter=12/12 dB




Figure 8: Inter-frequency cell search events in three scenarios, without femtocells deployed, with femtocells deployed but no femtocell in own home, with femtocells deployed and a femtocell in own home for different macro Sintra/Sinter thresholds.

noticeable increase of cell search events for the UEs which do not have their own femto at home. It is also seen from the figure that the deployment of femtocell reduces the intra-frequency search events of its own UE significantly and virtually eliminates the inter-frequency searches due to the high CPICH Ec/No of the femto. As we can see from Figure 9, the presence of femto results in an increase in the cell reselection (CR) events for those UEs that do not have a femtocell at home. The number of CRs increases as Sintra/Sinter parameters increase. This is because with higher Sintra/Sinter values, it will be more likely for the UE to perform search and discover other cells (e.g. femtoclls) which will result in more cell reselection or cell reselection attempts.

Cell reselection events

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Withoutfemocells

Withfemtocel ls

but nofemtocell atown home

Withfemtocells

and afemtocel l atown home

Perc

enta

ge o

f UEs

per

form

ing

cell

rese

lect

ion

at a

giv

en

DRX

cyc

le





Figure 9: Cell reselection events in three scenarios, without femtocells deployed, with femtocells deployed but no femtocell in own home, with femtocells deployed and a femtocell in own home for different macro Sintra/Sinter thresholds.

LAU events

00.20.40.60.8

11.21.41.61.8

Withoutfemocel ls

Withfemtocells

but nofemtocell

at ownhome

Withfemtocells

and afemtocell

at ownhome

Num

ber

of L

AU

s pe

r ho

ur





Figure 10: LAU events in three scenarios, without femtocells deployed, with femtocells deployed but no femtocell in own home, with femtocells deployed and a femtocell in own home for different macro Sintra/Sinter thresholds. Results are based on one-hour stay in resting locations.

Figure 10 compares the average number of LAU events per hour (including successful LAUs and rejected LAUs) performed by the UE. We assume the macro cells have the same LAC. Hence there is no LAU event in the absence of femtos. On the other hand, when femtocells are deployed, the MUEs and HUEs may attempt to camp on femtocells which will result in LAUs. If the UE is not allowed on the femtocell (e.g., an MUE), the LAU will get rejected and the UE will reselect back to a macro cell. This would result in an additional LAU. Also, with higher Sintra/Sinter values, it will be more likely for the UE to perform search and discover a femtocell which will result in more LAUs. Figure 11 shows the distribution of the time taken for a HUE to find its own femtocell when it enters its apartment from corridor. Negative values on the x-axis correspond to cases where UE finds its own femto in the corridor even before


entering the apartment. It is seen from the figure that higher values of Sintra/Sinter result in better HNB discovery. For example, Sintra/Sinter=12/12 dB guarantees that the HUE is able to find its own HNB whereas with Sintra/Sinter=10/8 dB, the HUE is not able to find its own HNB 10% of the time.

Figure 11 Distribution of the time taken for UE to find its own femto from the moment it enters apartment.

IV. METHODS FOR IMPROVING CAPACITY-OFFLOAD

In addition to coverage improvements, the HNBs result in significant throughput improvements for HNB users. More details on this can be found in [2]. The benefits of femtocells can be leveraged only when UEs discover HNBs. Capacity offload is rather straightforward in single carrier deployments where macro and home NBs co-exist. With multiple frequencies, however, the HNB-discovery is non-trivial and needs addressing. Consider for example, a two-frequency (f1 and f2) macro network deployment. As a UE camping on a macro cell on frequency f2 approaches a HNB operating on frequency f1, the UE experiences little interference form the HNB (due to ACIR) and hence there is only a slight degradation in the macro signal quality for the UE. This degradation may not be enough to trigger inter-frequency search (depending on the value of Sintersearch). As a result, the UE remains on the macro and will never be able to find it own HNB on f1. This behavior significantly impacts capacity offload. Typically, finding new cells is carried out by mobility management procedures. Idle mode mobility management is performed by the cell search, selection and reselection processes outlined in Figure 6. With good macro coverage, a UE may never initiate searches and would remain on the macro even when it is in the vicinity of its own HNB. The HNB-discovery issue, therefore, necessitates enhanced mobility management techniques that enable UEs to discover and camp on HNBs. Three potential solutions for addressing the HNB-discovery issue are inter-frequency-search threshold optimization, beacon-based approach, and

UE enhancements. Overviews of these approaches are provided next. A. Search Threshold Optimization A UE searches for cells on other frequencies through inter-frequency searches. A search is initiated when the signal quality of the serving cell falls below an inter-frequency search threshold (i.e., Squal

percentage of macro UEs performing intra-frequency and inter-frequency searches increases slightly due to the additional DL interference from the nearby HNBs. This tradeoff is quantified for different cell reselection parameters in a two-frequency femtocell deployment where one frequency is shared by macro and femto users and the other frequency is used by macro users only. Furthermore, given the significant throughput improvements provided by HNBs, methods for facilitating capacity offload to femtocells are presented. In particular, cell reselection parameter optimization, use of beacons and enhancements of UE search algorithms are described as possible methods for facilitating capacity offload to femtocells. The tradeoffs between capacity offload and UE battery life are also discussed. For example, while increasing the intra-frequency and inter-frequency thresholds for idle mode helps many users find their own HNB, it will degrade the standby time of macro users due to additional searches. A beacon-based approach is introduced as an alternative method for facilitating capacity offload to femtocells.

VI. REFERENCES [1] V. Chandrasekhar, J. G. Andrews, and A. Gatherer, Femtocell Networks: A survey, IEEE Comm. Magazine, vol. 46, pp. 5967, Sep. 2008.

[2] M. Yavuz, F. Meshkati, S. Nanda, A. Pokhariyal, N. Johnson, B. Raghothaman and A. Richardson, Interference Management and Performance Analysis of UMTS/HSPA+ Femtocells, to appear in IEEE Comm. Magazine, Sep. 2009.

[3] http://www.awe-communications.com

[4] 3GPP TS25.304 V.8.5.0, User Equipment (UE) procedures in idle mode and procedures for cell reselection in connected mode.


/ColorImageDict > /JPEG2000ColorACSImageDict > /JPEG2000ColorImageDict > /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 200 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 300 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 2.00333 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages true /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict > /GrayImageDict > /JPEG2000GrayACSImageDict > /JPEG2000GrayImageDict > /AntiAliasMonoImages false /CropMonoImages true /MonoImageMinResolution 400 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 600 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.00167 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict > /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (None) /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False

/CreateJDFFile false /Description > /Namespace [ (Adobe) (Common) (1.0) ] /OtherNamespaces [ > /FormElements false /GenerateStructure false /IncludeBookmarks false /IncludeHyperlinks false /IncludeInteractive false /IncludeLayers false /IncludeProfiles true /MultimediaHandling /UseObjectSettings /Namespace [ (Adobe) (CreativeSuite) (2.0) ] /PDFXOutputIntentProfileSelector /NA /PreserveEditing false /UntaggedCMYKHandling /UseDocumentProfile /UntaggedRGBHandling /UseDocumentProfile /UseDocumentBleed false >> ]>> setdistillerparams> setpagedevice

05425544

Documents

Transcript of 05425544