Capacity and Coverage in Two-Tier CDMA Cellular Networks

1. Capacity and Coverage in Two-Tier CDMA Cellular Networks Shalinee Kishore Department of Electrical Engineering Princeton University Supported by: AT&T Labs Fellowship Advisors: H. V. Poor, S. Schwartz, L. J. Greenstein (WINLAB) November 25, 2002

2. Microcell Macrocell • Two-Tier System:Macrocells and Microcells • Macrocells - cells in the traditional cellular system • Cell radii are 1 to 10 km. • Base stations are costly, antenna tower heights  30 m. • Microcells - smaller cells embedded within macrocells • Cell radii are less than 1 km. • Base stations are compact, low-cost, at heights of ~10 m.

3. Why Microcells? An Example Desired Coverage High Density of Users Actual Coverage Due to high-user-density regions, actual performance of macrocell falls short of desired performance.

4. Why Microcells? (Cont’d) • Other Reasons: Users can be separated based on • mobility • desired data rates Fast moving users  Macrocell Slow moving users  Microcell Voice users  Macrocell Data users  Microcell

5. Microcells in Single-Frequency Code Division Multiple Access (CDMA) Systems • CDMA is employed in current cellular phones in US and is • standard for third generation systems worldwide. • CDMA uplink (user-to-base): users assigned random codes. • Every user’s signal interferes with signals from every other user. • In single-tier systems (macrocells only), there is in-cell and out-of-cell • interference. • CDMA downlink (base-to-user): base station uses orthogonal • codes to transmit to all in-cell users. • In single-tier systems, there is ideally only out-of-cell interference. • Dispersive wireless channels cause loss-of-orthogonality, leading to • in-cell interference. • In both the uplink and downlink of two-tier systems, there is • additionally cross-tier interference.

6. Two Classes of CDMA Microcells Hotspots:* Small cells Clusters/Overlay: Small embedded inside a larger cells that tesselate and span macrocell to provide almost all of macrocell coverage in small region coverage area. No handoff with high user/traffic between tiers. density or poor coverage. Handoff between tiers. - Single-frequency (near-far problem) - Dual-frequency (spectral efficiency issues) * Focus of our research

7. Previous Work on CDMA Microcells • Hotspots • Shapira, “Microcell Engineering in CDMA Cellular Networks,” IEEE Transactions on • Vehicular Technology, 1994. • Gaytan and Rodriguez, “Analysis of Capacity Gain and BER Performance for CDMA • Systems with Desensitized Embedded Microcells,” ICUPC, 1998. • Wu, et al., “Performance Study for a Microcell Hot Spot Embedded in CDMA Macrocell • Systems,” IEEE Transactions on Vehicular Technology, 1999. • Overlays • I, et al., “A Microcell/Macrocell Cellular Architecture for Low- and High-Mobility Wireless • Users,” IEEE Journal on Selected Areas in Communications, Vol. 11, Issue 6, Aug. 1993. • Hamalainen, et al., “Performance of CDMA Based Hierarchical Cell Structure Network,” • IEEE TENCON, 1999. • Ghaleb, et al. “Tiered Services/Private System Support for CDMA Systems,” VTC, 1999.

8. Research Goals • Expand understanding of Macrocell/Microcell architectures in CDMA networks. • Develop new methods of analysis for evaluating such • systems. • Evaluate impact of propagation, user distribution, • channel fading, maximum transmit power constraints, • and dispersion on uplink and downlink capacity and • coverage area. • Devise techniques, tradeoffs, and engineering rules for • performance improvement and system deployment.

9. No variable fading of user signal powers Uplink: no transmit power constraint Downlink: no in-cell interference • Summary of Thesis • Ideal Conditions: • - Single-Macrocell/Single-Microcell (Two-Cell) System • - Multiple-Macrocell/Multiple-Microcell (Multi-Cell) System • - Other Issues in Two-Cell Systems • Effect of soft-handoff • Effect of voice activity detection • Effect of propagation parameters • 4) Microcells as Data Access Points (DAP’s)

10. Summary of Thesis (Cont’d) • Non-Ideal Conditions: • Uplink Capacity and Coverage • 1) Effect of transmit power constraints • 2) Effect of received power fading • Downlink Capacity: No Multiuser Detectors • 1) Effect of Channel Dispersion • 2) Alternative methods of power control

