Hybrid Scheduling in HeterogeneousHalf- and Full-Duplex Wireless Networks

Tingjun Chen*, Jelena Diakonikolas†, Javad Ghaderi*, and Gil Zussman*

*Electrical Engineering, Columbia University†Computer Science, Boston University

IEEE INFOCOM

Apr. 17, 2018

Full-Duplex Wireless

• Legacyhalf-duplexwirelesssystemsseparatetransmissionandreception ineither:

- Time:TimeDivisionDuplex(TDD)

- Frequency:FrequencyDivisionDuplex(FDD)

• (Samechannel)Full-duplexcommunication:simultaneoustransmission andreception onthesamefrequencychannel

2

Frequency

Pow

er

fTX = fRX

Transmit signalReceive signal

TDD

FrequencyPo

wer Transmit signal

Receive signal

fRX ≠ fRX

FDD

Frequency

Pow

er Transmit signalReceive signal

fTX = fRX

Full-Duplex (FD)

Full-Duplex Wireless

• Benefitsoffull-duplexwireless:

- Increasedsystemthroughput andreducedlatency

- Moreflexibleuseofthewirelessspectrumandenergyefficiency

• Viabilityislimitedbyself-interference

- Transmittedsignalisbillions oftimes(109 or90dB)stronger thanthereceivedsignal- Requiringextremelypowerful self-interferencecancellation

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The Columbia FlexICoN Project

4

• Full-DuplexWireless:FromIntegratedCircuitstoNetworks(FlexICoN)- Developmentoffull-duplex transceiver/system,algorithmdesign,experimentalevaluation,etc.

- Integrationoffull-duplexcapabilitywiththeopen-accessORBITtestbed

- FutureintegrationwiththePAWRCOSMOScity-scaletestbed (NSFPAWRSessiononWed.at15:30pminTapa1)

A programmable Gen-1 full-duplex node installed in ORBIT(Demo Session 2 on Wed. at 9:30am in Palace Lounge)

Gen-2 wideband full-duplex link(Demo at INFOCOM’17)

Motivation

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• Gradualreplacementandintroductionoffull-duplex(FD)devicesintolegacyhalf-duplex(HD)networks

• Goal:Developefficient andfair schedulingalgorithmsinsuchheterogeneoushalf-duplexandfull-duplexnetworkswithperformanceguarantees

FDUser

HDUser

FD AP

HDUser

HD AP

• Full-duplexradio/systemdesign

- Laboratorybench-topdesign: [Choietal.2010],[Duarte&Sabharwal,2010],[Aryafar etal.2012],[Bharadia etal.2013/2014],[Kimetal.2013/2015],[Korpi etal.2016],[Sayedetal.2017]

- Integratedcircuits(smallform-factor)design: [Zhouetal.2014/2015],[Debaillie etal.2015],[Yangetal.2015],[Reiskarimian etal.2016/2017],[Zhanget.al2017/2018]

• Throughputgainsfromfull-duplex:- [Xie &Zhang,2014],[Nguyenetal.2014],[Korpi etal.2015],[Marasevic etal.2017/2018]

• Cellular/WiFi scheduling:

- [Duarteetal.2014],[Yang&Shroff, 2015],[Alim etal.2016],[Chenetal.2015/2016],[Goyal etal.2016/2017]

• CSMA/Schedulinginlegacyhalf-duplexnetworks:- CSMA,Max-Weight,Greedy-Maximal,Longest-Queue-First, Q-CSMA,etc.[Kleinrock &Tobagi,1975], [Tassiulas&Ephremides1992],[Dimakis&Walrand,2006],[Brzezinskietal.2006],[Nietal.2012],[Birandetal.2012],etc.

• Heterogeneousnetworkswithbothhalf- andfull-duplexuserswerenotconsidered• Fairness betweenhalf- andfull-duplexuserswasnotconsidered• Verylittleworkprovidedperformanceguarantees(e.g.,throughputoptimality)

Related Work

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• Timeisslotted(t = 1, 2, …)

• Asingle-channel,collocated,heterogeneousnetworkwithoneaccesspoint(AP)andN users:

- TheAPandNF usersarefull-duplex (FD)

- NH = N – NF usersarehalf-duplex(HD)

• N downlinkqueuesattheAPandoneuplinkqueueateachuser

- TheAPhasinformation aboutalldownlinkqueues- Auserhasinformationaboutonly itsuplinkqueue

• Unitlinkcapacityandperfectself-interferencecancellation

• Feasibleschedules:asinglehalf-duplexuplinkordownlink,orapairoffull-duplexuplinkanddownlink• Apairoffull-duplexuplinkanddownlinkarealwaysscheduledatthesametime

