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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps Measuring the Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps Meisam Mirahsan Rainer Schoenen

SLIDE 1

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 1 of 24

Measuring the Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan Rainer Schoenen Sebastian Szyszkowicz Halim Yanikomeroglu Carleton University Ottawa, Canada

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 2 of 24

 HetNets with heterogeneous user distribution 

HetHetNets

 Sources of User Spatial Heterogeneity  Measuring Spatial Heterogeneity  Open Source Maps – A Great Resource for Wireless

Communications Modeling

 Initial Heterogeneity Results in a Dense Urban Area  Ongoing Related Research

Outline

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 3 of 24

Sources of User Spatial Heterogeneity: 1) Self-Clustering

SLIDE 4

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 4 of 24

Sources of User Spatial Heterogeneity: 2) Urban Layout Focus of this paper!

SLIDE 5

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 5 of 24

Sources of User Spatial Heterogeneity: 3) Fixed Social Attractors

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 6 of 24

Small Cell Planning around Social Attractors  Correlation between user clusters and AP locations

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 7 of 24

Small Cell Planning around Urban Layout  Correlation between user layout and AP locations

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 8 of 24

Heterogeneity in Applications

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 9 of 24

If Supply and Demand Do Not Match in Space and Time…

Can we store (in time) and/or transfer (in space) the supply? If difficult, then more heterogeneous + more unpredictable  more problems

Supply Demand

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 10 of 24

[U of Texas, Austin]

HetNets: Heterogeneity in Supply (Access Points)

Coexistence of several cells types with very different coverage ranges. Locations of APs somewhere between a regular grid and total randomness:

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 11 of 24

Measuring Spatial Heterogeneity: Step 1: Voronoi Tesselation

For a set of Points, Find the Voronoi Partition: areas that are closer to

their own point than any other point.

Two points are “natural neighbours” if their Voronoi cells touch.
Natural neighbours are connected by straight edges to form the

Delaunay triangulation.

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 12 of 24

Measuring Spatial Heterogeneity: Step 2: Coefficient of Variation

Statistic: Coefficient of Variation:

CoV{x} = std.dev.{x}/(mean{x} * K) - K a constant

We study two metrics (two “flavours”):
CoV of Voronoi Cell Areas (K=0.529)
CoV of Delaunay Cell Edge Lenghts (K= 0.492)
CoV (either flavour) captures heterogeneity(dispersion/clustering) of any

point process in one positive scalar value:

Poisson Point Process: CoV=1 super-Poissonian (e.g. clustered): CoV>1 sub-Poissonian (e.g., repulsive): 0<CoV<1

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 13 of 24

HetHetNets = HetNets + Heterogeneity in Demand (User Locations)

Users (black) self-clustering: clustering increases with beta User clustering around APs: increases with alpha [JSAC Oct 2015]

CoV=1.53 CoV=2.38 CoV=3.46 CoV=4.03 CoV=4.88 CoV=5.51

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 14 of 24

A topic in wave sciences (physics) But simple models for mobile radio exists: Path-loss = A + 10n log(d) + X(σ) Path-loss model: from 2 parameters to very many parameters COST, WINNER, 3GPP, … n and σ : Describe a scenario (urban microcell, rural macrocell, etc.)

Comparison with Propagation Modeling

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 15 of 24

Free open vector maps made by volunteers from around the world. Some cities, notably central Paris, France, have very complete building footprint information. Every building is encoded as a closed polygon with known coordinates. We use data from central Paris: 10km x 8km, divided into overlapping 1km x 1km tiles.

OpenSourceMaps.org: Open Maps of the Entire World

[www.openstreetmap.org]

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 16 of 24

Cut tiles (1km x 1km) from a large (whole city) master file. Find all buildings. Convert building coordinates from spherical (lat/lon) to local 2D approximation (error < 4cm). Merge building into blocks and remove inner courtyards. Final Result: City blocks (light blue) and open areas (white)

Tile Processing

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Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 17 of 24

Heterogeneity becomes more prominent with increased user density

Users Placed Randomly in Outdoor Areas

SLIDE 18

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 18 of 24

Heterogeneity becomes more prominent with increased user density.

Users Placed Randomly in Outdoor Areas

SLIDE 19

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 19 of 24

Heterogeneity becomes more prominent with increased user density

Users Placed Randomly in Outdoor Areas

SLIDE 20

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 20 of 24

Heterogeneity becomes more prominent with increased user density

Users Placed Randomly in Outdoor Areas

SLIDE 21

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 21 of 24

Heterogeneity becomes more prominent with increased user density

Users Placed Randomly in Outdoor Areas

SLIDE 22

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 22 of 24

Measuring Heterogeneity of Outdoor Urban Users

CoV > 1: Point Process exhibits clustering-like behaviour

Outdoor users/km2 Based on 83 1km2 maps with high building density

SLIDE 23

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 23 of 24

Measuring Heterogeneity of Outdoor Urban Users Based on 83 1km2 maps with

high building density

SLIDE 24

Spatial Heterogeneity of Outdoor Users in Wireless Cellular Networks Based on Open Urban Maps

Meisam Mirahsan, Rainer Schoenen, Sebastian Szyszkowicz, Halim Yanikomeroglu ICC 2015: 11 June 2015/ London/ UK Page 24 of 24

Comparison between different types of cities (European vs US, urban vs suburban) Are there more appropriate metrics for characterizing the outdoor urban users’ distribution. Combine urban information with social attractors model for even more heterogeneity. Finding a simple-enough point process that has similar properties to the urban users location, with tunable parameters that can account for different types of urban areas. Use urban data to characterize the spatial distribution of small cell AP locations, their coverage, and their correlation with he users’ locations. Other interesting uses of OpenStreetMaps data in wireless communications…