small cells & ultrasontm - qualcomm · pdf file* small cells will be deployed in areas of...

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Small Cells & UltraSONTM



Overview


Strong Mobile Data Demand Requires Extra Capacity

Source: Cisco VNI Mobile, 2014

0

6

12

2012 2013 2014 2015 2016 2017

Exab

ytes

per

Mo

nth

1000X

Overall Mobile Data Traffic Growth

MOBILE NETWORKS NEED TO PREPARE FOR 1000X TRAFFIC GROWTH!

0.9 EB 1.6 EB

4.7 EB

2.8 EB

11.2 EB

7.4 EB

66% CAGR 2012-2017

3


Small Cells & Extra Spectrum Are Critical For Reaching 1000x

4

MORE

SPECTRUM IN LOW AND HIGHER BANDS

MORE SMALL

CELLS EVERYWHERE!

Evolve

3G/4G/Wi-Fi

HetNets

Interference Mgmt/SON

Intelligently

Access 3G/4G/Wi-Fi

HIGHER

EFFICIENCY

MORE INDOOR

CELLS INSIDE-OUT DEPLOYMENT


Progressive Introduction Of Small Cells To Build

Dense Carrier-Grade Network

BRING CARRIER-GRADE NETWORK CLOSER

TO USER FOR NEXT LEAP OF PERFORMANCE

Macros

+ planned

small cells

+ dense

unplanned* small cells

Combined network managed by operator

* Small cells will be deployed in areas of high demand without detailed RF planning. 5

Unplanned small cell Planned small cell


Deploying Small Cells Wherever Needed

6

LOW COST DEPLOYMENT

• Minimal CapEx and OpEx

• Leverages existing premises and backhaul

EASY TO DEPLOY

• Simple plug-n-play by customer with SON

• Unplanned yet scalable and operator-managed

HIGH CAPACITY

• Significant capacity gains compared to macro-only deployment

6

Neighborhood Small Cells (NSCs)

Picocells

Enterprise small cells

Enterprise small cells


LTE OTA Network in San Diego

7

Hyper Dense Outdoor SC Network • ~15m between SCs • Semi-planned deployment • Wireless backhaul for some SCs

Dense Indoor Network • NSC with in2out coverage over

campus • Seamless mobility between cells • Unplanned deployment • Enterprise indoor network in one

of the buildings

R&D platform for UltraSON features



UltraSON Features


LTE UltraSON Features

Self Configuration: Automatic cell parameter and backhaul config.

• Automatic PCI selection

• Automatic neighbor discovery (including 3GPP

ANR)

Backhaul Aware Operation: Handle backhaul constraints

• Backhaul quality aware load balancing

Category UltraSON Features

Mobility Management: Optimize HO performance and reduce signaling load

• Frequent Handover Mitigation

• Forward handover

• Robust mobility (including 3GPP MRO)

Dynamic Resource and Tx Power Management: Optimize capacity, minimize pilot pollution and load balancing

• Tx power management

• Resource partitioning and coordination

(including 3GPP ICIC)

• Load balancing (including 3GPP MLB and

macro-SC)


SON Features Help Small Cells Deliver Carrier-Grade

Performance

• In an unplanned/semi-planned deployment, RF environment around each

small cell is different and dynamic

• Small cell needs to be able to respond when it is turned on and continue

to adapt to the changing environment

10

AT STARTUP

• Select PCI and configure neighbor list • Calibrate Tx power • Optimize idle re-selection parameters and paging

area

AFTER STARTUP

• Adapt Tx power & update neighbor list • Coordinate & partition resources with other cells • Monitor backhaul quality & prioritize preferred

users • Balance load among different cells


Automatic PCI Selection and PCI Collision Resolution

• PCI selection/reselection using Network Listen and X2 messages

• Use a combination of Network Listen, X2 messages and UE

assistance to detect/resolve any potential PCI collision caused by

hidden node

PCI 1 PCI ?

PCI 4 PCI 3

PCI 2

11

PCI 1 PCI 3

PCI 4 PCI 2

PCI 2


Automatic Neighborhood Relation (ANR)

• Target PCI to Cell ID mapping

needs to be discovered to

enable handover

– Network Listen alone cannot

detect all neighboring target

cells for handover

• Mobile reports (ANR) and X2

message exchange can be

utilized to enhance the

neighbor cell list obtained via

Network Listen

• Need to handle persistence

and dynamic nature of network

topology

Macrocell2

Macrocell1

Small Cell 1

UE

Small Cell 2

Small Cell 1 can only detect Macrocell1

UE can also detect Macrocell2 and Small Cell 2

12


Main Considerations for Mobility Management for Small Cells

Facilitate handover to small cells to maximize traffic offload

Key Issues:

