PRECISE: Power Aware Dynamic Traffic Steering in Tightly Coupled LTE Wi-Fi … · 2019-11-03 ·...

PRECISE: Power Aware Dynamic Traffic Steering inTightly Coupled LTE Wi-Fi Networks

Thomas Valerrian Pasca S, Himank Gupta, Bheemarjuna ReddyTamma and Antony Franklin A

Department of Computer Science and EngineeringIndian Institute of Technology - Hyderabad

PIMRC - 2017 PRECISE IITH 1 / 27

Outline

1 Introduction

2 Challenges in C-LWIP Architecture

3 Proposed SolutionIM PhaseGI PhasePRECISE

4 Performance Evaluation

5 Conclusions


Introduction

Introduction

Mobile data traffic growth is exploding and it will reach 35Exabytes per month by 2020 [1]Telco providers/operators face challenges in order to improve theirnetwork capacitiesUtilizing unlicensed band efficiently has gained operator interestfor the increasing their bandwidth

Offloading traffic from cellular network toWi-Fi network has become operator sweetspot for handling the demandWe focus on LWIP for harvesting the benefitsof unlicensed band


Introduction

Multi RAT Aggregation

Application Layer

Protocol Stack Optimization

Intelligence is required to send the traffic

over multiple interfaces based on metrics

such as RTT and bandwidth

Medium access techniques can be enhanced,

when one link regulates and coordinates

medium access of the other link

Application should be intelligent to open

multiple sockets on different IP addresses

and reorder the data at application layer

Traffic offload algorithms based on

network state can be implemented for

effective utilization of multiple links

Replace your text here! Replace your text here! Replace your

text here!

Replace your text here! Replace your text here! Replace your

text here!

Your Text

Application layeraggregation (eg.,Samsung boost)Transport layeraggregation (eg.,MPTCP)IP layer aggregationloosely coupled (eg.,PMIP, ANDSF)IP layer aggregationtightly coupled (eg.,LWIP)


Introduction

LTE Wi-Fi interworking

Internet EPC

WLAN eNB

UE

NSWO S2a S1 S2a/S2b S1 S1NSWO NSWO

Tunneling

R12 eSaMOG

(CN Based)

CN Based

NB-IFOM & ANDSF Enhancement

RAN Based

Integrated 3GPP-WLAN RATs

1

1Ref: Intel presentation at TSDSIPIMRC - 2017 PRECISE IITH 5 / 27

Introduction

LWIP Architecture

LWIP has following benefitsWi-Fi operations are controlled directlyvia LTE base station (eNB) andtherefore LTE core network (i.e.,Evolved Packet Core (EPC)) need notmanage Wi-Fi separatelyRadio level integration allows effectiveradio resource management acrossWi-Fi and LTE linksLTE acts as the licensed-anchor pointfor any UE, providing unified connectionmanagement with the network

LWIP has finer level of control on radiointerfaces, for making efficient steeringdecision

S1 U

Figure : C-LWIPArchitecture


Challenges in C-LWIP Architecture

Challenges in C-LWIP Architecture

Co-tier interference due to densification of small cellsQoS provisioning for users in high interference zoneIndependent deployment of LTE and Wi-Fi nodes results in poorinterference mitigationSteering the traffic across LTE and Wi-Fi alone does not suffice.


Proposed Solution

Proposed Solution - PRECISE

Two Phase of Optimization i.e. IM Phase and GI PhaseIM Phase: Sets the Optimal transmit Power for LTE and Wi-Fiinterfaces to avoid co-tier interferenceGI Phase: Sets the transmit power of LTE and Wi-Fi interface inorder to meet the GBR requirementsSteering: Efficient traffic steering to aggregate the link benefits

IM Phase GI Phase

LTE Coverage in

IM Phase

Wi-Fi Coverage

in IM Phase

Coverage expanded

by GI Phase

Coverage reduced

by GI Phase

A

CB

D


Proposed Solution IM Phase

Interference Mitigation (IM) Phase I

Maximize the SINR for the users by varying the power of LTE andWi-Fi links

A fractional frequency reuse pattern of LTE and Wi-Fi coveragemaximizes the users SINR

Maximize ΘIM =

U,B∑i=1,j=1

(αLi,j × SINRL

i + αWi,j × SINRW

i ) (1)


Proposed Solution IM Phase

Interference Mitigation (IM) Phase II

s.t.B∑

j=1

αLi,j ≤ 1 ∀i and

B∑j=1

αWi,j ≤ 1 ∀i (2)

αLi,j =

{1, if SINRL

i ≥ ThLTE

0, otherwise(3)

αWi,j =

{1, if SINRW

i ≥ ThWi−Fi

0, otherwise(4)

αLi,j =

{0 or 1, if αW

i,j = 10, otherwise

(5)

αWi,j =

{0 or 1, if αL

i,j = 10, otherwise

(6)

