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. Stefan Mangold - ComNets Aachen University1OutlineOutline 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. Stefan Mangold - ComNets Aachen University2 Motivation of this Thesis IEEE 802.11 is the dominant radio system for wireless Local Area Networks (LANs): Today’s 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. Stefan Mangold - ComNets Aachen University3 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 (@PHY) 5 GHz unlicensed band Shared resources Main Service: MSDU Delivery Reference model 

5. Stefan Mangold - ComNets Aachen University4 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 Medium Access

6. Stefan Mangold - ComNets Aachen University5 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!

7. Stefan Mangold - ComNets Aachen University6 Contention-based medium access: EDCF Different EDCF parameters per Access Category (AC) DIFS  AIFS[AC] CWmin  CWmin[AC] *) not in current draft standard 802.11e Medium Access: HCF CWmax  CWmax[AC] (PF=2  PF[AC]*)

8. Stefan Mangold - ComNets Aachen University7 Achievable Throughput Three different EDCF parameter sets AC (priority):highermedium(=legacy)lower AIFSN[AC]:229 CWmin[AC]:715 31 CWmax[AC]:102310231023 PF[AC]:24/1632/1640/16 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 Bianchi’s legacy 802.11 model)

9. Stefan Mangold - ComNets Aachen University8 512 byte frame body: 512 byte frame body, RTS/CTS: 2304 byte frame body: 2304 byte frame body, RTS/CTS: Legacy (Medium) Priority

10. Stefan Mangold - ComNets Aachen University9 512 byte frame body: 512 byte frame body, RTS/CTS: 2304 byte frame body: 2304 byte frame body, RTS/CTS: Low Priority (larger CWmin[AC])

11. Stefan Mangold - ComNets Aachen University10 512 byte frame body: 512 byte frame body, RTS/CTS: 2304 byte frame body: 2304 byte frame body, RTS/CTS: High Priority (smaller CWmin[AC])

12. Stefan Mangold - ComNets Aachen University11 Modified Bianchi Model

13. Stefan Mangold - ComNets Aachen University12 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

14. Stefan Mangold - ComNets Aachen University13 Access Probability per Slot

15. Stefan Mangold - ComNets Aachen University14 Approximation of Expected Idle Times Expected size of contention window N[AC] = number of backoff entities of AC tau[AC] = probability that a backoff entity is transmitting Access probability per slot Expressed by geometric distribution

16. Stefan Mangold - ComNets Aachen University15 CSMA Regeneration Cycle Process State transition diagram for the Markov chain States C, H, M, L represent busy system States 1, 2, 3..., CWmax+1 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

17. Stefan Mangold - ComNets Aachen University16 Markov Chain (1) Resulting state transition probabilities access: collision: idle:

18. Stefan Mangold - ComNets Aachen University17 Markov Chain (2) Resulting stationary distributions high: other:

19. Stefan Mangold - ComNets Aachen University18ResultResult The priority vector Share of capacity Modified Bianchi model provides the saturation throughput

20. Stefan Mangold - ComNets Aachen University19 Scenario & Results (1) Four backoff entities per AC (4/4/4) Variable, legacy and low priority Results of WARP2 simulation indicate accurate approximation

21. Stefan Mangold - ComNets Aachen University20 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

22. Stefan Mangold - ComNets Aachen University21 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

23. Stefan Mangold - ComNets Aachen University22 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!

24. Stefan Mangold - ComNets Aachen University23 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)

25. Stefan Mangold - ComNets Aachen University24 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:

26. Stefan Mangold - ComNets Aachen University25 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!

27. Stefan Mangold - ComNets Aachen University26 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

28. Stefan Mangold - ComNets Aachen University27 The Superframe as Single Stage Game Allocation process during a superframe: QoS:

29. Stefan Mangold - ComNets Aachen University28 Abstract Representation of QoS Throughput: normalized share of capacity Delay: normalized resource allocation interval Jitter: normalized delay variation,

30. Stefan Mangold - ComNets Aachen University29 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 The Player

31. Stefan Mangold - ComNets Aachen University30 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.

32. Stefan Mangold - ComNets Aachen University31 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: Markov Chain

33. Stefan Mangold - ComNets Aachen University32 Result and Evaluation Resulting observations for both players: Comparison with simulation results (YouShi):

34. Stefan Mangold - ComNets Aachen University33 The Utility Function Players attempt to meet their requirements Therefore, players attempt to maximize the observed payoff (outcome), by using a utility function

35. Stefan Mangold - ComNets Aachen University34 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 A i. There exists at least one Nash equilibrium, which can be calculated as: a=action, V=payoff, N=number of players (N=2)

36. Stefan Mangold - ComNets Aachen University35 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)

37. Stefan Mangold - ComNets Aachen University36 Bargaining Domain

38. Stefan Mangold - ComNets Aachen University37 Persist: demand=requirement Shown are YouShi simulation results and analytical apprx. Poor delay performance for pl.2 Strategy: Persist pl1pl2

39. Stefan Mangold - ComNets Aachen University38 Persist/Best Response/Cooperation

40. Stefan Mangold - ComNets Aachen University39 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: How to establish Cooperation

41. Stefan Mangold - ComNets Aachen University40 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

42. Stefan Mangold - ComNets Aachen University41 Dependence on Discounting Factor Future counts Future is less important

43. Stefan Mangold - ComNets Aachen University42 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!

44. Stefan Mangold - ComNets Aachen University43ConclusionsConclusions 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)

45. Backup Slides

46. Stefan Mangold - ComNets Aachen University45ArchitectureArchitecture Infrastructure Basic Service Set (BSS) one station is the access point Independent Basic Service Set (IBSS) ad-hoc

47. Stefan Mangold - ComNets Aachen University46 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

48. Stefan Mangold - ComNets Aachen University47 Multiple Backoff Entities per Station

49. Stefan Mangold - ComNets Aachen University48 Markov Chain State transition probabilities Stationary distributions

50. Stefan Mangold - ComNets Aachen University49 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. Stefan Mangold - ComNets Aachen University50 Best Response: adapt demand to achieve highest outcome (myopic competition) Action profile (demand) converges to NE Strategy: Best Response pl1pl2

52. Stefan Mangold - ComNets Aachen University51 Cooperation: reduced demand, shorter resource allocations Now both players achieve higher outcomes (next page…) Strategy: Cooperation pl1pl2