doc.: ieee 802.11-04/441r0 submission april 2004 roger skidmore, wvcslide 1 overview of prediction...
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April 2004
Roger Skidmore, WVCSlide 1
doc.: IEEE 802.11-04/441r0
Submission
Overview of Prediction of Wireless Communication Network Performance
Roger Skidmore
Wireless Valley Communications, Inc.
April 2004
Roger Skidmore, WVCSlide 2
doc.: IEEE 802.11-04/441r0
Submission
Introduction – What is “Prediction”?• Prediction means different things to different people• This presentation considers “prediction” in the context
of WLAN deployment• Important to consider that you can not deploy a WLAN
without making “predictions”– You are making a decision about what to buy, where to put
it, and how to configure it – Anything other than a purely measurement-based design (i.e.,
putting up access points, measuring, moving access points, measuring, repeat) involves some degree of prediction• Pure measurement-based design becomes very expensive, very
quickly as the size and complexity of the network increases
April 2004
Roger Skidmore, WVCSlide 3
doc.: IEEE 802.11-04/441r0
Submission
Automating Prediction with Software• Using software to model wireless network
performance is becoming more common– Goal is to minimize up-front deployment costs and
back-end network management issues– The better the design, the easier the management
• An ounce of prevention is worth a pound of cure
• Predictive algorithms and techniques refined through years of use in cellular/PCS technologies provide reliable accuracy with a re-usable methodology with regard to radio propagation
April 2004
Roger Skidmore, WVCSlide 4
doc.: IEEE 802.11-04/441r0
Submission
Typical Prediction Process
Predict Radio Wave Propagation (PHY)
Create Computer Model of Physical Environment
Create Computer Model of Equipment
Overlay RF Analysis (PHY) with Equipment / Technology Effects
(MAC)
Position / Interconnect Equipment within
Environmental Model
April 2004
Roger Skidmore, WVCSlide 5
doc.: IEEE 802.11-04/441r0
Submission
Create a Computer Model of the Environment• Manipulate various data sources (CAD files, raster
images, etc.) into a form usable for radio wave propagation prediction
• If available, structural information can dramatically improve prediction accuracy– Walls, floors/ceilings, windows, large shelving– Can usually categorize structures into broad categories
of material type• For example, Concrete, Tinted Glass, Metal Shelving, etc.
• User information can be considered– For example, user density and priority levels, traffic
patterns, service types, etc.
Example building model
April 2004
Roger Skidmore, WVCSlide 6
doc.: IEEE 802.11-04/441r0
Submission
Example Method of Modeling Equipment• Each piece of equipment is broken up into individual
modules that are linked internally• Each module defined by a component database• Modules are interconnected together to achieve final
representation of a desired piece of equipment– For example, an access point may combine a Antenna and
Transceiver modules, or may include various Cable modules
• Interconnectivity effects– For example, using different types of antennas can directly
affect the operating characteristics of devices to which they are attached
April 2004
Roger Skidmore, WVCSlide 7
doc.: IEEE 802.11-04/441r0
Submission
Create Computer Model of Equipment• Detailed description of equipment characteristics are
used to provide additional predictive results such as throughput
• Typically derived through experimental trials• Example equipment-specific parameters:
– Air interface / Protocols (e.g., 802.11a/b/g)– Antennas, Antenna Patterns– Transmit power, Data-rate specific transmit power– Hand-off thresholds– Frequency-specific effects (for multi-band equipment)– Noise / Interference rejection– Interoperability effects
April 2004
Roger Skidmore, WVCSlide 8
doc.: IEEE 802.11-04/441r0
Submission
Position / Interconnect Equipment
WLAN Access Point 204.71.202.16, Floor 4
CAT5 Cable, Floor 4
WLAN Access Point 204.71.202.16, Floor 4
CAT5 Cable, Floor 4
April 2004
Roger Skidmore, WVCSlide 9
doc.: IEEE 802.11-04/441r0
Submission
Predict Radio Wave Propagation• Well-known algorithms and methods for doing this
– ITU standards, COST-231, FCC guidelines, academic research– Industry proven to be accurate and reliable
• Well-known tradeoffs between accuracy of specific algorithms and the conditions under which the algorithms are best applied
• Algorithms vary widely in terms of accuracy, computational intensity, parameters considers, and applicability to various scenarios
• Many algorithms can be calibrated with measurement information
• Result is an accurate representation of the RF environment
April 2004
Roger Skidmore, WVCSlide 10
doc.: IEEE 802.11-04/441r0
Submission
Predict Radio Wave Propagation• Received signal strength
intensity (RSSI) on the downlink for an example 802.11g WLAN
-40 dBm
-55 dBm
-70 dBm
-85 dBm
-100 dBm
~25 feet
April 2004
Roger Skidmore, WVCSlide 11
doc.: IEEE 802.11-04/441r0
Submission
Overlay RF Analysis with Equipment / Technology Effects
• Once RF channel (PHY) environment is defined through prediction, can overlay equipment / technology-specific effects to derive operating characteristics at higher layers (e.g., throughput)
• Equipment model defines known relationship between the RF channel environment and the operating “performance” of the actual equipment
• Many algorithms can be calibrated with measurement information
• Result is more identifiable as “network performance”
April 2004
Roger Skidmore, WVCSlide 12
doc.: IEEE 802.11-04/441r0
Submission
> 1 Mbps
650 - 800 kbps500 - 650 kbps350 - 500 kbps200 - 350 kbps
800 - 1000 kbps
< 200 kbps
Active Access PointActive Access Point Overlay RF Analysis with Equipment / Technology Effects
PDA with 802.11b PCMCIA card
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