Cell Design to Maximize Capacity in CDMA Networks. Robert Akl, D.Sc.

Transcription

1 Cell Design to Maximize Capacity in CDMA Networks Robert Akl, D.Sc.

2 Outline CDMA inter-cell effects Capacity region Base station location Pilot-signal power Transmission power of the mobiles Maximize network capacity Mobility Call admission control algorithm Network performance

3 CDMA Capacity Issues Depends on inter-cell interference and intra-cell interference Complete frequency reuse Soft Handoff Power Control Sectorization Voice activity detection Graceful degradation

4 Relative Average Inter-Cell Interference I ji m is the path loss exponent. ζ is the decibel attenuation i E ω due to shadowing, and has zero mean and standard deviation j χ 2 i ζ i m ζ j 10 r j ( x,y)10 E m 2 r C i ( x,y) /χi 10 n j Area( C j ζ j i ) 10 ω jda( x,y) σ s.

5 Soft Handoff User is permitted to be in soft handoff to its two nearest cells.

6 Soft Handoff (c) region (c) region (b) region (a) region ) ( E 10 ) ( E 10 ) ( E 10 ) ( E 10 x,y ωda r r χ r r I x,y ωda r r χ r r I x,y ωda r r χ r r I x,y ωda r r χ r r I j k k k j j i k k i j j ζ m j ζ m k i ζ m i m k ki ζ m k ζ m j i ζ m i m j ji ζ m i ζ m k i ζ m i m k ki ζ m i ζ m j i ζ m i m j ji

7 Inter-Cell Interference Factor κ n ji j per user inter - cell interference factor from cell j to cell i. users in cell j producea relative average interference in cell i equal to n j κ ji.

8 Capacity Region

9 Network Capacity Transmission power of mobiles Pilot-signal power Base station location

10 Power Compensation Factor Fine tune the nominal transmission power of the mobiles PCF defined for each cell PCF is a design tool to maximize the capacity of the entire network

11 Power Compensation Factor (PCF) Interference is linear in PCF Find the sensitivity of the network capacity w.r.t. the PCF

12 Sensitivity w.r.t. pilot-signal power Increasing the pilot-signal power of one cell: Increases intra-cell interference and decreases inter-cell interference in that cell Opposite effect takes place in adjacent cells

13 Sensitivity w.r.t. Location Moving a cell away from neighbor A and closer to neighbor B: Inter-cell interference from neighbor A increases Inter-cell interference from neighbor B decreases

14 Optimization using PCF

15 Optimization using Location

16 Optimization using Pilot-signal Power max T subject to M i1 n i n i, (network capacity) M j1 n β κ for i 1,..., M. j j ji ( C β i j, L i ) c ( i) eff 0,

17 Combined Optimization

18 Twenty-seven Cell CDMA Network Uniform user distribution profile. Network capacity equals 559 simultaneous users. Uniform placement is optimal for uniform user distribution.

19 Three Hot Spots All three hot spots have a relative user density of 5 per grid point. Network capacity decreases to 536. Capacity in cells 4, 15, and 19, decreases from 18 to 3, 17 to 1, and 17 to 9.

20 Optimization using PCF Network capacity increases to 555. Capacity in cells 4, 15, and 19, increases from 3 to 12, 1 to 9, and 9 to 14. Smallest cellcapacity is 9.

21 Optimization using Pilot-signal Power Network capacity increases to 546. Capacity in cells 4, 15, and 19, increases from 3 to 11, 1 to 9, and 9 to 16. Smallest cellcapacity is 9.

22 Optimization using Location Network capacity increases to 549. Capacity in cells 4, 15, and 19, increases from 3 to 14, 1 to 8, and 9 to 17. Smallest cellcapacity is 8.

23 Combined Optimization Network capacity increases to 565. Capacity in cells 4, 15, and 19, increases from 3 to 16, 1 to 13, and 9 to 16. Smallest cellcapacity is 13.

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25 Combined Optimization (m.c.)

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28 Call Admission Control Fix cell design parameters Design a call admission control algorithm Guarantees quality of service requirements Good blocking probability

29 Our Model New call arrival process to cell i is Poisson. Total offered traffic to cell i is:

30 Handoff Rate

31 Blocking Probability

32 Fixed Point

33 Net Revenue H Revenue generated by accepting a new call Cost of a forced termination due to handoff failure Finding the derivative of H w.r.t. the arrival rate and w.r.t. N is difficult.

34 Maximization of Net Revenue

35 3 Mobility Cases No mobility q ii = 0.3 and q i = 0.7 Low Mobility A i q ij q ii q i High Mobility A i q ij q ii q i

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42 Maximization of Throughput

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51 Conclusions Solved cell design problem. Formed general principles on cell design. Designed a call admission control algorithm. Calculated upper bounds on throughput for a given network topology and traffic distribution profile.