2 tier cell ppt
DESCRIPTION
Capacity and Coverage in Two-Tier CDMA Cellular NetworksTRANSCRIPT
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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
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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.
• Base stations are compact, low-cost, at heights of ~10 m.
MacrocellMicrocell
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Desired Coverage
Why Microcells? An Example
High Density of Users
Actual Coverage
Due to high-user-density regions, actual performance of macrocell falls short of desired performance.
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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
Why Microcells? (Cont’d)
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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 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.
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Two Classes of CDMA Microcells
Hotspots:* Small cells Clusters/Overlay: Small embedded inside a larger cells that tesselate and spanmacrocell to provide almost all of macrocellcoverage in small region coverage area. No handoffwith 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 WirelessUsers,” 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.
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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.
Research Goals
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Summary of Thesis
• Ideal Conditions:
No variable fading of user signal powersUplink: no transmit power constraintDownlink: no in-cell interference
- Single-Macrocell/Single-Microcell (Two-Cell) System
- Multiple-Macrocell/Multiple-Microcell (Multi-Cell) System
- Other Issues in Two-Cell Systems
1) Effect of soft-handoff 2) Effect of voice activity detection3) Effect of propagation parameters4) Microcells as Data Access Points (DAP’s)
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• 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
Summary of Thesis (Cont’d)
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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 () • 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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In order to meet SINR requirements for macrocell and microcell users,
where
IINKNK MM ))((
MNN
1
1
Mj
j
Mj Mj
j
j
Mj
j j
MjM
T
TMj
T
TI
T
Tj
T
TI
RWK
Cross-TierInterference
Terms
Feasibility
(single-cell pole capacity)
(Feasibility)
Tij = Transmission gain from base i to user j, = desensitivity
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Transmission Gain (Path Gain) Model
bd
dbH
bddbH
T
,
,
4
2
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
= Lognormal Shadow Fading
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),( locations over Users ofDensity ),(where
),(41,
2
),(41,
2),(),(
where
),(],|[
222
222
)),min(,max(
)),max(,min(
1
maxmax2
2
max
2max
yxyxf
wzDgD
hhwDzf
wzDgD
hhwDzf
wzgwzf
dwdzwzfRvvP
XY
MXY
MXY
ZW
wvzb
b
w
vzbw
ZWM
M
M
Finding the CDF for one term of IM: Let TMj/Tj = vM
Exact analysis is doable but extremely complicated.
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Simpler Analysis: Mean Approximation
• Instead of computing distribution of and , we compute their mean values
•
• Obtain the following requirement on NM and N:
MI I
vNvENIEvNvENIE MMMMM ][][ and ][][
)1()(
vvNK
NKKN
MM
M
• Since IM and I are sums, they converge fairly tightly to their means.
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Capacity Contours for Single-Macrocell/Single-Microcell System
Number of Macrocell Users
Nu
mb
er o
f M
icro
cell
Use
rs
Exact Analysis
Simulation
Approximation
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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,
LKNMKNKMLN TTM )()(),(
TMN and can be calculated using two-cell techniques.TN
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• Derived a simple and reliable approximation for NT:
vv
KN
M
T
1
2
Mutlicell Systems: Key Results (Cont’d)
• Similar analysis yields reliable approximation for NTM.
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Single-Macrocell/Multiple-Microcell System
To
tal
Ave
rag
e N
um
ber
of
Use
rs,
95%
Fea
sib
ilit
y
L, Number of Microcells
Simulation Results, error bar
Linear Approximation
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Simulation Results, error bar
Linear Approximation
9-Macrocell/Multiple-Microcell System
To
tal
Ave
rag
e N
um
ber
of
Use
rs,
95%
Fea
sib
ilit
y
L, Number of Microcells
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Other Issues in Ideal Two-Cell Systems:
Soft-Handoff,Voice Activity Detection,
Propagation Parameter Sensitivity,and Microcells as DAPs
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• 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.
Other Issues in Two-Cell Systems: Key Results
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• Effect of Voice Activity Factor: Let be the fraction of time voice users speak. Under voice activity detection, mean approximation contour is modified as:
)1(~ˆ
)~ˆ(ˆ~
vvNK
NKKN
MM
M
.~
and ,~
,1ˆ where,
NN
NNKK M
M
• Sensitivity to Propagation Parameters: Fairly insensitive
Other Issues in Two-Cell Systems: Key Results (Cont’d)
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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.
Downloading a map to a passing car
Email, voice mail,and fax to thepedestrian
High bit-rateDAP coverage
Low bit-ratecellular coverage
Examples of DAP’s: Infostations, Dedicated Short-Range Communications (DSRC), and Intelligent Transportation Systems (ITS)
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Problem Statement
Recall: Microcell coverage shrinks as desensitivity () reduces.
Question: What happens when and microcell coverage area shrinks to that of a DAP?
0
Determine: Per-user throughput, u , and total DAP throughput, , as functions of .
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Normalized Average Throughput (E[ / W ]) Versus N
orm
aliz
ed A
vera
ge
Th
rou
gh
pu
t
Desensitivity
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Uplink Capacity and Coverage:
Max Power Constraintsand 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
• W = 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
.4
max
max
d
b
W
PF
P [Outage] = (1-P [Feasibility]) + P [Feasibility] ·P [Transmit Power > Pmax].
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N,
To
tal
Nu
mb
er o
f U
sers
, 5%
Ou
tag
e
4
max
max
db
WP
F
Capacity in System with Max Power Constraints
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• 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’ = Tij, 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
Variable Power Fading: Background
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Uniform Multipath Channel
Channel Delay Profile
delay
power
Lp
Number of Paths
Height of each path is mean square value of a Rayleigh random-variable.
• 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.
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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• W = Noise power
Determine:
Uplink user capacity so that P[Outage] does not exceed .
• for the three standard environments, i.e., RA, TU, and HT, as functions of F.
• for any environment when F >> F* (unlimited terminal power).
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• Uplink capacity constant for RA, HT, and TU environments whenF < 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:
• Showed uplink capacity is the same for channels with the same DF.
DF Replace Lp in with DF
Napprox
Non-UniformDelay Profile
vvL
LK
N
Mp
p
11
2
, for Lp > 1.
Variable Power Fading: Key Results
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RA HT TU
Uplink Capacityusing Simulation
Uplink Capacityusing Approximation
(via Uniform Channel)
33 36 37
32.5 35.86 37.1429
Obtaining NT for RA, HT, and TU Channels via the Uniform Channel
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Downlink Capacity:
Channel Dispersionand 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 userterminals.
• Orthogonality factor, , captures loss-of-orthogonality of user signals in a channel. [0,1], where = 0 when no dispersion in channel and = 1 when infinite dispersion.
• can be computed from channel delay profile.
• Thus far: assumed = 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, .• Conventional receivers at user terminals• Base station k transmits total power PTk, k { M,}• Macrocell user i assigned fraction xi of PTM
• Microcell user j assigned fraction yj of PT
• Downlink power control scheme for allocating xi and yj
Determine:
Downlink user capacity, number of simultaneous voiceusers
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Downlink Capacity: Key Results
• Recast uplink capacity, NT, as a function of .
• Capacity of any channel ( ) approximated using capacity of uniform channel.
• For two of three power control strategies studied (uniform and slow), overall capacity dominated by uplink for all .
• Under fast power control, user capacity can be approximated (by relating to u) as:
• Fast power control leads to downlink capacity that is higher than uplink.
.0 for ,
21
1
2
vv
KN
M
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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-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.
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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.