iCAR : an Integrated Cellular and Ad-hoc Relaying System *

1. iCAR : an Integrated Cellular and Ad-hoc Relaying System * Hongyi Wu Advisor: Dr. Chunming Qiao LANDER, SUNY at Buffalo This project is supported by NSF under the contract ANIR-ITR 0082916 and Nokia.

2. Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

3. Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

4. What is a cellular system? • The problem of scarce frequency resource • Based on subdivision of geographical area • One Base Transceiver Station (BTS) in each cell. • Frequency is reused in cells far away.

5. A MH can only access the channels in one cell (except soft-handoff). Unbalanced traffic among cells Variable locations of the Hot Spots (congested cells) Cell-splitting not flexible nor cost-effective enough Tremendous growth of wireless data/voice traffic Limited capacity Problems in Cellular Systems

6. What is Mobile Ad hoc Network (MANET)? • An autonomous system of mobile nodes connected by wireless links. • The nodes are routers. • The nodes are organized in a arbitrary graph. • The nodes are free to move.

7. Objectives of Our Work • Balance traffic among cells • Decrease call blocking and dropping probability • Increase system’s capacity cost-effectively • Support heterogeneous networks • Provide service for shadow area • Reduce mobile host’s (MH) transmission power and/or increase transmission rate

8. Outline • Motivations • Introduction of iCAR • iCAR Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

9. Basic Idea : Integration of Cellular and Ad-hoc Relaying Technologies • ARS : Ad-hoc Relaying Stations • Each ARS and MH has two interfaces (celluar and relay) ARS MH

10. One example of relaying • MH X moving into congested Cell B is relayed to Cell A x A B A B x (a) (b)

11. An ARS differs from a BTS and a MH • Compared to BTS • Mobility • Air interface • Compared to MH • Mobility • Security,authentication,privacy • Billing

12. Basic Operations • Primary Relay : a strategy that establishs a relaying route between a MH (in congested cell) to a nearby non-congested cell. • Failed Hand-off • Blocked new call • MH switches over from C-interface to R-interface A B x

13. Basic Operations (Cont’d) • Secondary Relay • Primary relay failed • Not covered by ARS • Reachable BTS is congested too • Free the channel of an active call which can be relayed to a neighbor cell x A B y (a) x A B y (b)

14. Basic Operations (Cont’d) • Cascaded Relay • Cascade the above relays more multiple times if they are failed. x x A B A B y y z z C C

15. CI and NCI • Congestion-Induced (CI) Relaying • Reduce call blocking or dropping probability when congestion occures. • Noncongestion-Induced (NCI) Relaying • Pro-actively balance load • Shadowing Area • Uncovered Area • Transmission Power

16. Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

17. Full Coverage • The maximum number of relay stations needed so as to ensure that a relaying route can be established between any BTS and an MH located any where in the cell 2 Km 1.5 Km 1 Km 200m 50 200 114 18 350m 66 38 500m 8 18 32

18. Seed Growing Approach • With fewer ARS’s, relaying can still be effective. Some can be seeds (placed at each pair of shared edges), and others can grow from them (placed nearby).

19. Number of Seed ARSs • For a fix coverage area, the system with fewer UN-SHARED edges needs more seed ARSs. • The max number is obtained by considering a circle area and count the number of shared edges. Proposition: For a n-cell system, the maximum number of seed ARS’s is

20. Quality of Coverage • The quality of ARS coverage (Q) is defined to be the relay-able traffic in an iCAR system. • The Q value depends on the traffic intensity, the cell size, the ARS size, the system topology, etc. • The higher the Q value, the better the ARS placement • The Q value is not always proportional to the ARS coverage.

21. Seed ARS’s Placement B • Two approaches to place the seed ARS • Edge (ARS No.1) • S: ARS ceverage; • TA, TB: Traffic intensity of cell A and B. • bA,bB: Blocking probability of cell A and B. B B A 2 2' 1 B B 1' B Seed ARS’s 3 3' … Half of S covers cell A, but only unblocked part (1-bB) of them is relay-able

22. Seed ARS’s Placement B • Vertex (ARS No.1') B B A 2 2' 1 B B 1' B Two third of S covers cell B. .. One third of S covers cell A. Note that, the Blocking probability is bB2 because the call may Be relayed to two cells. Seed ARS’s 3 3'

23. Seed ARS’s: Edge v.s. Vertex • Preliminary results • Case1 : when TB<TA<50 Erlangs, Qvertex<QEdger. • Case2 : when TA, TB>50 Erlangs or TA<TB, QVertex>QEdge. • Case2 is out of normal operation range • Rule of Thumb 1 • Place the seed ARS's at edges of a hot spot cell.

