network slicing based 5g: mobility, resource management, and challenges · network slicing based...

http://www.ece.ubc.ca/~haijunzhang/ [email protected]

Network Slicing Based 5G:

Mobility, Resource Management, and Challenges

Haijun Zhang April 29, 2017

University of Science and Technology Beijing

Email：[email protected]

Web: http://www.ece.ubc.ca/~haijunzhang/

mailto:[email protected]

http://www.ece.ubc.ca/~haijunzhang/


Content

Background

System Architecture

Challenges

Mobility Management

Resource Management

1

2

3

4

5


1

Background

5G Drivers

5G Development

Guide


Mobile Internet and the Internet of Things (IoT) are two main drivers for future network slicing based 5G networks.• Exponential traffic and Massive data requirements• Ultra dense heterogeneous networks• Cloudization and virtualization• "Mobile" out, wireless "connectivity" in• New business model• Energy challenge• Nobody can "make" more spectrum…

5G Drivers


5G Development

A concept for future mobile and wireless communications system that supports the connected information society.• An end-to-end ecosystem• Network as a service• Fully mobile and connected society • Consistent user experience• Sustainable business models

1000xhigher mobile data volumes

10x – 100xhigher number of connected devices

10x – 100xtypical end-user data rates

5xlower latency

10xlonger battery life for low-power devices


2

System Architecture

System architecture

Slicing management

Guide


WiFi

Mesh

MEC

Data Center

Content Server

Management Server

Edge Cloud

Core Cloud

Network Slicing

Bac

khau

lF

ront

hau

l

Access Unit Access UnitAccess Unit

uRLLC SliceIoT Slice

NFV&SDN

Control plane

Data plane

eMBB Slice

Control plane

Data plane

Control Unit

Data UnitCache

Cloud Unit

Cloud Unit

Control Unit

Data Unit

Control Unit

Application V2X

Data UnitV2X

Cloud Unit

Centralization

Distribution

Fro

nth

aul

Fro

nth

aul

Bac

khau

l

Bac

khau

l

Macro BS

System Architecture

➢ Substantial change of

5G network architecture

➢ Perfect combination of

NFV & SDWN

➢ Heterogeneous ultra

dense small cell

networks

Network slicing based 5G system architecture


An end-to-end network slice is a specific collection of network functions and resource allocation modules isolated from other network slices.

uRLLC Slice

eMBB Slice

IoT Slice

NFV&SDNVir

tuali

zed

Reso

urc

es

Ph

ysi

cal

Resou

rces

Compute

Storage

Network

Compute

Storage

Network

Compute

Storage

Network

Compute

Storage

Network

Access

NetworkEdge Cloud

Core

Cloud

Netw

ork

S

lices

Application

Control plane

User plane

Dedicated Physical

Infrastructures

SDN

ControllerVNFM

Management & Orchestration

VIM

Network Slicing Management

VIM: Virtualized Infrastructure Management

VNFM: VNF Management

➢ enhanced mobile

broadband (eMBB)

slice

➢ ultra-reliable and low-

latency communication

(uRLLC) slice

➢ Internet of things (IoT)

slice

Slicing Management

Network slicing management with SDN & NFV


3

Mobility Management

Necessity

Mobility management

Guide


Network slicing based 5G systems will still face mobility management challenges caused by the potentially ultra high density of 5G networks combined with highmobility and high density of end devices.

Necessity

➢ the simple and single RAT

handover cases have evolved

to managing complex, multi-

RAT mobility scenarios

➢ the integrated control

functions can reduce control

signaling even for massive

distribute network nodes

➢ different network slices have

different requirements for

mobility, latency and reliability


Mobility Management

UETarget

Access UnitCore Cloud

Source

Edge Cloud

Target

Edge Cloud

Source

Access Unit

Measurement ControlArea Restriction Information Provided

Packet Data Packet Data

UL Allocation

Measurement Reports Measurement Reports

HO Decision

HO Request

Admission Control

HO Request ACK

HO Request ACK

Handover CommandHandover Command

Detach from Source

cell & Synchronize to

Target cell

Deliver buffered & transit

packets to target cell

Data forwarding

Data forwarding

Buffer packets

from source cell

Synchronization

DL Allocation

UL Allocation + TA for UE

SN state transfer

Handover Confirm Handover Confirm

Packet Data Packet Data Packet Data

Path Switch Request User Plane Update

Request

Switch DL pathEnd Marker

Packet Data Packet Data

End Marker

End MarkerEnd Marker

User Plane Update

ResponsePath Switch Response

Ack

UE Context Release

Release

Resources

Handover

Preparation

Handover

Execution

Handover

Completion

L3 Signaling L1/L2 SignalingUser Data

➢ Mobile devices register their locations when they first connect to the network, and then report their location information to the network periodically.

