R2D2: Embracing Device-to-Device Communication in Next Generation Cellular Networks

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R2D2: Embracing Device-to- Device Communication in Next Generation Cellular Networks 1 Tarun Bansal*, Karthik Sundaresan + , Sampath Rangarajan + and Prasun Sinha* Speaker: Zhixue Lu* *Ohio State University and + NEC Labs America

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R2D2: Embracing Device-to-Device Communication in Next Generation Cellular Networks. Tarun Bansal*, Karthik Sundaresan + , Sampath Rangarajan + and Prasun Sinha* Speaker: Zhixue Lu* * Ohio State University and + NEC Labs America. Device-to-Device (D2D) Communication. - PowerPoint PPT Presentation

Transcript of R2D2: Embracing Device-to-Device Communication in Next Generation Cellular Networks

Page 1: R2D2: Embracing Device-to-Device Communication in Next Generation Cellular Networks

R2D2: Embracing Device-to-Device Communication in Next Generation Cellular Networks

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Tarun Bansal*, Karthik Sundaresan+, Sampath Rangarajan+ and Prasun Sinha*

Speaker: Zhixue Lu*

*Ohio State University and +NEC Labs America

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Device-to-Device (D2D) Communication Normally smartphones communicate with each other through

cellular base station

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Without D2D With D2D

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D2D Traffic Applications

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(a) Base Station Assisted: Localized communication and Machine-to-

Machine (M2M) communication

Benefit: Service provider helps with security, neighbor discovery and ensuring Quality-of-

Service

(b) Peer-to-Peer: Public Safety when traditional infrastructure is not available

Benefit: No interference

Our focus is on integration of Base Station Assisted D2D Traffic withexisting cellular communication

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D2D Benefits Spatial Reuse of Resources

– Multiple D2D transmissions per cell [Janis 2009, Doppler 2009, Lee 2013]

D1 D2

D4

D4

D1

D2Cell divided into 3 sectors with each sector covering

120o

Not possible to schedule multiple

D2D transmissions in the same sector.

D3

D3

Our analysis for sectored deployments: Very little benefit from additional spatial reuse

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D2D Benefits (contd.)

Offloading– Fewer time slots taken [Janis 2009, Doppler 2009, Lee 2013]

Time slot 1 Time slot 2

Time slot 1

Without D2D With D2D

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Benefit of D2D in sectored deployments(Static Channel Allocation)

Offload benefit is significant (1 time slot instead of 2)

Additional Spatial Reuse benefit (due to D2D) is not significant in sectored deployments due to small sector size

0 10 20 30 4010

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No D2D Baseline

D2D Baseline

D2D Genie

D2D Traffic (in %)

Thro

ughp

ut (i

n M

bps) Spatial Reuse

BenefitOffload Benefit

D2Dclassifiedas cellular

Tries to schedule

multiple D2D transmissions

per sector

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Identifying third D2D Benefit: Flexible Load

Use as flexible load– Resources need to be fixed in both Uplink and Downlink directions– In practice, UL-DL traffic distribution varies both in space and time e.g. residential

vs. commercial, morning vs. evening – D2D can go on either on the Uplink or Downlink resources– Use resources that would have been otherwise wasted

time

frequency

D2D flows

time

frequency

Uplink Flows Downlink Flows

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D2D Benefits

Offloading (1 time slot instead of 2)

Use as flexible traffic (Place on either DL or UL resource)

How do we maximize these two benefits?

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Static vs. Dynamic Channel Allocation

Static Channel Allocation

Dynamic Channel Allocation leverages spatial

traffic variations

Two co-located sectors

can have the same channel

Too much traffic: Borrow channels from neighboring sectors

Interior Channels Exterior Channels

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Challenges in Incorporating D2D with Dynamic Channel Allocation

UL or DL communications (directional) can still go simultaneously

D2D (omnidirectional) may cause interference to coexisting transmissions in sectored deployments (not considered before)

Determining interference from D2D transmission requires knowledge of path loss between all users (costly).

D1

D3D2

Similarly, D2D transmission cannot coexistwith UL or D2D

D2D presents a new challenge: Transmissions may cause interference if co-located sectors are using the same resource.

