1. 1 Multi-Channel Wireless Networks: Capacity and Protocols Nitin H. Vaidya University of Illinois at Urbana-Champaign Joint work with Pradeep Kyasanur Chandrakanth Chereddi Jungmin So Computer Communications Workshop 2005 © 2005

2. 2 Multi-hop Wireless Networks Mesh networks Ad hoc networks

3. 3 Wireless Capacity Wireless capacity limited In dense environments, performance suffers How to improve performance ?

4. 4 Improving Wireless Capacity Exploit physical resources Exploit diversity/multiplicity of resources Examples …

5. 5 Exploit Infrastructure Infrastructure provides a tunnel to forward packets E A BC D BS1BS2 X Z infrastructure Ad hoc connectivity

6. 6 Exploit Antennas Steered/switched directional antennas A D C B A B D C

7. 7 Improve Spatial Reuse Power/Rate/Carrier-Sense Control ABCD A BCD Transmit Spatial Power Rate reuse High High Low Low Low High

8. 8 Exploiting Diversity Exploiting diversity requires suitable protocols

9. 9 This Talk Utilizing multiple channels in wireless networks Capacity bounds Insights on protocol design Implementation issues

10. 10 Multiple Channels Available frequency spectrum often split into channels 26 MHz100 MHz200 MHz150 MHz 2.45 GHz 915 MHz 5.25 GHz 5.8 GHz 3 channels8 channels4 channels 802.11 in ISM Band

11. 11 Multiple Channels Common practice in multi-hop networks: Tune all interfaces to the same channel Channel 1

12. 12 Better capacity using multiple interfaces One interface per channel 1 1 c c 1 c Multiple Channels

13. 13 Multiple Channels with Interface Constraint What if interfaces (m) < channels (c) ? 1 1 c = m m = c 1 c 1 m m BaselineOur system

14. 14 This Talk Utilizing multiple channels in wireless networks Capacity bounds Insights on protocol design Implementation issues

15. 15 Capacity = ? [Gupta-Kumar] Random source-destination pairs among randomly positioned n hosts in unit area, with n

16. 16 Capacity = ? = minimum flow throughput Capacity = n

17. 17 Capacity Constraints Capacity constrained by available spectrum bandwidth Other factors further constrain wireless network capacity …

18. 18 Connectivity Constraint [Gupta-Kumar] Need routes between source-destination pairs Places a lower bound on transmit range Not connectedConnected A D A D

19. 19 Interference Constraint [Gupta-Kumar] Interference among simultaneous transmissions Limits spatial reuse is a Guard parameter d A B (1+ )d D C

20. 20 Capacity of Wireless Networks [Gupta-Kumar] Bit rate for each transmission = W Capacity increases with n as

21. 21 Capacity of Wireless Networks [Gupta-Kumar] Result holds when m = c 1 1 1 1 c m = c W/c W

22. 22 Capacity of Wireless Networks What if fewer interfaces ? Additional constraints on capacity become relevant

23. 23 Interface Constraint Throughput is limited by number of interfaces in a neighborhood Interfaces, a resource k nodes in the neighborhood total throughput k * m * W/c

24. 24 Destination Bottleneck Constraint Per-flow throughput limited by total number of flows at a host D f incoming flows If node throughput = T Per-flow throughput = T / f

25. 25 Random network – Region 1 Capacity constrained by connectivity + interference No dependence on m and c

26. 26 Random network – Region 2 Capacity constrained by interfaces + interference

27. 27 Random network – Region 3 Capacity constrained by destination bottleneck

28. 28 This Talk Utilizing multiple channels in wireless networks Capacity bounds Insights on protocol design Implementation issues

29. 29 Insights from Capacity Analysis (1) Static channel allocation does not yield optimal performance in general Must dynamically switch channels Need protocol mechanisms for channel switching A C B Channel 1 2 D 3

30. 30 Insights from Capacity Analysis (2) Optimal transmission range function of density of nodes and number of channels Goal: # of interfering nodes = # of channels

31. 31 Insights from Capacity Analysis (3) Routes must be distributed within a neighborhood This is not necessary in single channel networks A B C D E F A B C D E F Multi-Channel (m<c) Optimal strategy Single Channel (m=c=1) Optimal strategy

32. 32 Insights from Capacity Analysis (4) Channel switching delay potentially detrimental, but may be hidden with careful scheduling, or additional interfaces

33. 33 Example Configuration IEEE 802.11a/b devices 2 interfaces per host Soekris box

34. 34 This Talk Utilizing multiple channels in wireless networks Capacity bounds Insights on protocol design Implementation issues

35. 35 Which Layers to be Multi-Channel Aware? Practical decision: Above MAC layer Allows use of unmodified 802.11

36. 36 Separation of Responsibility Interface management: Shorter timescales Dynamic channel assignment to interfaces Interface switching Routing: Longer timescales Multi-channel aware route selection metrics Link Network Transport Physical Layer Upper layers 802.11

37. 37 Channel Assignment 2 interfaces much better than 1 Hybrid channel assignment: Static + Dynamic A Fixed (ch 1) Switchable B Fixed (ch 2) Switchable C Fixed (ch 3) Switchable 12 32

38. 38 Selecting Channel Diverse Routes Most routing protocols use shortest-hop metric Not sufficient with multi-channel networks Need to exploit channel diversity A B C D 1 1 21 Route A-C-D is better Select routes with greater channel diversity

39. 39 Impact of Switching Cost Interface switching cost has to be considered A node may be on different routes, requiring switching A B C D 21 2 1 Route A-B-D is better E 3 Prefer routes that do not require excessive switching

40. 40 Other Issues Routing table entries need to store interface and channel identifiers Packet buffering pending channel switch Multi-channel broadcast

41. 41 Testbed Status Interface and channel abstraction layer implemented Can run legacy routing protocol above this Multi-channel routing implementation in progress 20+ node testbed to be deployed later in Fall 2005

42. 42 Conclusion Capacity results hint at significant performance benefits using many channels with few interfaces Need suitable protocols to exploit the channels

43. 43 Thanks! www.crhc.uiuc.edu / wireless