Mobile UEs on small cell layer likely to cross cell boundary frequently

Excessive handovers create signaling load and potential outage and hence should be avoided

Small cell to Small cell

Small cell carrier

Overlay Macro carrier

13


Frequent Handover Mitigation (FHM) Improves User Experience

14

• Frequent handovers impact user experience and increased signaling load

• Use MRO for overall mobility parameter optimization to improve handover

performance

• Use Frequent Handover Mitigation for per UE optimization beyond MRO:

• Classify users as high speed or ping-pong users

• Adjust handover parameters per UE to prevent ping-pongs

• Handover high mobility users to macro layer

Macrocell (Frequency f1)

Small cells (Frequency f2)

Fast moving UEs crossing coverage of different small

cells

Ping-ponging UE at the edge of small cells


Reduce Handover Failures Through Mobility

Robustness Optimization (MRO)

15

• Small cells monitor handover failures and the causes

– Example: “Too Early”, “Too Late”, and “Wrong Cell” handovers

– X2 messages exchanged between source and target cells on failures

• UltraSON tracks handover failures and successes for ping-pong,

slow moving and fast moving users

• UltraSON adjusts handover parameters for each user type at each

cell to reduce handover failures

A small cell serves and optimizes mobility for users with different mobility requirements

Fast moving users

Slow moving users

Ping-pong users


Forward Handover (FHO) Improves Robustness

16

• Robust handover performance is important to ensure excellent

user experience

– E.g., for push-to-talk application

• In regular handovers, source cell would prepare target cell by

sending UE context

• If target cell did not receive UE context in time, it can fetch UE

context from the source cell to reduce handover interruption

X2 Fetch UE context


Transmit (Tx) Power Management Improves SINR

17

• 7 outdoor small cells

• Improvement in SINR with UltraSON techniques

– Median SINR improvement of 6-10 dB

UltraSON ON UltraSON OFF


Joint Tx Power and Resource Management

• Dense small cell deployment results in degradation of SINR due to inter-SC

interference

• Joint Tx power and resource management to maximize capacity and network-

wide user experience

– Resource/interference coordination to improve user SINR

– Dynamic orthogonalization of resources for cell edge users

• Use of UE measurements reports and X2 messages for Tx power and

resource management

18

All Users Benefit if the SCs use orthogonal

resources

Both Users can be served on all resources

as the interference seen is low

Network-wide fairness is increased if User B gains a

lot, in return of User A sacrificing a small fraction of

resources

A

B

Signal

Interference


• Backhaul bandwidth availability can vary due

to backhaul sharing with other traffic (e.g.,

WiFi) and other users

• Backhaul aware load balancing is done

via:

– Estimating backhaul quality by probing

bandwidth and delay estimation servers

– Offloading SC UEs to macro when SC

backhaul is the bottleneck

– Dynamic load balancing between small

cells and between small cells and macros

based on backhaul quality

– Prioritizing home/enterprise user traffic

over other user traffic

Non-cellular traffic

from backhaul owner

Internet

Neighborhood Small Cell

Residential Gateway

Competing traffic from neighbors

19

Backhaul Aware Load Balancing - Overview


Mobility Load Balancing Between Neighboring Cells

20

• Mobility Load Balancing (MLB) distributes user load between LTE

macrocell and small cells as well as between small cells to

provide better user experience and improve system capacity

• MLB uses cell load information to optimize cell boundaries to

offload users

• UltraSON uses both mobility parameters and downlink transmit

power adjustment for load balancing

A B

A B



NSC Capacity Simulation Results


Dense Urban Neighborhood Small Cells Simulation Assumptions

Red: 2 story bldg Blue: 3 story bldg

Green: 4 story bldg Cyan: 5 story bldg

Yellow: 6 story bldg

Dense-Urban Area (Simulation with Apartment Buildings)

Black star: Small cell

Magenta Circle: Mobile

Blue circle: Macrocell

met

er

Notes: a) Small cells are randomly dropped in a apartment statistically

independent of other small cells’ locations b) At most one small cell is dropped in any apartment

Parameter Value

Macrocell ISD 500m

Population Density 20000 per sq km

Number of Apartments per Macrocell

(2 subs per Apt.) 720

User Distribution

70% Indoors/

30% Outdoors;

Randomly dropped

22


Neighborhood Small Cell Capacity Simulation Dense Urban Model Configuration

• Multi-floor apartment blocks placed in a

3-cell macro area

• Each apartment block has two buildings

with a street in the middle

• 10 apartments in each floor in each

building

– Two rows of 5 apts

– Each apt is 10m x 10m with a 1m-wide

balcony

• Detailed RF propagation modeling for

indoors and outdoors

– Indoor propagation based on Keenan-

Motley multi-wall model

– Explicit modeling of internal and external

walls, windows and floor losses

• Internal wall loss: 8dB

• External wall loss: 20dB

• Floor loss: 18.3dB (indoor users only)