11. Two-Cell System: Uplink and Downlink in Ideal Conditions

12. Uplink Capacity of Two-Cell System: Problem Statement • Given: • CDMA system with single macrocell and single microcell • Matched filter receiver and SINR-based power control • Probability density of user location over coverage region • Processing gain (W/R) and desired SINR (G ) • Propagation characteristics, including shadow fading • Criterion for base station selection (e.g., strongest path gain, • minimum required transmit power) • Hard-handoff: each user communicates with only one base • Determine: • Uplink user capacity (number of simultaneous voice users)

13. Feasibility In order to meet SINR requirements for macrocell and microcell users, (Feasibility) where (single-cell pole capacity) Cross-Tier Interference Terms Tij = Transmission gain from base i to user j, d = desensitivity

14. Transmission Gain (Path Gain) Model T = Transmission Gain d = Distance Between User and Base b = Breakpoint Distance of Median Path Gain H = Proportionality Constant, Accounts for Antenna Gains and Wavelength c = Lognormal Shadow Fading

15. Finding the CDF for one term of IM: Let TMj/Tmj = vM Exact analysis is doable but extremely complicated.

16. Simpler Analysis: Mean Approximation • Since IM and Im are sums, they converge fairly tightly to • their means. • Instead of computing distribution of and , we • compute their mean values • Obtain the following requirement on NM and Nm:

17. Capacity Contours for Single-Macrocell/Single-Microcell System Number of Microcell Users Exact Analysis Simulation Approximation Number of Macrocell Users

18. Multicell System: Under Ideal Conditions

19. Multicell Systems: Key Results • Showed total user capacity is maximum when there are an • equal number of users served by each cell. • Showed total user capacity is approximately linear in L and • M (number of macrocell bases) for L small. Specifically, and can be calculated using two-cell techniques.

20. Mutlicell Systems: Key Results (Cont’d) • Derived a simple and reliable approximation for NTm: • Similar analysis yields reliable approximation for NTM.

21. Single-Macrocell/Multiple-Microcell System Simulation Results,  s error bar Linear Approximation Total Average Number of Users, 95% Feasibility L, Number of Microcells

22. 9-Macrocell/Multiple-Microcell System Simulation Results,  s error bar Linear Approximation Total Average Number of Users, 95% Feasibility L, Number of Microcells

23. Other Issues in Ideal Two-Cell Systems: Soft-Handoff, Voice Activity Detection, Propagation Parameter Sensitivity, and Microcells as DAPs

24. Other Issues in Two-Cell Systems: Key Results • Effect of Soft-Handoff: Both base stations receive each • user’s signal; two signals added • using maximal ratio combining. • - Developed analytical methods to approximate user • capacity under soft-handoff. • - Showed user capacity increases by at most 20% over • hard-handoff.

25. Other Issues in Two-Cell Systems: Key Results (Cont’d) • Effect of Voice Activity Factor: Let a be the fraction of time voice users speak.Under voice activity detection, mean approximation contour is modified as: • Sensitivity to Propagation Parameters: Fairly insensitive

26. Microcells asData Access Points DAP: Base station with limited coverage that provides high-speed data access to users one-at-a-time. Email, voice mail, and fax to the pedestrian Downloading a map to a passing car Low bit-rate cellular coverage High bit-rate DAP coverage Examples of DAP’s: Infostations, Dedicated Short-Range Communications (DSRC), and Intelligent Transportation Systems (ITS)

27. Problem Statement Recall: Microcell coverage shrinks as desensitivity (d ) reduces. Question: What happens when and microcell coverage area shrinks to that of a DAP? Determine: Per-user throughput, tu , and total DAP throughput, t , as functions of d.

28. Normalized Average Throughput (E[ t / W ]) Versus d Normalized Average Throughput d,Desensitivity

29. Uplink Capacity and Coverage: Max Power Constraints and Variable Power Fading

30. Maximum Power Constraints:Problem Statement • Given: • A Single-Macrocell/Single-Microcell System • User distribution • Propagation model • Pmax = Maximum transmit power level for any user • dmax = Maximum distance over which users are distributed • hW = Noise power • Determine: • Uplink user capacity as a function of Pmax and dmax

31. Maximum Power Constraints: Key Results • Defined P [Outage] as • Presented uplink user capacity for given level of outage as • a function of a single, dimensionless parameter F, where P [Outage] = (1-P [Feasibility]) + P [Feasibility] ·P [Transmit Power > Pmax].

