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The Lucent Cellular Optimization Tool. Chandra Chekuri, Ken Clarkson, John Hobby, Howard Trickey, Lisa Zhang Larry Drabeck, John Graybeal, Georg Hampel, Paul Polakos Peiwen Hou, Bhushan Apte. Why “Ocelot”?. .*w.*o.*t.* blowout bowknot figwort madwort ragwort ribwort rowboat swot swotted
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The Lucent Cellular Optimization Tool Chandra Chekuri, Ken Clarkson, John Hobby, Howard Trickey, Lisa Zhang Larry Drabeck, John Graybeal, Georg Hampel, Paul Polakos Peiwen Hou, Bhushan Apte
Why “Ocelot”? • .*w.*o.*t.* blowout bowknot figwort madwort ragwort ribwort rowboat swot swotted • .*t.*c.*o.* outcome outcrop portico stucco stuccos taco tacos taction talcose tobacco • .*t.*ce.*o.* trecento • .*t.*o.*ce.* thoraces toepiece trounce twopence • .*ce.*.*op.* acetophenetidin cellophane cephalopod cephalopodan mycetophagous • .*op.*ce.* copacetic coparcenary coparcener coppice opalescence opalescent opulence populace • .*s.*ce.*o.* saucebox scenario seicento • .*ce.*p.*t.* centripetal centripetally cephalization cephalometry cephalothorax chemoreception chemoreceptive concept cesspit
The Problem • We want to tune cellular systems for: • Contract requirements • Peak performance
We can change: • Antenna Power • Antenna Tilt (with difficulty) • Antenna Azimuth (ditto) • (GSM) frequency plan • Not antenna location • Plausible for a metropolitan area market.
Current Practice: Drivetests • Drive around making measurements • adjust some parameters • repeat until done
Ocelot Approach • Model system numerically • Compute performance measures for model • Numerically optimize performance
OCELOTOptimization Ocelot-Optimized Design Coverage: 98% Initial Design Coverage: 84% Uncovered Areas. Covered Areas. Sectors colors: Tilt 00 7 0
Performance measures • Coverage • should serve all of market, without “holes” • Capacity • should serve as many calls as possible • There is a tradeoff between these two goals
Low Coverage High Coverage High Pilot Pollution in Center => Large Coverage Hole Reduced Pilot Pollution in Center: => Small Coverage Holes Cells have equal traffic load => High Effective Network Capacity Traffic load unbalanced => Small Effective Network Capacity High Capacity Low Capacity Max Coverage vs. Max Capacity Network coverage and network capacity cannot be optimized at the same time =>Example: 5-Cell Scenario Large Antenna Tilt Small
Max Capacity Max Coverage Compromise Capacity vs. Coverage 50% 3%
Demo of OCELOT in Action • Optimization of a CDMA Market
Sectors colors: Tilt 00 7 0 CELLS OF WIRELESS NETWORK
Sectors colors: Tilt 00 7 0 OCELOT COVERAGE OPTIMIZATION STARTS
Sectors colors: Tilt 00 7 0 INITIAL COVERAGE 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 FINAL COVERAGE 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 Initial Design INITIAL COVERAGE 98 82 84 86 88 90 92 94 96 100 %
Sectors colors: Tilt 00 7 0 Ocelot Optimized Design FINAL COVERAGE 98 82 84 86 88 90 92 94 96 100 %
OCELOT Performance • Significant Performance Improvements using Ocelot • Coverage : 5% to 20% • Capacity : 20% to 80% • Field trials have Demonstrated Ocelot Optimization is Superior to Drive Test Optimization • Ocelot successfully used worldwide • Used in ~30 CDMA IS95 markets • Used in ~10 GSM markets • Demo UMTS markets
Technical Challenges • Traffic modeling (pattern of calls) • Predicting pathlosses (signal strengths) • Modeling network performance • Hard: phones and base-stations interact • Computing derivatives (for optimization) • User interface should be: • Robust to errors • Responsive while computing
Outline • Traffic modeling and meshes • CDMA system modeling • Reverse-link interference and power control • Power amplifier sharing • The GUI • Theme: many applications of algorithmic ideas
Traffic modeling • Phone traffic pattern is modeled with a “mesh” • planar graph • Evaluate system based on calls from mesh edges • Mesh is from a street map (if available) • Street map density is roughly population density • People make calls from cars • Edges of mesh also have traffic weights
Geometric operations • Import maps • Map overlay: line segment intersection • Clipping against polygons • user supplied, or • “Autoboundary”
Autoboundary • Base-station locations imply phone traffic density • Code: • find a-shape • Minkowski sum with square • Cull