0 50 100 150 200 250 300 3500

50

100

150

200

250

300

350ISD=1000m

Birds-eye view

Zoomed-in layout

10m

11m

10m

Apartment Block

23


Neighborhood Small Cells Capacity Simulation Baseline (macro-only) vs. Macro+Small Cells Deployments

F1

F2

Macro Network

NSC Network

Macro + Small Cells Deployment

F1

Macro Network

Baseline Macro Deployment

Rel 8 LTE, single 10 MHz LTE carrier at 2 GHz carrier frequency

Rel 8 LTE, 10 MHz carrier for macros at 2 GHz while small cells are deployed in 3.5 GHz

24


0x

20x

40x

60x

80x

100x

120x

140x

160x

180x

0% 10% 20% 30% 40% 50%

DL

Me

dia

n T

hro

ugh

pu

t G

ain

(x)

Small Cell Penetration (%)

DL Median Throughput Gains (LTE dense urban, 10 MHz BW small cells in 3.5 GHz, gains

relative to macros only)

25 UEs/macro 200 UEs/macro

Neighborhood Small Cells Provide Significant DL Capacity

Gains for LTE

Neighborhood Small Cells Offer Scalable Capacity As Demand Increases

• 500m ISD, 720 apartments/cell, 2 subs/apartment. Users randomly dropped, 70% indoor and 30% outdoor, 2x2 MIMO • Gains shown are relative to macro-only baseline. Macros deployed in 10 MHz bandwidth at 2 GHz. Small cells deployed at 3.5 GHz with 10 MHz bandwidth. • Small cell penetration is percentage of total apartments per macrocell (720) with a small cell. For a particular operator, this number cannot exceed its own

market share. For example, an operator with 30% market share can at most have 216 small cells in a macro (assuming no small cell is deployed outside customer premise by the operator).

(360 small cells) (72 small cells)

100x capacity gains at 20% penetration

Simulation Configuration

10 MHz

@ 2 GHz

10 MHz @

3.5 GHz

Macro

Small cell

25


Exceeding 1000x Capacity Gain With Dense Neighborhood

Small Cells And More Spectrum

• 500m ISD, 720 apartments/cell, 2 subs/apartment. Users randomly dropped, 70% indoor and 30% outdoor, 2x2 MIMO • Gains relative to baseline with macros only. Macros deployed in 10 MHz bandwidth at 2 GHz. Small cells deployed at 3.5 GHz with 100 MHz bandwidth. • Small cell penetration is percentage of total apartments per macrocell (720) with a Small Cell. For a particular operator, this number cannot exceed its own

market share. For example, an operator with 30% market share can at most have 216 small cells in a macro (assuming no small cell is deployed outside customer premise by the operator).

(360 small cells)

0x

200x

400x

600x

800x

1,000x

1,200x

1,400x

1,600x

1,800x

0% 10% 20% 30% 40% 50%

DL

Me

dia

n T

hro

ugh

pu

t G

ain

(x)

Small cell Penetration (%)

DL Median Throughput Gain (LTE, dense urban, 100 MHz small cells in 3.5 GHz, relative to

macros only) 25 UEs/macro 200 UEs/macro

(72 small cells)

1000x capacity at 20% small cell penetration

Simulation Configuration

10 MHz

@ 2 GHz

100 MHz @

3.5 GHz

Macro

Small cell

26



SON Architecture: Hybrid SON


Distributed and Centralized SON Components

28

• Autonomous eNB operation with real-time decision making

– eNB utilizes rich data set obtained from the radio layers

– Reduced signaling load eases complexity and processing need at

centralized entity

• Centralized Node with long term decision making

– Receives selected metrics from RAN

– Sets policies for distributed algorithms

– Performs optimization over wide area

Sets policies, less signaling, more scalable

Distributed Decision Making

Central Node


Hybrid SON: High Level View

KPIs Alarms Filtered information

Parameter Ranges Policy Guidelines

Backh

aul

Centralized Node

RAN 2

RAN 1


Summary

• Small cells can be deployed wherever extra capacity is needed

• Hyper-dense deployment of open access neighborhood small cells utilizes additional spectrum in the most efficient way

• Small cells provide a cost-effective way for operators to reach 1000x today’s network capacity – Low-cost deployment model leveraging existing premise and backhaul

• Easy to deploy, scalable and operator-managed via SON – Qualcomm is developing UltraSON Open for robust small cell

deployment

• Hybrid SON preserves the advantages of centralized SON and distributed SON

30


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small cells & ultrasontm - qualcomm · pdf file* small cells will be deployed in areas of...

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