Analysis of IEEE 802.11e and Application of Game Models for Support of Quality-of-Service in Coexisting Wireless Networks

1
Analysis of IEEE 802.11e and Application of Game
Models for Support of Quality-of-Service in
Coexisting Wireless Networks

• Stefan Mangold
• ComNets Aachen University
• 30-June-2003

2
Outline

• IEEE 802.11 wireless LAN
• Brief introduction Distributed Coordination
  Function (DCF)
• IEEE 802.11e QoS extension
• Overview Enhanced DCF (EDCF)
• Achievable throughput with the EDCF
• Model for achievable throughput per priority
• Result evaluation with WARP2
• Overlapping radio networks in unlicensed bands
• Game model of competition
• Result evaluation with YouShi
• Analysis of competition scenario stability,
  expected outcomes
• Cooperation in repeated games
• Conclusions

3
Motivation of this Thesis

• IEEE 802.11 is the dominant radio system for
  wireless Local Area Networks (LANs)
• Todays Wireless LANs cannot support Quality of
  Service (QoS)
• However, the demand is growing for new
  applications with QoS requirements
• Wireless LANs operate in unlicensed frequency
  bands, where they have to share radio resources
• Problems/Questions
• How to support QoS in wireless LANs?
• If wireless LANs can support QoS, what level of
  QoS can be maintained in unlicensed frequency
  bands?
• New methods to support QoS in wireless LANs are
  developed and evaluated in this thesis.

4
IEEE 802.11 Wireless LAN

• Radio standard for data transport system that
  covers ISO/OSI layer 1 and 2
• Multiple Physical (PHY) layers
  .11/.11a/.11b/.11g
• One common Medium Access Control (MAC) layer
• Here IEEE 802.11a PHY
• OFDM multi-carrier transmission
• Up to 54Mbit/s (_at_PHY)
• 5 GHz unlicensed band
• Shared resources
• Main Service
• MSDU Delivery
• Reference model ?

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Medium Access

• Distributed Coordination Function (DCF)
• Listen before talk CSMA/CA
• Binary exponential backoff
• Contention window increases with each
  retransmission
• Received MPDUs (data frames) are acknowledged
• Variable frame body sizes (up to 2312 byte)
• One queue per station
• Collisions occur if many stations operate in
  parallel

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IEEE 802.11 Wireless LAN Basics

• MAC protocol is distributed (simple and
  successful)
• One queue per station (station backoff entity)
• MSDU can be fragmented into multiple MPDUs
• RTS/CTS helps to improve efficiency
• QoS involves achieving a minimum MSDU Delivery
  throughput and MSDU Delivery delays not exceeding
  a maximum limit
• Delay variation and loss rate are often
  considered
• IEEE 802.11 Task Group E (TGe) defines QoS
  mechanisms to be integrated into the legacy
  802.11 MAC
• This supplement standard is referred to as IEEE
  802.11e (here draft 4.0)
• QoS Support in legacy 802.11? ? no!

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802.11e Medium Access HCF

• Contention-based medium access EDCF
• Different EDCF parameters per Access Category
  (AC)
• DIFS?AIFSAC
• CWmin?CWminAC
• ) not in current draft
  standard

• CWmax?CWmaxAC
• (PF2?PFAC)

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Achievable Throughput

• Three different EDCF parameter sets
• AC (priority) higher medium(legacy) lower
• AIFSNAC 2 2 9
• CWminAC 7 15 31
• CWmaxAC 1023 1023 1023
• PFAC 24/16 32/16 40/16
• Question achievable throughput per backoff
  entity in an isolated scenario? ? "saturation
  throughput"
• Isolated scenario means the same EDCF parameters
  are use by all backoff entities
• Results depend on frame body length, number of
  contending backoff entities, RTS/CTS,
  fragmentation
• Approach WARP2 stochastic simulation and
  analytical model (modifications of Bianchis
  legacy 802.11 model)

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Legacy (Medium) Priority

• 512 byte frame body 512 byte frame body,
  RTS/CTS
• 2304 byte frame body 2304 byte frame body,
  RTS/CTS

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Low Priority (larger CWminAC)

• 512 byte frame body 512 byte frame body,
  RTS/CTS
• 2304 byte frame body 2304 byte frame body,
  RTS/CTS

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High Priority (smaller CWminAC)

• 512 byte frame body 512 byte frame body,
  RTS/CTS
• 2304 byte frame body 2304 byte frame body,
  RTS/CTS

