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 ATT Labs Fellowship
• Advisors H. V. Poor, S. Schwartz,
• L. J. Greenstein (WINLAB)
• November 25, 2002

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• 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.

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? (Contd)

• 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
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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 users 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.

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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
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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.

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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.

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• 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 (DAPs)

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Summary of Thesis (Contd)

• 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

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Two-Cell System Uplink and Downlink in Ideal
Conditions
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• 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)

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

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Capacity Contours for Single-Macrocell/Single-Micr
ocell System
Number of Microcell Users
Exact Analysis
Simulation
Approximation
Number of Macrocell Users
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Multicell System Under Ideal Conditions
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• 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.
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Mutlicell Systems Key Results (Contd)

• Derived a simple and reliable approximation for
  NTm

• Similar analysis yields reliable approximation
  for NTM.

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Single-Macrocell/Multiple-Microcell System
Simulation Results, ? s error bar
Linear Approximation
Total Average Number of Users, 95 Feasibility
L, Number of Microcells
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9-Macrocell/Multiple-Microcell System
Simulation Results, ? s error bar
Linear Approximation
Total Average Number of Users, 95 Feasibility
L, Number of Microcells
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Other Issues in Ideal Two-Cell Systems Soft-Hand
off, Voice Activity Detection, Propagation
Parameter Sensitivity, and Microcells as DAPs
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Other Issues in Two-Cell Systems Key Results

• Effect of Soft-Handoff Both base stations
  receive each
• users 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.

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Other Issues in Two-Cell Systems Key Results
(Contd)

• 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

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Microcells as Data 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 DAPs Infostations, Dedicated
Short-Range Communications (DSRC), and
Intelligent Transportation Systems (ITS)
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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.
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Normalized Average Throughput (E t / W ) Versus
d
Normalized Average Throughput
d, Desensitivity
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Uplink Capacity and Coverage Max Power
Constraints and Variable Power Fading
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• 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

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• 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 gt Pmax.
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Capacity in System with Max Power Constraints
N, Total Number of Users, 5 Outage
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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

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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 lt
  Lp. For example,
• DFRA 1.6, DFHT 3.3, and DFTU 4.0.

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• 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 POutage does not
  exceed g.
• for the three standard environments, i.e., RA,
  TU, and HT,
• as functions of F.
• for any environment when F gtgt F (unlimited
  terminal
• power).

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Variable Power Fading Key Results

• Uplink capacity constant for RA, HT, and TU
  environments when
• F lt 0.1 and decreases sharply in F when F lt 0.1.
• Capacity reduces by as much as 15 for the RA
  environment.
• When F gtgt F, user capacity in uniform
  multipath channel can be approximated as

, for Lp gt 1.

• Showed uplink capacity is the same for channels
  with the same
• DF.

Replace Lp in with DF
DF
Napprox
Non-Uniform Delay Profile
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Obtaining NT for RA, HT, and TU Channels via the
Uniform Channel
RA
HT
TU
Uplink Capacity using Simulation
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36
37
Uplink Capacity using Approximation (via Uniform
Channel)
37.1429
32.5
35.86
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Downlink Capacity Channel Dispersion and Effect
of Alternate Power Control
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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.

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• 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

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• 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

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• 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-microcel
  ls, 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.

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• 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.