PLmin ≤ PL

j ≤ PLmax ; PW

min ≤ PWj ≤ PW

max (7)PIMRC - 2017 PRECISE IITH 10 / 27

Proposed Solution GI Phase

GBR Improvement (GI) Phase

Objective function maximizes the weighted SINR function whereweight is proportional to number of unsatisfied GBR

Maximize ΘGI =

U,B∑i=1,j=1

(rLi,j × SINRL

i + rWi,j × SINRW

i ) (8)

s.t. {SINRL

i − (γ ×Θ(SINRLi )) ≥ 0 if Θ(SINRL

i ) ≥ SM

SINRLi −Θ(SINRL

i ) ≥ 0 otherwise(9)

{SINRW

i − γ ×Θ(SINRWi ) ≥ 0 if Θ(SINRW

i ) ≥ SM

SINRWi −Θ(SINRW

i ) ≥ 0 otherwise(10)

PLmin ≤ PL

j ≤ PLmax ; PW

min ≤ PWj ≤ PL

max (11)


Proposed Solution GI Phase

Traffic Steering : TOPSIS

Input: Set of all flow (Fi ) parameters, Link to which flow affinityhas to be obtained

1: Vector Normalization of all flow parameters Fi,j where i ∈ {flows1,. . . ,k}, j ∈ {network parameters}

2: Apply given set of weights wT = {w1, . . . ,wn}3: Fi,j ← Fi,j × wj4: Find A+ (Positive ideal solution) and A− (Negative ideal solution)5: Find Positive ideal separation (S+) and Negative Ideal separation

(S−)6: Calculate Ci for each flow: Ci ← Si−

Si++Si−7: AI ← sort {Ci } in descending order8: Return the flow affinity index AI i for every flow Fi


Proposed Solution PRECISE

PRECISE

Trigger IM

Phase

Start

Obtain all Flow Parameters

Gs >=90%

Trigger GI

Phase

TOPSIS

Load LTE >

Load Wi-Fi

Steer unmet GBR

flows to Wi-Fi

Is GBR unmet?

Steer set of NGBR

flows with high AI

to Wi-Fi

Is GBR unmet?

Steer set of NGBR

flows with high AI

to LTE

Steer unmet GBR

flows to LTE

Stop

After

experiment

duration



Experimental Setup

Parameter Value

# of UEs, LWIP Nodes 100, 4Max Tx power of LTE & Wi-Fi 23, 20 dBm

LTE path loss model 3GPP indoor path loss modelWi-Fi path loss model ITU path loss modelLTE MAC Scheduler Priority Set Scheduler (PSS)

UE position RandomUE mobility model Constant Position Mobility Model

Wi-Fi Standard IEEE 802.11nWi-Fi frequency and bandwidth 2.4 GHz, 20 MHzLTE frequency and bandwidth 2.6 GHz, 10 MHz



Simulation Setup

0

50

40

300

1020

20

3010

40

0 50

5

10

-40

-20

0

20

40

60

X: 26

Y: 25

Z: 7

X: 35

Y: 41

Z: 1

X: 42

Y: 17

Z: 7

X: 11

Y: 23

Z: 4

Figure : Building dimensionconsidered for evaluation

Building of dimension 50m X50m X 10mBuilding has two floors and awall per every 10m4 C-LWIP nodes placed withmean euclidean distancebetween nodes as 20mPath loss model includes walland floor losses


Performance Evaluation

SINR Distribution

0

0.2

0.4

0.6

0.8

1

-20 -10 0 10 20 30 40 50

CD

F

SINR (dB)

Fixed Power (LTE)PRECISE (LTE)

Fixed Power (Wi-Fi)PRECISE (Wi-Fi)

Figure : CDF of UE SINR.

SINR distribution observed infollowing 2 Cases

LWIP with fixed powerLWIP with optimal powerobtained from PRECISEalgorithm

PRECISE has improved SINRof UEs by 4 dB in both LTEand Wi-Fi linksThis improvement in SINR isdue to optimal power control



Ensure GBR in the network

0

20

40

60

80

100

120

140

# o

f G

BR

flo

ws n

ot m

et

GI Phase TriggerLoad=100Load=300Load=600

0

20

40

60

80

100

120

140

0 2 4 6 8 10

Thro

ughput (M

bps)

Time (Seconds)

Load = 100Load = 300Load = 600

Figure : Events triggered for varyingload.

When no of flows are 100, IMphase is triggered morefrequently since there are lessunsatisfied GBR flows.As number of flows increases,more GI Phase is triggeredmore which regulates thetransmit power inorder toreduce unsatisfied GBR Flows.



Different Phases of PRECISE Algorithm

0

10

20

30

40

50

100 200 300 400 500 600

# o

f T

rig

gers

Load (# of flows in the network)

IM-Phase TriggersGI-Phase Triggers

Figure : Triggers for differentthreshold.