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Modified Bianchi Model
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Share of Capacity

• Saturation throughput shown so far is only valid
  for isolated scenarios
• Nice to have, but useless for QoS support
• For QoS support, a backoff entity needs to know
  the expected throughput in mixed scenarios
• Achievable throughput per backoff entity is
  referred to as "share of capacity"
• Question what is the share of capacity a backoff
  entity can achieve in a mixed scenario?
• This is THE important question for EDCF QoS
  support
• Bianchi model does not provide the answer
• There is no solution available until today

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Access Probability per Slot
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Approximation of Expected Idle Times

• Expected size of contention window
• NAC number of backoff entities of AC
• tauAC probability that a backoff entity is
  transmitting
• Access probability per slot
• Expressed by geometric distribution

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CSMA Regeneration Cycle Process

• State transition diagram for the Markov chain
• States C, H, M, L represent busy system
• States 1, 2, 3..., CWmax1 represent idle system
• Time is progressing in steps of a slot
• State of the chain changes with state transition
  probabilities as indicated in the figure

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Markov Chain (1)

• Resulting state transition probabilities
• access
• collision
• idle

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Markov Chain (2)

• Resulting stationary distributions
• high
• other

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Result

• The priority vector
• Share of capacity
• Modified Bianchi model provides the saturation
  throughput

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Scenario Results (1)

• Four backoff entities per AC (4/4/4)
• Variable, legacy and low priority
• Results of WARP2 simulation indicate accurate
  approximation

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Scenario Results (2)

• 10/2/4 backoff entities per AC
• Backoff entities with variable priority are more
  dominant, as expected
• Results of WARP2 simulation indicate accurate
  approximation

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Scenario Results (3)

• 2/10/4 backoff entities per AC
• Backoff entities with variable priority are more
  dominant, as expected
• WARP2 simulation results deviate for different
  persistent factors

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EDCF Summary

• EDCF MAC protocol is distributed (as DCF, simple)
• Multiple queues per station (queue backoff
  entity)
• The presented model can be used for prediction of
  expected share of capacity per backoff entity
• The model can be extended towards delay and loss
  prediction
• EDCF supports QoS, but cannot guarantee as
  resulting share depends on activity of other
  backoff entities
• QoS Support in legacy 802.11? ? no!
• QoS Support in 802.11e EDCF? ? yes, but no
  guarantee!

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HCF Controlled Medium Access

• EDCF cannot guarantee QoS, because of distributed
  MAC
• For guarantee, controlled medium access allows
  access right after PIFS, without backoff
• Similar to polling in legacy 802.11 (PCF)

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HCF in Overlapping BSS

• Controlled medium access requires an isolated BSS
• No other backoff entity must access the medium
  with highest priority (after PIFS), otherwise
  collisions occur!
• This is a very strict requirement, and difficult
  to achieve in an unlicensed frequency band
• Dynamic frequency selection may help, as in
  HiperLAN/2
• 512 byte frame body 2304 byte frame body

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HCF Controlled Access Summary

• The controlled medium access is often referred to
  as HCF
• This coordination function is not distributed, it
  is centralized (requires a Hybrid Coordinator)
• It works only in isolated scenarios, which is not
  a very likely scenario in unlicensed bands
• The coexistence problem of overlapping BSSs will
  be discussed in the following
• QoS Support in legacy 802.11? ? no!
• QoS Support in 802.11e EDCF? ? yes, but no
  guarantee!
• QoS Support with 802.11e HCF? ? not in unlicensed
  bands!

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Scenario two BSSs Sharing one Channel

• Basic service sets are modeled as players that
  attempt to optimize their outcomes
• Single stage game one superframe (200ms)
• Multi stage game repeated interaction

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The Superframe as Single Stage Game

• Allocation process during a superframe
• QoS

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Abstract Representation of QoS

• Throughput normalized share of capacity
• Delay normalized resource allocation interval
• Jitter normalized delay variation

,
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The Player

• Player "i" and opponent player "i" have
  individual requirements
• Players select demands to meet requirements
• Through allocation process, players observe
  outcomes per single stage game observed QoS
• This single stage game is repeated with every
  superframe
• Players adapt behaviors in the multi stage game

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Allocation Process (Formal Description)

• Required
• If this process can be formally described through
  an accurate approximation, we can analyze
• Expected outcomes (existence of Nash equilibrium
  (NE))
• Stability (convergence to NE)
• Fairness (position of NE in bargaining domain)
• It can be discussed
• what QoS support is feasible for the individual
  players (player CCHC BSS)
• what level of QoS can be achieved
• if mutual cooperation improves the outcome per
  player

