EU FP7 Project iJOIN

http://www.ict-ijoin.eu/ @ict_ijoin

EU FP7 Project iJOIN

Cloudification of the 5G Radio Access Network

ITG Zukunft der Netze 2014

Sept. 26th 2014 Andreas Maeder, Peter Rost (NEC Laboratories Europe)

Contact: {andreas.maeder, peter.rost}@neclab.eu

iJOIN: Interworking and JOINt Design of an Open Access and Backhaul Network Architecture for Small Cells based on Cloud Networks

http://www.ict-ijoin.eu/



http://www.ict-ijoin.eu/ @ict_ijoin (( 2 ))

Laws of growth: drivers of cloudification

GSM GPRS

UMTS EDGE

HSDPA

WiMAX HSPA+

LTE LTE-A

1

10

100

1.000

10.000

100.000

1.000.000

1990 1995 2000 2005 2010 2015 2020

Cellular peak data rates over time

Dat

a R

ates

[kBi

t/s]

8088 80486

Pentium Pro

Pentium 4

AMD K8 Core 2 Duo Core i7 Opteron

Sparc T3

Intel Xeon Phi

0,1

1

10

100

1000

10000

1970 1980 1990 2000 2010 2020

Tran

sist

or C

ount

(10^

6)

Transistor Density

0,1

1

10

100

1000

1985 1990 1995 2000 2005 2010 2015

Sotra

ge D

ensi

ty (G

Bit/i

n²)

Storage Area Density Storage

Commu- nication

Processing





• SaaS • PaaS • IaaS

• On-demand • Broad access • Pooling • Elasticity • Measured

• C-RAN • RAN-Sharing • SDN • SDR

How the “Cloud” changes the picture …

SQL ISP

• NFV • vEPC • SDN

Core Network HetNet RAN Heterogeneous Backhaul

60GHz

Relay/Microwave

Copper

Optical

Mobile Network

Virtualization / “Cloudification”

The communication realm The IT world

Blurring borders between Communication and Information Technology





Key enablers to satisfy data demands

0

200

400

600

800

1000

1200

1400

1600

MoreSpectrum

FrequencyDivision

Modulationand Coding

SpectrumReuse

25 5 5

1600

Centralised Processing • C-RAN handles inter-cell interference, allows for higher

utilisation and to avoid peak-provisioning • Up to 50% energy-saving • 20%-50% OPEX reduction, 15% CAPEX reduction • Requires high capacity and low delay backhaul Centralisation is an option to implement the network but

requires more flexibility than today

Small Cells • 50% Total cost of ownership (TCO) savings • Four-fold increase in density until 2014 • Worth about 6.1bln USD until 2014 Small-cells are the option to handle higher rates and to

improve energy/cost-efficiency Fact

or o

f im

prov

emen

t





Key Concepts

Flexible centralisation through RANaaS (RAN-as-a-Service) Push RAN functionality into cloud-like platforms Simplified RAN management and flexible small-

cell solutions Reduce complexity & cost through elastic &

flexible function assignment Higher energy-efficiency through computational

diversity and higher utilisation

Joint design and optimisation of RAN and backhaul Interworking of access and backhaul network Optimise for flexible centralisation Optimise backhaul for small cells Consider heterogeneous backhaul network

(fibre and wireless) Relax backhaul requirements through dynamic

provisioning (“on-demand”)

Cloud Platform Core

Network

eNB

iSC iSC

iSC

iSC

iSC

eNB

RANaaS

Join

t Opt

imis

atio

n of

RA

N a

nd B

ackh

aul

iTN

RANaaS

LTE Air I/F mmWave Fibre Link

Very

den

se s

mal

l ce

ll ne

twor

k H

eter

ogen

eous

ba

ckha

ul la

yer

Flex

ible

RAN

func

t. as

sign

. to

clou

d

iSC: iJOIN Small Cell





Key Concepts: flexible functional split

RF

PHY

MAC

RRM

Netw. Mgmt.

Adm./Cong. Control

“Conventional” implementation of LTE

RF

PHY

MAC

RRM

Netw. Mgmt.

Adm./Cong. Control

C-RAN Implementation (BB-pooling)

Exe

cute

d at

BS

Centrally executed

Cen

trally

ex

ecut

ed

Executed at R

RH

Flexible Functional Split

Example: Partly centralised (inter-cell) RRM

Example: Joint Decoding





Key concepts: exploit centralization gains

Computational diversity Exploitation of temporal and spatial traffic fluctuations Efficiently use available resources, scale resource according to needs

(resource pooling, elasticity)

RAN

RANaaS

RANaaS Interface RANaaS Hypervisor





Key concepts: service and function agility

Localized optimization Optimization based on purpose, deployment, … Using software implementation rather than configuration (SON) Flexible software assignment over time and space

RAN

RANaaS

RANaaS Interface RANaaS Hypervisor





Challenges

Feasible and beneficial functional splits

Architecture

Data center placement

Utilization efficiency

Resource management of virtualized environment

Cost efficiency





Challenges: Where to split?