32. Capacity in System with Max Power Constraints N, Total Number of Users, 5% Outage

33. Variable Power Fading: Background • Thus far: considered infinitely-dispersive uplink channel  • user signal has constant output power after RAKE processing. • Actual channels have finite number of paths with variation • about mean path power  user signal has variable fading. • Can model fading with modified transmission gain: • Tij’ =kTij, k is a unit-mean random variable. • Examine performance for four scenarios: • Rural Area (RA) environment • Typical Urban (TU) environment • Hilly Terrain (HT) environment • Uniform multipath channel

34. Uniform Multipath Channel Channel Delay Profile power Height of each path is mean square value of a Rayleigh random-variable. delay Lp Number of Paths • Diversity Factor (DF) measures the amount of multipath • diversity in channel. Computable for any delay profile. • Uniform channel has DF = Lp. • Non-uniform channels with Lp paths have DF < Lp. For example, • DFRA= 1.6, DFHT= 3.3, and DFTU = 4.0.

35. Variable Power Fading: Problem Statement • Given: • Single-macrocell/single-microcell system • Propagation model with variable fading • Pmax = Maximum transmit power level • dmax = Maximum distance over which users are distributed • hW = Noise power • Determine: • Uplink user capacity so that P[Outage] does not exceed g. • for the three standard environments, i.e., RA, TU, and HT, • as functions of F. • for any environment when F >> F* (unlimited terminal • power).

36. Variable Power Fading: Key Results • Uplink capacity constant for RA, HT, and TU environments when • F < 0.1 and decreases sharply in F when F < 0.1. • Capacity reduces by as much as 15% for the RA environment. • When F >> F*, user capacity in uniform multipath channel can be approximated as: , for Lp > 1. • Showed uplink capacity is the same for channels with the same • DF. Replace Lp in with DF DF Napprox Non-Uniform Delay Profile

37. Obtaining NT for RA, HT, and TU Channels via the Uniform Channel RA HT TU Uplink Capacity using Simulation 36 37 33 Uplink Capacity using Approximation (via Uniform Channel) 37.1429 32.5 35.86

38. Downlink Capacity: Channel Dispersion and Effect of Alternate Power Control

39. Downlink Capacity: Background • CDMA downlink: Base stations transmit orthogonal • signals to users. • Channel dispersion causes loss of orthogonality at user • terminals. • Orthogonality factor, b, captures loss-of-orthogonality of • user signals in a channel. b [0,1], where b= 0 when no • dispersion in channel and b= 1 when infinite dispersion. • b can be computed from channel delay profile. • Thus far: assumed b = 1 (infinite dispersion) but ideal • multiuser detectors removed all in-cell interference.

40. Downlink Capacity: Problem Statement • Given: • Single-macrocell/single-microcell system • Channel delay profile, i.e., orthogonality factor, b. • Conventional receivers at user terminals • Base station k transmits total power PTk, k { M,m } • Macrocell user i assigned fraction xi of PTM • Microcell user j assigned fraction yj of PTm • Downlink power control scheme for allocating xi and yj • Determine: • Downlink user capacity, number of simultaneous voice • users

41. Downlink Capacity: Key Results • Recast uplink capacity, NT, as a function of b. • Capacity of any channel ( b) approximated using • capacity of uniform channel. • For two of three power control strategies studied (uniform and slow), overall capacity dominated by uplink for all b. • Under fast power control, user capacity can be • approximated (by relating b to bu) as: • Fast power control leads to downlink capacity that is • higher than uplink.

42. Conclusion • Analytical methods developed for estimating attainable • uplink user capacity in two-tier CDMA systems. • Analysis done in progression from single-macrocell/single- • microcell, to single-macrocell/multiple-microcells, to • multiple-macrocells/multiple-microcells. • Results general with respect to system and propagation • parameters and accurate, as confirmed via simulation. • Analysis extended to DAP, showing how microcells can • be modified to support high speed data.

43. Computed effect of soft-handoff and voice activity detection on uplink user capacity. • Quantified effect of maximum power constraints on coverage area and capacity. • Used the uniform multipath channel to approximate the uplink user capacity and downlink user capacity under fast power control for finitely-dispersive channels. • Demonstrated the importance of fast downlink power control in two-tier CDMA systems.