.
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Markov Chain

• Observed payoffs in a single stage game
• Stationary distributions
• p0 idle channel (EDCF background traffic)
• p1 player 1 allocates radio resource
• p2 player 2 backing off while player 1 allocates
  resource
• State transition probabilities

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Result and Evaluation

• Resulting observations for both players
• Comparison with simulation results (YouShi)

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The Utility Function

• Players attempt to meet their requirements
• Therefore, players attempt to maximize the
  observed payoff (outcome), by using a utility
  function

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Existence of Nash Equilibrium (NE)

• Proposition in the Single Stage Game of two
  coexisting CCHCs exists a Nash equilibrium in the
  action space A.
• Proof show that the outcome (the payoff V) is
  continuous in A, and show that it is
  quasi-concave in Ai.
• There exists at least one Nash equilibrium, which
  can be calculated as
• aaction, Vpayoff, Nnumber of players (N2)

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Pareto Efficiency

• Players that take rational actions will
  automatically adjust into a NE (because there is
  at least one NE)
• If the NE is unique, the respective action
  profile can be predicted as expected point of
  operation
• However, there may exist action profiles in the
  single stage game that lead to higher payoffs
• If such profiles do not exist, the NE is referred
  to as Pareto efficient (Pareto optimal)
• Pareto efficiency can be determined by numerical
  search
• Can be shown in bargaining domain (next page)

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Bargaining Domain
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Strategy Persist

• Persist demandrequirement
• Shown are YouShi simulation results and
  analytical apprx.
• Poor delay performance for pl.2

pl1
pl2
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Persist/Best Response/Cooperation
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How to establish Cooperation

• Cooperation can be beneficial for both players,
  and is established in repeated interactions
  (multi stage game)
• Cooperation and punishment
• Payoff discounting in multi stage game

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Condition for Cooperation

• It is more efficient to cooperate instead of
  defect (instead of playing best response), if
• It depends on the discounting factor
  (importance/shadow of future) if mutual support
  is achievable
• The more important the future is, the more likely
  is the establishment of cooperation
• For example, CCHCs will interact for many
  superframes

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Dependence on Discounting Factor
Future counts
Future is less important
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Wrap Up

• There is always a Nash equilibrium in the single
  stage game
• If the outcome of the Nash equilibrium is not
  satisfying, a player may attempt to punish the
  opponent, for establishment of mutual support
• Depending on the behaviors of the CCHCs (the
  interacting players), and their requirements,
  cooperation can be achieved
• QoS can be supported if cooperation is
  established
• QoS Support in legacy 802.11? ? no!
• QoS Support in 802.11e EDCF? ? yes, but no
  guarantee!
• QoS Support with 802.11e HCF? ? not in unlicensed
  bands!
• QoS Support with shared radio resources? ? with
  mutual support yes!

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Conclusions

• IEEE 802.11e EDCF will provide basic means for
  QoS support
• The controlled medium access of HCF (polling)
  cannot support QoS in unlicensed frequency bands
• New analytical model for EDCF is developed
• allows to predict and control QoS
• New approach for coexisting radio networks
• may help radio networks operating in unlicensed
  bands to support QoS
• Results will be used in
• Contributions to IEEE 802.11e
• IEEE 802.19 coexistence discussions
• Spectrum etiquette development at Wi-Fi alliance
• Development of Spectrum Agile Radios (DARPA)

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Backup Slides
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Architecture

• Infrastructure Basic Service Set (BSS)
• one station is the access point
• Independent Basic Service Set (IBSS)
• ad-hoc

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Medium Access - Example

• Station 1 initiates frame exchange first
• Other stations set the Network Allocation Vector
  (NAV)
• Distributed approach ? difficult for station to
  support QoS

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Multiple Backoff Entities per Station
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Markov Chain

• State transition probabilities
• Stationary distributions

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Allocation Process (Example)

• Two single stage games (two superframes)
• Two players interact with each other
• A third player models the EDCF background traffic
• For analysis, a formal description of this
  process is needed

51
Strategy Best Response

• Best Response adapt demand to achieve highest
  outcome (myopic competition)
• Action profile (demand) converges to NE

pl1
pl2
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Strategy Cooperation

• Cooperation reduced demand, shorter resource
  allocations
• Now both players achieve higher outcomes (next
  page)

pl1
pl2