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D2D Interference (Dynamic Channel Allocation)

0 10 20 30 4050

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D2D Baseline

No D2D Baseline

D2D Traffic (in %)

Thro

ughp

ut (i

n M

bps)

Lower throughput with D2D due to collisions among neighboring sectors

D2Dclassifiedas cellular

Omnidirectional nature of D2D makes it non-trivial to schedule transmissions

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Objective• How to do dynamic resource allocation in multi-cell deployments

with D2D traffic?

• How to schedule UL, DL and D2D transmissions while avoiding interference?

• Previous work only looks at resource allocation without D2D traffic, OR

Scheduling with D2D in single cell deployments with no sectorization.

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R2D2 Contributions A light-weight scalable solution (R2D2) that works at two

different time-scales

– Phase 1: Allocate resources to each base station at coarser time scale (cross-sectors)

– Phase 2: Allocate resources to each flow independently at each base station at finer time scale (co-located sectors) while avoiding interference

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R2D2 Contributions Practical: Works in sectored deployments with multiple cells

Proposed multiple scheduling algorithms with provable guarantees

Showed using simulation results that proposed algorithms perform close to optimal in practice

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Phase 1: Cross-Base Station Resource Allocation

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Cell\ Historical Demand

DL UL D2D

Cell J X X X

Cell L X X X

Cell M X X X

Resources Available

X X

Input

Cell\ Resources Allocated

DL UL

Cell J X X

Cell L X X

Cell M X X

OutputR2D2Phase 1

Algorithm

J ML

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Phase 1: Cross-Sectors Resource Allocation

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Objective: Allocate UL and DL resources across 3 sectors in each of the directions

Proposed algorithm satisfies following properties:‒ Flexibly places the D2D traffic on UL and DL resources

‒ Localized and Scalable

‒ Ensure no interference across sectors belonging to different base stations

See Paper for more constraints and detailed solution

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Phase 2: Per-frame Scheduling

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D1

D2

D3

Each sector was a part of different interfering

set in Phase 1:

Same resourcemay get assigned toco-located sectors

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Phase 2: Per-frame Scheduling (contd.)

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Schedule UL, DL and D2D transmissions such that total throughput is maximized while avoiding interference

‒ Assign a time-frequency resource block to each flow in the three sectors

‒ Challenge: Path loss information between devices is unknown

D1

D2

D3

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Phase 2 Contributions

Scheduling algorithms at each Base Station:– A greedy polynomial algorithm with approximation ratio

of ½

– A faster greedy polynomial algorithm with approximation ratio of ¼

– More challenging since D2D can go on either DL resources or UL, but not both

• A greedy polynomial algorithm with approximation ratio of 1/3

Time-Divisioned System

Frequency-Divisioned

System

See Paper for detailed solutions

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Simulation Setup Simulation with 19 base stations and 57 sectors

– Modeled practical parameters including path loss, shadowing

Other algorithms simulated– R2D2 Low Complexity

– D2D Dynamic Genie (Optimal, knows path loss information between all users)

– No D2D Dynamic (Uses dynamic resource allocation and classifies all D2D traffic as Cellular)

– Existing Algorithm Static (Uses static resource allocation and does not use D2D as flexible traffic, Janis et al., IJCNS 2009) 20

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Results with variation in D2 traffic R2D2 Low Complexity

performs within 5% of optimal

R2D2 Low Complexity gives a throughput of 2.5x and 4.9x compared to existing solution and No D2D, respectively

Benefits coming from‒ Intelligent resource

allocation during Phase 1 while placing D2D traffic flexibly

‒ Interference-free scheduling during Phase 2

2.5x4.9xwithin

5%

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R2D2 Low Complexity D2D Dynamic Genie

No D2D Dynamic Janis et al. Static

D2D Traffic (in %)

Tota

l Thr

ough

put (

in M

bps)

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Conclusions Investigated the problem of incorporating D2D

communication in next generation cellular deployments with sectorization

Identified a new benefit of D2D communications: Flexibility‒ Towards that, proposed a solution that works at two different time

granularities that ensures scalability‒ Synergy between the two phases makes R2D2 light weight while

avoiding all interference

Proposed multiple algorithms with provable approximation ratios for resource allocation and scheduling

Thank You