Abstract: Wireless LAN (WLAN) access in public hotspot areas
becomes popular in the recent years. Since more and more multimedia
information is available in the Internet, there is an increasing demand
for accessing multimedia information through WLAN hotspots.
Currently, the bandwidth offered by an IEEE 802.11 WLAN cannot
afford many simultaneous real-time video accesses. A possible way to
increase the offered bandwidth in a hotspot is the use of multiple access
points (APs). However, a mobile station is usually connected to the
WLAN AP with the strongest received signal strength indicator (RSSI).
The total consumed bandwidth cannot be fairly allocated among those
APs. In this paper, we will propose an effective load-balancing scheme
via the support of the IAPP and SNMP in APs. The proposed scheme is
an open solution and doesn-t need any changes in both wireless stations
and APs. This makes load balancing possible in WLAN hotspots,
where a variety of heterogeneous mobile devices are employed.
Abstract: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.