In every 200 msec either of IMPhase or GI Phase will betriggeredAs number of flows increasesfrom 100 to 600, the numberof IM Phase trigger reducessince more unsatisfied GBRflows exists.PRECISE instantiates more GItriggers to reduce unmet GBRflows



Throughput Analysis

0

0.2

0.4

0.6

0.8

1

0 0.5 1 1.5 2 2.5 3 3.5

CD

F

User Throughput (Mbps)

Wi-Fi PreferredRel-12

α-OptimalPRECISE

Figure : CDF of UEs throughput.

CDF of UEs throughputobserved for a fixed number ofFlows i.e 600.Rel-12 ensures that UE isassociated with best interfaceand flows are routed through itα-Optimal only steer the flowsacross interface proportionallyfair based on link ratesPRECISE regulates thetransmit power and alsoenables flow steering acrossbest interface



Throughput Analysis (contd.)

0

20

40

60

80

100

120

140

160

300 350 400 450 500 550 600

Thro

ughput (M

bps)



α-OptimalPRECISE

Figure : Throughput for different load.

0

50

100

150

200

300 350 400 450 500 550 600N

um

ber

of U

nsatisfied G

BR



α-OptimalPRECISE

Figure : Unsatisfied GBR.



Throughput and GBR Analysis

Performances of different algorithms are compared with PRECISEalgorithm for 600 Flows.PRECISE algorithm has improved the network throughput by 48%and 84 % as compared to α-optimal Algorithm and 3GPP REL-12respectively.PRECISE algorithm minimizes the unmet GBR flows compared toother algorithms beacause of PRECISE alogrithm regulates thetransmit power of LWIP node and steer the flows to best availableinterface. While α-optimal only steer the flows and Rel-12 choosethe interface beased on best SINR available.PRECISE algorithm has reduced the number of GBR flows unmetby 35% as compared to α-optimal scheduler.


Conclusions

Conclusions and Future Directions

Co-located LWIP enables sophisticated control over LTE andWi-Fi RATs.PRECISE algorithm thrives to ensure QoS and maximizesthroughput in co-located LWIP deployment scenario.PRECISE algorithm employs power control for interferencemitigation and to enhance GBR throughput of UEs with poorSINR.PRECISE supports dynamic flow steering using MADM techniquein order to improve the network throughput.PRECISE outperformed throughput of α-optimal scheduler by48% and 3GPP Rel-12 interworking by 84%.PRECISE reduced the number of unmet GBRs by 35% comparedto α-optimal scheduler.PRECISE can be optimized further to improve UE battery savings.


Conclusions

Acknowledgements

This work was supported by the project "Converged CloudCommunication Technologies"


Conclusions

References I

[1] Cisco. (2017) Visual Networking Index: Global Mobile Data TrafficForecast Update. [Online]. Available: https://goo.gl/zY4nKI[2] 3GPP, "LTE-WLAN Aggregation and RAN Controlled LTE-WLANInterworking," Tech. Rep. 36.300, 2016.[3] S. Thomas et al., "Architectural Challenges and Solutions forCollocated LWIP - A Network Layer Perspective," in 2017 Twenty ThirdNational Conference on Communication (NCC), March 2017, pp. 1-6.[4] S. Deb et al., "Algorithms for eICIC in LTE HetNets," IEEE/ACMTrans. on Net., vol. 22, no. 1, pp. 137-150, 2014.[5] J.-H. Lee et al., "Host-based distributed mobility management:Example of traffic offloading," in IEEE CCNC, Jan 2013, pp. 637-640.[6] K. Lee et al., "Mobile Data Offloading: How Much Can Wi-FiDeliver?" IEEE/ACM Trans. on Net., vol. 21, no. 2, pp. 536-550, April2013.


Conclusions

References II

[7] S. Singh et al., "Optimal traffic aggregation in multi-RATheterogeneous wireless networks," in IEEE, ICC, May 2016, pp.626-631.[8] S. Singh et al., "Proportional Fair Traffic Splitting and Aggregation inHeterogeneous Wireless Networks," IEEE Communications Letters,vol. 20, no. 5, pp. 1010-1013, May 2016.[9] Y.-J. Lai, T.-Y. Liu, and C.-L. Hwang, "Topsis for MADM," EuropeanJournal of Operational Research, vol. 76, no. 3, pp. 486-500, 1994.[10] 5GAmericas. (2015, Nov) Whitepaper on LTE Aggregation andUnlicensed spectrum. [Online]. Available: http://goo.gl/4yHPhH[11] 3GPP, "LTE/WLAN Radio Interworking" Tech. Rep. 37.834, 2013.[12] Skype. (2017) How much bandwidth does Skype need?[Online].Available: https://goo.gl/KYCZ5V


Conclusions


Conclusions

For Further Queries Contact US

[email protected]

www.thomasvalerrianpasca.in

https://github.com/ThomasValerrianPasca/


Date post:	22-May-2020
Category:	Documents
Upload:	others
View:	10 times
Download:	0 times

PRECISE: Power Aware Dynamic Traffic Steering in Tightly Coupled LTE Wi-Fi … · 2019-11-03 ·...

Documents