Wireless Network Design: Optimization Models and Solution ...

6 Optimization Based WLAN Modeling and Design 129
ronment may require deploying many more APs. Recently, a number of small cities
and towns across the United States deployed city wide WLAN networks that allow
boradband access to Internet resources at reasonable costs for residents, local government
workers, and emergency and first responders. Though initially very popular
with city councils across the United States, these networks faced large operational
costs that have limited their growth.
The basic WLAN design problem involves decisions concerning the number and
location of radio transmitters/receivers (APs), the frequency to be assigned to each
AP, and the signal power of each AP. Many organizations install WLANs as an
alternative to cabled networks without spending much time on planning and design.
Some simply place APs in a grid, turn them on, and add more as problems arise.
However, careful planning ensures high performance at minimum cost.
6.2 Literature Survey
There are two basic strategies have been adopted by industry specialists for designing
WLANs: site surveys and the use of software tools. Many of these software
tools use optimization models and algorithms to solve this problem. Reseatch studies
that propose the use of optimization models and algorithms generally address
one or more of the following problems: i) determine a minumum cost coverage for
a given site, ii) determine a channel assignment for a fixed set of APs to optimize
some metric, or iii) determine the optimal AP placement to optimize some metric. In
addition, the literature also contains descriptions of several proprietary design tools
developed by industrial research groups.
6.2.1 Site Surveys
An excellent description of a site survey for the Miami International Airport may
be found in [4]. Geier and his associates mounted an AP on a roll-around cart with
its antenna attached to the top of a telescopic pole. Since APs are usually mounted
on the ceiling, this configuration could be used to approximate the location of an
installed AP. On a separate cart, they carried laptops and other equipment that could
record signal-to-noise ratios. Using this equipment, they tested over sixty AP locations
before developing a proposed design. This practice adopts the well known
approach used in cellular radio frequency (RF) optimization, where cell site coverage
is checked via extensive drive testing.
Mateus et al. [12] (see also [17]) report on their experience using a site survey
to locate 3 APs to cover 2 floors of an academic building with labs and faculty
offices. The authors selected 6 candidate locations for AP installation to cover 253
demand areas. Signal strength data was collected at each of the 253 demand points
by slowly rotating a mobile receiver at each location. Signal strength is sensitive