MA

C

HARQ Rtx

Multiplexing

Priority Handling

PH

Y-

FEC

Modulation

Etc.

PDCP

RLC

Buffering

Segmentation/ARQ

GTP

Scheduling

RRC

- More bandwidth - Lower Latencies

+ More gain?

Constraints and requirements: Backhaul characteristics

(latency, bandwidth) 3GPP requirements (latency,

bandwidth, protocol stack) Computational resources

Benefits:

Multiplexing gains (computational resources, user traffic)

Coordination gains (interference mitigation, cancellation, load balancing, ...)

..are an operator-defined optimization target!





RLC

PDCP

MAC

PHY

RRC

Functional split options

Minimal centralization requirement to achieve centralization gains: Main scenarios:

• Centralized data processing (PHY+higher layers) • Centralized resource allocation • Centralized connection control U-Plane

C-Plane

Centralized Resource Allocation

RANaaS SC

RLC

PDCP

MAC

PHY

Centralized Connection Control

LRRC GRRC

Scheduling

RANaaS: Central RRM iSC: Local RRM

RANaaS: global RRC iSC: Local RRC

RANaaS SC

CRRM Measurements, etc

LRRM





LTE Bandwidth demands

100% 1.1%

LTE UL 20Mhz 50% RB utilization 2 Rx Antennas SE 3 bit/s/Hz

user diversity gains





Challenges: network architecture

J2





Challenges: Data Processing Capabilities

Computational complexity depends on Functional split Number of connected base stations Number of connected devices Channel and traffic conditions

Strongly non-linear complexity in SNR





Computational complexity

System-level results for per-cell CC Correlation between #UEs and CC? Impact of scheduling, resource allocation?

3.6 3.65 3.7 3.75 3.8 3.85 3.9 3.95 4 4.05x 104

0

2

x 104

subframe index

tota

l com

p. c

ompl

exity

(bits

⋅ it)

3.6 3.65 3.7 3.75 3.8 3.85 3.9 3.95 4 4.05x 104

0

5

num

ber o

f UE

s pe

r cel

l

Comp. compl.#UEs





Challenges: Utilization Efficiency

0 5 10 15 20 25 30 35 40 45 5020

40

60

80

100

120

140

Number of cells N

Util

izat

ion

[%]

log10(ε) = -2log10(ε) = -1.75log10(ε) = -1.5log10(ε) = -1.25log10(ε) = -1

Utilization in current systems below 40% Utilization in centralized systems increases… but how much? Computational outage vs. channel outage should be same order

90+% Utilization can be achieved with centralized RAN





Challenges: Data Center Placement

Access Aggregation Metro Core

Internet

small cell

RANaaS

eNB

P/S-GW

iTN

Wired link

p2p wireless

P2mp wireless

C1

C3

C4

C5

C7

C6

C2





Challenges: cost-efficiency

0 2 4 6 8 101.5

2

2.5

Data center density [per sq-km]

CA

PEX

[MEU

R p

er s

q-km

]

DRANCRAN, LTE performanceCRAN, 0.4dB offsetCRAN, 0.9dB offset

BH Data centers





Cloudification decision variables

Functional split /

deployment

Constraints: backhaul, cell/user density,

protocols

Computational resource

availability

Operator optimization

target

Cost





Conclusions

New paradigms Operate RAN based on commodity hardware Resilience to computational and communication imperfections Allow for similar reliability on computation side as on communication side

New insights

Cloud RAN is cost-efficient when planned and deployed appropriately Computational demands are main drivers; depends on RAN resource allocation Many more results available on www.ict-ijoin.eu, e.g. feasible splits, BH

dimensioning, data center placement, CoMP, commodity HW implementation, …

Outlook: RAN cloudification will be integral aspect of 5G Standardization bodies will take up (e.g. small cell forum) IT companies will continue to push into telco space






Thank you for your attention!





Backhaul Technology Characteristics

BH technology Latency (one-way) Throughput

Ideal fiber access 2.5 µs 10 Gbps

Fiber Access 1 10 ms – 30 ms 10 Mbps – 10 Gbps

Fiber Access 2 5 ms – 10 ms 100 Mbps – 1 Gbps

DSL Access 15 ms – 60 ms 10 Mbps – 100Mbps

Cable 25 ms – 35 ms 10 Mbps – 100 Mbps

Sub -6 GHz Wireless 5 ms – 35 ms 50 Mbps – 100Mbps

Microwave < 1 ms 100 Mbps – 1 Gbps

mmW radio < 1 ms 500 Mbps – 2 Gbps

Diverse characteristics Significant impact




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EU FP7 Project iJOIN