Model

7

A heterogeneous networkwith NF = NH = 2

FDUser

HDUser

FDAP

Problem Formulation

8

• CapacityRegion:Convexhullofallfeasibleschedules

• Foralegacyhalf-duplexuser:

• Forafull-duplexuser:

• Aschedulingalgorithmisthroughput-optimal ifitcankeepthenetworkqueuesstableforallarrivalratevectorsintheinteriorofthecapacityregion

• Goal:Achievemaximumthroughputinnetworkswithheterogeneoushalf-duplexandfull-duplexusersinadistributedmanner,whilebeingfair toalltheusersandhavingfavorabledelayperformance

• Solution:H-GMS– AHybridschedulingalgorithmthatcombinescentralizedGreedyMaximalScheduling(GMS)anddistributedQ-CSMA

Uplink

Dow

nlin

k

1

1

Uplink

Dow

nlin

k

1

1

or and

�uplink

+ �downlink

1

max{�uplink

,�downlink

} 1

�uplink

1

�downlink

1

Introducing Full-Duplex Users – Everyone Gains!

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• AhomogeneousnetworkwithN = 10 half-duplex usersvs. AheterogeneousnetworkwithNH half-duplexusersandNF full-duplexusers(NH + NF = N = 10)

• ConsidertheastaticCSMAalgorithmwithfixedtransmissionprobabilitiespH andpF forhalf-duplexandfull-duplexusers.LetpF = γ pH withγ ∈ (0, 1]

• WithpH = 0.5, throughputgainofthenetwork:

A heterogeneous networkwith fixed N and varying NF

FDUser

HDUser

FDAP

Increased number

of FD users

Increased priority of FD users

γ

All FD users

Introducing Full-Duplex Users – Everyone Gains!

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• AhomogeneousnetworkwithN = 10 half-duplex usersvs. AheterogeneousnetworkwithNH half-duplexusersandNF full-duplexusers(NH + NF = N = 10)

• ConsidertheastaticCSMAalgorithmwithfixedtransmissionprobabilitiespH andpF forhalf-duplexandfull-duplexusers.LetpF = γ pH withγ ∈ (0, 1]

• WithpH = 0.5, throughputgainofindividualusers:

Increased number

of FD users

Increased priority of FD users Increased priority of FD users

Evenhalf-duplexuserscangain!

• Max-WeightScheduling(MWS)isthroughput-optimal

- Q-CSMAcanbeapplied

• WhatabouttheGreedyMaximalScheduling(GMS)?

- ThereturnedschedulemaynotbeMax-Weight

Scheduling Algorithms

11MWS ≠ GMS

FDUser HDUser

FDAP

3

4

5

6

FDUser HDUser

FDAP

3

4 3

2

MWS = GMS

• Max-WeightScheduling(MWS)isthroughput-optimal

- Q-CSMAcanbeapplied

• WhatabouttheGreedyMaximalScheduling(GMS)?

- ThereturnedschedulemaynotbeMax-Weight

• Proposition:ThecentralizedGreedyMaximalScheduling(GMS)algorithmisthroughput-optimalinanycollocatedheterogeneoushalf-duplexandfull-duplexnetworks

- Proof isbasedonlocal-pooling

Scheduling Algorithms

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• Question:HowtoachieveGMSisadistributedmanner?

• Solution:H-GMS – aHybridschedulingalgorithmthatcombinescentralizedGMSanddistributedQ-CSMA

Ifthepreviousslotisanidle slot:• Step1:Initiation (centralizedGMSattheAP)

- TheAPselectsthedownlinkwiththelongestqueue

- TheAPdrawsaninitiator linkfromalltheuplinksandtheselecteddownlinkaccordingtoanaccessprobabilitydistributionα

Proposed Algorithm: H-GMS in slot t

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FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

Step 1

Ifthepreviousslotisanidle slot:• Step2:Coordination(distributedQ-CSMA)

- Iflinkl isselectedastheinitiatorlink, itisactivatedw.p.p(Ql(t))

Proposed Algorithm: H-GMS in slot t

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FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

Step 2: if the HD downlink is selectedStep 1

Transmission probability andweight functions f(Q(t))

p(Q(t)) =exp(f(Q(t)))

1 + exp(f(Q(t)))

Ifthepreviousslotisanidle slot:• Step2:Coordination(distributedQ-CSMA)

