Installation guide

13
Wi-Fi Location-Based Services—Design and Deployment Considerations
OL-11612-01
Location Tracking Approaches
• Tx
PWR
represents the transmitter output power in dB.
• Loss
TX
represents the sum of all transmit-side cable and connector losses in dB.
• Gain
TX
represents the transmit-side antenna gain in dBi.
• Loss
RX
represents the sum of all receive-side cable and connector losses in dB.
• Gain
RX
represents the receive-side antenna gain in dBi.
Solving for distance between the receiver and mobile device allows you to plot a circular area around
the location of the receiver. The location of the mobile device is believed to be somewhere on this
circular plot. As in other techniques, input from other receivers in other cells (in this case, signal strength
information or RSSI) can be used to perform RSS tri-lateration or RSS multi-lateration to further refine
location accuracy.
The signal strength information used to determine position can be obtained from one of two sources.
Location positioning systems can determine position based on one of the following:
• The network infrastructure reporting the received signal strength at which it receives mobile device
transmissions (“network-side”)
• The mobile device reporting the signal strength at which it receives transmissions from the network
(“client-side”)
In 802.11 WLANs, the granularity with which RSSI is reported typically varies from radio vendor to
radio vendor. In fact, 802.11 client devices produced by different silicon manufacturers may report
received signal strength using inconsistent metrics. This can result in degraded and inconsistent location
tracking performance.
To avoid this situation, there are two basic options:
• Deploy a location tracking solution that relies on “network-side” RSSI measurements.
Because most deployments of 802.11 WLANs are standardized on IEEE 802.11 access points from
a single vendor, this is a very straightforward solution and is typically the solution most often
chosen.
• Deploy a location tracking solution that relies on “client-side” RSSI measurements.
Because it is not practical to assume that every client device in an enterprise WLAN is from the same
vendor, this option necessarily requires a means of providing “equalization” for each specific client
hardware model from each vendors to some “reference” hardware model with which the location
solution is designed to perform most accurately. For example, if positioning system software is
designed to expect RSSI in a range from -127dBm to +127dBm in 254 1dBm increments, some level
of mathematical equalization is required if some clients are capable of reporting RSSI in this format
while others can only report RSSI in a range from -111dBm to +111 dBm in 74 3dBm increments.
Typically, the responsibility for providing this means of equalizing RSSI reporting across one or
more hardware vendors (and maintaining pace with the various new revisions of hardware that each
major vendor produces) belongs to the location solution vendor.
To date, implementations using RSS lateration have enjoyed a cost advantage by not requiring
specialized hardware at the mobile device or network infrastructure locations. This makes signal
strength-based lateration techniques very attractive from a cost-performance standpoint to designers of
802.11-based WLAN systems wishing to offer integrated lateration-based positioning solutions.
However, a known drawback to pure RSS lateration is that propagation anomalies brought about by
anisotropic conditions in the environment may degrade accuracy significantly. This is because in reality,
propagation in any cell is far from an ideal circular pattern based on an ideal path loss model. Signal
levels vary significantly because of multipath, interference, occlusion, and attenuation. This is not
typically taken into account when designing systems using “textbook” theoretical RSS lateration models
in their purest form.