24. Seed ARS v.s. Grown ARS • Preliminary Results • Case1 : seed (ARS 2). Assuming edge placement of seed) • Case2 : grow (ARS 2’). The QoC value of the grown ARS is about 0.61•S •TA•(1-bB). • Rule of Thumb 2 • Try to place an ARS as a seed if it is possible.

25. Growing Direction • When there are already sufficient seed ARS’s, • Additional ARS's can grow • toward inside of a hot cell A (ARS No.3) • toward outside of cell A (ARS No.3') • Rule of Thumb 3 • Place an ARS in the cell with a higher traffic intensity.

26. Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

27. Theorems • Theorems1 Assume that the total traffic in a n-cell system is T Erlangs, then the (system wide) call blocking probability is mininized when the traffic in each cell is T/n Erlangs. Why? Assume there are M channels in each cell, and the traffic intensity in cell i is Ti ( ). According to Erlang B formula, the blocking probability in each cell is

28. Theorem (Cont’d) The average blocking probability of entire system is In order to compute the minimum value of B, we derive the partial differentiation, Solve a group of equations, we can get the critical points,

29. Theorems (Cont’d) • Theorem2 For a given total traffic in a system, and a fixed number of data channels, an idea iCAR system has a lower blocking probability than any conventional cellular system (including a perfectly load-balanced one). Why? An idea iCAR system can relay traffic from one cell to any other cells. So, it can be treated as a SUPER cell with nT traffic and nM channels. The blocking probability of the super cell is We can prove that it is lower than B(M,T).

30. Analysis based on multi-dimensional Markov chains • Consider a system with only seed ARS’s

31. Analysis (Cont’d) • For primary relaying • An approximate model (considering cell X in figure (b)) • To simplify the analysis, we assume that the blocking probability of the neighboring cells of X is fixed, i.e. the traffic relayed to cell Bs won’t change their blocking probability. This assumption will be nullified in the accurate analysis model.

32. Analysis (Cont’d) • For primary relaying • An approximate model • State diagram • Final result

33. Analysis (Cont’d) • For primary relaying

34. Analysis (Cont’d) • An accurate model of primary relaying for a 2-cell system.

35. Analysis (Cont’d) • Secondary relaying • An approximate model

36. Analysis (Cont’d) • An accurate model

37. Simulations • Simulation model • GloMoSim • 25 cells • Cell A is a hot spot • Location dependent traffic (ripple effect) • 50 DCH’s per cell • 56 seed ARS’s • 25,600 MH’s • Call arrive rate is in poisson distribution • Holding time is in exponential

38. Simulations (cont’d) • Results • Blocking rate • Blocking rate can be reduced by primary relaying, but not much • Secondary relaying reduces the call blocking rate further

39. Simulations (Cont’d) • More results Throughput Call Dropping Rate

40. Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Theorems • Analysis • Simulations • Signaling Protocols • Future Work and Conclusion

41. Signaling and routing protocols for QoS traffic • Why do we need signaling and routing protocols? For iCAR to support real-time IP-based applications in wireless mobile environment, set up bandwidth guaranteed relaying path. • Candidates of protocols for iCAR

42. Protocol 1: a PSC-assisted protocol • Primary relaying

43. Protocol 1 (cont’d) • Secondary relaying

44. Protocol 2: a link-state based protocol • Primary relaying

45. Protocol 2 (Cont’d) • Secondary relaying

46. Protocol 3: an aggressive route-searching protocol • Primary relaying

47. Protocol 3 (cont’d) • Secondary relaying

48. Performance Comparison • Three protocols have their own advantages and disadvantages • The PSC-assisted protocol will have the lowest signaling overhead in terms of the number of signaling messages. But in this protocol, PSC becomes the performance bottle neck and a signal point of failure.

49. Performance Comparison (Cont’d) • The link-state based protocol is distributed. It requires the ARSs to flood the update messages. Also, the ARSs need large enough memory to maintain topology and bandwidth information, and high computation power to compute the relaying route. • The aggressive route searching protocol does not maintain the relaying bandwidth information of other ARSs. It is an on-demand and the simplest distributed protocol. It requires fewest memory and computing power.

50. Simulation • We evaluate the performance of the proposed signaling protocols in terms of request rejection rate and signaling overhead via simulations. • Seven cells, 30~60 ARSs and 1600 MHs were simulated in the model we discussed before.