➢ The HSS will be distributed into the edge cloud, making them closer to end devices to shorten registration delays and reduce backhaul burdens.

➢ 5G networks will aggregate multiple heterogeneous RATs.

➢ Multi-RAT coordination is needed for different RATs to share location information of their mobile devices for achieving unified multi-RAT access and seamless mobility in 5G networks.

Location registration Handover management


SDWN(5G)

4

Resource Management

System modelling

Problem formulation

Simulation results and

discussions

Guide


System Modelling

➢ A suburban environment is considered with small cells randomly distributed in the macrocell coverage area.

➢ Uplink transmission resource allocation is developed including joint subchannel and power allocation.

➢ Small cells receive two kinds of interference: • cross-tier interference from the microcell;• co-tier interference from neighboring small cells.

Scenario assumption

➢ Coverage radius: macrocell, 500 m; small cells: 10 m.➢ Carrier frequency: 2 GHz.➢ Channel bandwidth: 10 MHz.➢ Minimum inter-small-cell distance: 20 m.➢ Macrocell user (requesting IoT slicing services) number: 50.➢ Each small cell user (requesting eMBB and uRLLC slicing services)

number: 2 or 4.

System parameters


The uplink resource allocation problem is developed as the maximization of uplink capacity on each subchannel for small cells considering the following constraints:

Problem Formulation

, , , ,

, , , ,, f 1 1 1

maxF

f u n f u n

F U NF

f u n f u na p u n

a C

, , , , max1

, , max

, , , ,1

, , , , , ,1 1

, ,1

, ,

s.t. 1 : , ,

2 : 0 , , ,

3 : , ,

4 : ,

5 : 1, ,

6 : {0,1}, , ,

NF

f u n f u nn

F

f u nN

F

f u n f u n u eMBBnF U

F FM th

f u n f u n f u n nf uU

f u nu

f u n

C a p p f u

C p p f u n

C a C R k u D

C a p g I n

C a f n

C a f u n

Objective function:

Constraint conditions:

a non-convex discrete objective function

➢ a convex continuous function

(by relaxing the binary subchannel allocation indictors)

➢ K×N sub-problems

(Lagrangian dual decomposition method)

• the optimal power allocation

(KKT conditions)

• the optimal subchannel allocation

(sub-gradient method)

• maximum transmit power

• minimum data rate requirement

• threshold of total interference power

• subchannel scheduling policy


Simulation Results and Discussions

eMBB uRLLC IoT

➢ The eMBB slice capacity rises nearly linearly with the density of small cells and increases

slightly with the number of users per small cell.

➢ The total capacity of uRLLC slice increases with the number of small cells, but the capacity

of uRLLC slice is 20 times less than that of eMBB slice.

➢ The total capacity of the IoT slice decreases with the number of small cells, due to the

increasing cross-tier and co-tier interference.


5

Challenges

Network reconstruction

Slicing management

Cooperation with other

5G technologies

Guide


• Both RAN and CN need reconstruction to support end-to-end network slicing.

• Especially in UDHSNs, not only the cooperation of macrocells and small cells should be designed to meet the customized slicing demands.

• The cooperation of multiple RATs should be considered to provide seamless mobility and high transmission throughput.

Network reconstruction


• Supporting customized configuration of resources, management models, system

parameters for various use cases in an isolated or abstract way.

• Service providers and operators have started developing industrial solutions for

network slicing.

• To create, activate, maintain and deactivate network slicing at the service level.

• To adjust load balance, charging policies, security and QoS at the network level.

• To abstract or isolate virtualized network resources; inter-slice and intra-slice

resource sharing.

Slicing management


• Network slicing needs to coexist and cooperate with traditional wireless network

technologies (such as broadband transmission, mobile cloud engineering (MCE),

SDN and NFV) evolved from LTE/LTE-A systems.

• However, there is still no proper approach to integrate network slicing with C-RAN,

SDN and NFV.

• The virtualized cloud of access networks and CN have the advantages of physical

resource pooling, distribution of software architectures, centralization of management.

Technology Cooperation

Air Interface

• Higher frequency bands

• NOMA

• massive MIMO

• mmWaves

• CR

Network Deployment

• Ultra-dense

• Heterogeneous

• Small cell

• D2D

• V2X

Virtualization

• User/Control plane spilt

• Cloudization

• C-RAN

• SDN/NFV

• MCE


Thanks！

network slicing based 5g: mobility, resource management, and challenges · network slicing based...

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