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Link Layer Multicasting with Smart Antennas No
Client Left Behind Souvik Sen, Jie Xiong,
Rahul Ghosh, Romit Roy Choudhury Duke
University
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Wireless Multicast Use-Cases

• Widely used service
• Interactive classrooms, Smart home, Airports
• MobiTV, Vcast, MediaFlo
• Single transmission to reach all clients

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Motivation

• Today
• Multicast rate dictated by rate of weakest
  client (1 Mbps)
• Inefficient channel utilization
• Goal
• Improve multicast throughput
• Uphold same reliability

1 Mbps
5.5 Mbps
11 Mbps
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Problem is Non-Trivial

• Scattered clients, different channel conditions
• Time-varying wireless channel
• Absence of per-packet feedback

1 Mbps
5.5 Mbps
11 Mbps
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Solution also Non-Trivial
11 Mbps
1 Mbps

• Low rate transmission leads to lower throughput
• High rate transmission leads lower fairness

Past research mostly assume omnidirectional
antennas
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Problem Validation through Measurements
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Measurements in Duke Campus
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Measurements in Duke Campus
AP
Transmission _at_ 1 Mbps
Clients
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Measurements in Duke Campus
Transmission _at_ 2 Mbps
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Measurements in Duke Campus
Transmission _at_ 5.5 Mbps
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Measurements in Duke Campus
Transmission _at_ 11 Mbps
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Measurements in Duke Campus
Delivery Ratio
Client index
Topologies are characterized by very few weak
clients
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Reality
shadow regions
Weak clients tend to be clustered over small
regions
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Intuition
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Intuition
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Intuition
11 Mbps Omni
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Intuition
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Intuition
4 Mbps Directional
11 Mbps Omni
1 Mbps Omni
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Intuition to Reality
Few directional transmissions to cover few clients
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Challenges

• Partitioning the client set with optimal omni
  and directional rates
• Estimation of wireless channel
• Providing a guaranteed packet delivery ratio

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Proposed Protocol - BeamCast
Link Quality Estimator
BeamCast
Retransmission Manager
Multicast Scheduler
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Link Quality Estimator (LQE)

• How to estimate the bottleneck rate for each
  client?
• Bottleneck rate Max. rate to support a given
  delivery ratio
• AP takes feedback from the clients periodically
• LQE creates a database using the feedback
• Bottleneck rates are updated by using this
  database

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Link Quality Estimator (LQE)

• Theoretical relationship between delivery ratio
  (DR) and SNR

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Multicast Scheduler (MS)

• How to determine optimal transmission schedule?
• A schedule 1 omni many directional
  transmissions
• Optimal schedule Schedule with minimum
  transmission time
• MS extracts distinct client data rates from
  feedback
• We assume,
• Beamforming rate F x Omnidirectional rate
  F gt 1

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Multicast Scheduler (MS)

How to determine optimal transmission rate for
each beam?
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Multicast Scheduler (MS)

• Problem becomes harder with overlapping beams

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Multicast Scheduler (MS)

• Problem becomes harder with overlapping beams

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Multicast Scheduler (MS)

• Problem becomes harder with overlapping beams

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Multicast Scheduler (MS)

• Problem becomes harder with overlapping beams

Dynamic Programming used to solve the problem
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Multicast Scheduler (MS)
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Multicast Scheduler (MS)
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Retransmission Manager

• To cope with packet loss
• Receives lost packet information from the
  clients periodically
• Retransmits a subset of lost packets
• Choose packets using a simple heuristic

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Evaluation

• Qualnet simulation
• Comparison with Feedback enabled 802.11
• Main Parameters
• Dynamic channels Rayleigh, Rician fading
  External interference
• Antenna beamwidth 45o, 60o, 90o
• Factor of rate improvement with beamforming 3, 4
• Metrics Throughput, Delivery Ratio, Fairness
• Application specified Minimum Delivery Ratio
  90

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Multicast Throughput
Throughput decreases with increase in client
density
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Delivery Ratio
Increased delivery ratio for all clients, hence,
No Client Left Behind
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Limitations

• Switching delay has been assumed to be negligible
• Rate reduction for both fading and interference
• Requires link layer loss discrimination
• Focuses on one-AP-many-clients scenario
• Multi-AP environment will require coordination

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Conclusions

• Opportunistic beamforming for wireless
  multicasting
• Multiple high rate directional vs. a single omni
  transmission
• Rate estimation, scheduling and retransmission to
  achieve high throughput at a specified delivery
  ratio
• A potential tool for next generation wireless
  multicast

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Thanks !
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Questions or Thoughts ??
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Multicast Throughput
BeamCast performs better with increasing Fading !
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Smart Antennas in Multicast

• Jaikeo et. al talk about multicasting in ad-hoc
  networks
• Assume multi-beam antenna model
• Provide an analysis for collision probability
• Do not consider asymmetry in transmission range
• Ge et. al characterize optimal transmission
  rates
• -Discuss throughput and stability tradeoff
• Papathanasiou et. al discuss multicast in IEEE
  802.11n based network
• Minimize total Tx power but still provides a
  guaranteed SNR
• Assume perfect channel state information is
  available

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System Settings

• We assume IEEE 802.11 based WLANs
• Beamforming antennas are mounted on access
  points (AP)
• Clients are equipped with simple omnidirectional
  antennas
• Clients are scattered around AP and remain
  stationary
• Surrounding is characterized by wireless
  multipath and shadowing effects

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System Settings

• Antenna Model

A

• Improvement in data rate is possible
• C W log2 (1 SINR)

Higher with beamforming antennas
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Fairness

• Jains Fairness Index

Both schemes are comparable
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