- Iflinkl isselectedastheinitiatorlink, itisactivatedw.p.p(Ql(t))- Iftheinitiatorlinkisafull-duplexuplink (downlink), thecorresponding downlink (uplink) willalsobeactivated

Proposed Algorithm: H-GMS in slot t

15

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

Step 2: if the FD uplink is selectedStep 1

Transmission probability andweight functions f(Q(t))

p(Q(t)) =exp(f(Q(t)))

1 + exp(f(Q(t)))

Ifthepreviousslotisanidle slot:• Step3:Transmission

- Onepacketistransmittedoneachactivatedlink

Proposed Algorithm: H-GMS in slot t

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FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

Step 2: if the FD uplink is selectedStep 1

FDUser HDUser

FDAP 4

5αAPα1 α2

Step 3

2

2

Ifthepreviousslotisabusy slot:• TheAPkeepsthesameinitiatorlinkandrepeatssteps2&3

Proposed Algorithm: H-GMS in slot t

17

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

Step 2: if the FD uplink is selectedStep 1

FDUser HDUser

FDAP 4

5αAPα1 α2

Step 3

2

2

• Theorem:Foranyarrivalratevectorinsidethecapacityregion,thesystemMarkovchain(X(t), Q(t)) ispositiverecurrentundertheH-GMSalgorithm.Theweightfunctionf canbeanynonnegativeincreasingfunctionsuchthator.

- Proof isbasedonfluid limitanalysis

• VariantsofH-GMS:- H-GMS (orH-GMS-L)- H-GMS-R:theAPselectsadownlinkqueueuniformly atRandom,α isuniformly distributed

- H-GMS-E:theAPselectsthedownlinkwiththelongestqueue,α isproportional totheEstimateduplinkqueues

Main Results

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lim

x!1 f(x)/ log(x) < 1

lim

x!1 f(x)/ log(x) > 1

FDUser HDUser

FDAP

3

3 4

5α

α α

FDUser HDUser

FDAP

3

3 4

5α α

α

FDUser HDUser

FDAP

3

3 4

5αAPα1 α2

H-GMSα = 1/3

H-GMS-Rα = 1/3

H-GMS-Eαl � Ql

p(Q(t)) =exp(f(Q(t)))

1 + exp(f(Q(t)))

Performance Evaluation – Queue Length

• SimulationswithN = 10 userswithNF = NH = 5 inaheterogeneousnetwork• Equalarrivalrateonalltheuplinksanddownlinkswithtotalarrivalrateρ ∈ (0, 1]• Averagequeuelength(packet)foreverylink

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Thelargelyreducedqueuelengthresultedfrom(i)utilizingthecentralizeddownlinkqueueinformationattheAP,and(ii)theintroductionoffull-duplexusers

Performance Evaluation – Fairness

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• SimulationswithN = 10 userswithNF = NH = 5 inaheterogeneousnetwork• Equalarrivalrateonalltheuplinksanddownlinkswithtotalarrivalrateρ ∈ (0, 1]• Fairnessbetweenfull-duplexandhalf-duplexusers(i.e.,ratiobetweentheirqueuelengths)

H-GMS-L andH-GMS-E improvefairnessbyselectingtheinitiatorlinkdifferently

Avg. Qfull-duplex

Avg. Qhalf-duplex

Performance Evaluation – Effect of NF

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• SimulationswithN = 10 userswithNF = NH = 5 inaheterogeneousnetwork• Equalarrivalrateonalltheuplinksanddownlinkswithtotalarrivalrateρ ∈ (0, 1]• FairnessunderdifferentvaluesofNF

Medium traffic intensity, ρ = 0.8 High traffic intensity, ρ = 0.95

Avg. Qfull-duplex

Avg. Qhalf-duplex

Summary

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• Schedulinginheterogeneoushalf-duplexandfull-duplexwirelessnetworks

• Alltheuserscangain(evenforhalf-duplexusers!)intermsofthroughputwhenintroducingfull-duplexusersintolegacyhalf-duplexnetworks

• H-GMS – ahybridschedulingalgorithmcombiningcentralizedGMSanddistributedQ-CSMA,andisproventobethroughput-optimal

• PerformanceevaluationofH-GMS

• Futuredirections:

- DelayanalysisofH-GMS

- Experimentalevaluationusingexisting/customizedfull-duplex testbeds

• Pleasecometoourfull-duplexdemotomorrowat9:30amifyouareinterested!

Thank you!

tingjun@ee.columbia.edu

http://www.ee.columbia.edu/˜tc2668

Tingjun Chen, Jelena Diakonikolas, Javad Ghaderi, and Gil Zussman,“Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks”.

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