1 Exploiting Diversity in Wireless Networks Nitin H. Vaidya University of Illinois at Urbana-Champaign Presentation at Mesh Networking Summit Snoqualmie, WA, June 23-24, 2004

2 Capacity of Wireless Networks Limited by  Interference  Available spectrum Need to find ways to get most out of available spectrum

3 Diversity / Multiplicity / Heterogeneity  Diversity provides flexibility in using available resources  Can help improve performance

4 Diversity / Multiplicity / Heterogeneity Research Agenda  Abstractions that capture diversity  Protocols that exploit diversity

5 Diversity / Heterogeneity  Many dimensions:  Physical layer  Architecture  Upper layer

6 Channel Diversity

7  Multiple channels can help improve performance  Obvious approaches: Exploit diversity to choose channel with best gain Use multiple channels simultaneously to improve capacity  Developing practical protocols for the “obvious” approaches is still a challenge

8 Alternative Approach  Exploit protocol characteristics to benefit from the diversity  Examples: Pipelining Backup routes

9 Backoff Data / ACK RTS/CTS  Channel contention resolved using backoff (and optional RTS/CTS) IEEE

10 Backoff Data / ACK RTS/CTS Unproductive  Backoff keeps channel idle  unproductive  Most protocols have such idle contention periods Simple Observation

11 Data / ACK BackoffRTS/CTSBackoffRTS/CTS Backoff Data / ACK Pipelining Using Multiple Channels  Control Channel: Backoff and RTS/CTS  Data Channel: Data and ACK Stage 1 Stage 2

12 Pipelining works well only if pipeline stages are balanced ! Data / ACK BackoffRTS/CTSBackoffRTS/CTS Backoff Data / ACK Control Channel Data Channel

13 Solution: Partial Pipelining  Only partially resolve channel contention in the pipelined stage

14 Partial Pipelining  Stage 1: Narrow-Band Busy Tone Channel  Stage 2: Data channel Backoff phase 1 Data/ACK RTS/CTS Backoff phase 2 Data/ACK RTS/CTS Backoff phase 2 This slide contained an error in the set of slides used at the Mesh Networking Summit. The error has been corrected in this version.

15 Partial Pipelining  No packets transmitted on busy tone channel  Bandwidth can be small

16 Partial Pipelining  By migrating backoff to a narrow-band channel, cost of backoff is reduced Data Channel Bandwidth Busy Tone Channel Bandwidth Backoff Duration Area = cost of backoff

17 Moral of the Story  Looking beyond physical layer diversity exploitation schemes helps  Protocol characteristics can be exploited

18 Another Example

19 Multiple Interfaces  Consider devices equipped with both a and b a802.11b Higher max rateLower max rate Lower rangeHigher range

20 Channel Diversity  b “network”  denser than the a network  but provides lower rate Example approach:  Use a as primary network  Use b network to provide backup routes when a routes fail –The b network could be used for other things too

21 Protocol Interactions  For TCP, route failure more painful than a degradation in available capacity  The backup routes can avoid a route failure  Benefits of added capacity can be magnified by exploiting protocol behavior

22 Research Agenda  Develop practical protocols that can exploit diversity  Pay attention to protocol characteristics

23 Antenna Heterogeneity

24 Antenna Heterogeneity  “Fixed beam” antennas prevalent on mobile devices  Omnidirectional antennas (often with diversity)  Other antennas likely to become more prevalent  Switched, steered, adaptive, smart … –Can form narrow beamforms, which may be changed over time  Re-configurable antennas –Beamforms can be changed over time by reconfiguring the antenna, but not necessarily narrow beams

25 Antenna Heterogeneity  Beamforms: All antennas are not made equal  Timescale: Can beamforms be changed at packet timescales?

26 Protocol Design  Protocols designed for “fixed” beam antennas inadequate with “movable” beam antennas  State of the art MAC Protocols for specific antenna capabilities

27 Research Challenge How to design “antenna-adaptive” protocols ?  Need to develop suitable antenna abstractions that span a range of antenna designs  Forces us to think about essential characteristics of antennas –Example: Variability of beamforms a more fundamental property than directionality

28 Diversity / Heterogeneity  Many dimensions:  Physical layer  Architecture  Upper layer

29 Pure Ad Hoc Networks  No “infrastructure”  All communication over (one or more) wireless hops E A BC D X Z Ad hoc connectivity Y

30 Hybrid Networks  Infrastructure + Ad hoc connectivity E A BC D AP1AP2 X Z infrastructure Ad hoc connectivity Y

31 Hybrid Networks  Infrastructure may include wireless relays A C D AP1AP2 X Z infrastructure Ad hoc connectivity Y B R P R R

32 Hybrid Networks  Heterogeneity  Some hosts connected to a backbone, most are not  Access points/relays may have more processing capacity, energy A C D AP1AP2 X Z infrastructure Ad hoc connectivity Y B R P R

33 Heterogeneity Beneficial  Infrastructure provides a frame of reference –Provide location-aware services –Reduce route discovery overhead AP0AP1AP2AP3 A B D R2 R1 R3 A

34 Heterogeneity Beneficial  Reduce diameter of the network  Lower delay  Potentially greater per-flow throughput A C D AP1AP2 X Z infrastructure Ad hoc connectivity Y B R P R

35 Infrastructure Facilitates New Trade-Offs (hypothetical curves) User density distribution affects the trade-off Ad hoc-ness connectivity overhead Poor Man’s Ad Hoc Network

36 Research Issues  How to trade “complexity” with “performance” ? –Parameterize ad hoc-ness ?  Should the spectrum be divided between infrastructure and ad hoc components?  What functionality for relays / access points?

37 Misbehavior

38 Misbehavior  Misbehavior occurs with limited resources  Violating protocol specifications benefits misbehaving hosts  Example: Small backoffs in  higher throughput

39 Research Agenda  Protocols that maximize performance while discouraging/penalizing misbehavior  Challenge:  Wireless channel prone to temporal and spatial variations  Different players see different channel state  Impossible to detect misbehavior 100% reliably

40 Conclusions

41 Conclusions  Diversity/Heterogeneity natural to wireless networks  Need better abstractions to capture the diversity  Need protocols that can exploit available diversity  Need to be able to survive misbehavior

42 Other Research  Distributed algorithms for multi-hop wireless networks  Clock synchronization  Message ordering  Leader election  Mutual exclusion

43 Thanks! Advertisement: National Summit for Community Wireless Networks Urbana-Champaign, Illinois August 20-22,