In a densely populated area with many users, adding a new wireless access
point may not necessarily improve Wi-Fi performance. There are times when students
must deal with poor download rates even with Access Points (AP) in every classroom.
Cochannel interference is the root cause of several typical Wi-Fi issues. A discussion
may be compared to Wi-Fi communication. The capacity to communicate and listen
properly are both essential for effective communication. When two speakers are
speaking in a similar tone, the conversational uncertainty is exacerbated. Wi-Fi
broadcasts are the same way. The interference and drag performance might be
worsened by two or more nearby APs using the same channel. This study suggests a
smart antenna technology. When a smart antenna AP finds a nearby AP signal, it will
automatically alter its pattern to minimise interference and provide quick and reliable
transmission. The same principle applies when we cup our hands over our lips or ears
to enable us to yell or listen more clearly. There are a lot of false positives in the typical
approaches for WLAN node signal recognition. The optimal signal for a WLAN node
is therefore identified using this study's proposed BPNN model, which uses the
PFMDMM system for signal classification. This Decision-Making Model Using
Parameterized Fuzzy Measures has been shown via experiments. A WLAN node's
optimal signal may be more accurately predicted using a decision-making model based
on preference-leveled evaluation functions. The precision of the signal identification
and the anticipated findings were found to be almost identical to those obtained from
real ground measurements. The test team mimicked cochannel interference, which
would occur in a setting with plenty of APs, such as a workplace, hotel, or airport. The
suggested smart antenna AP regularly outperformed other apps by an average of 75%
greater coverage and unmatched performance.
Keywords: BPNN, Decision making model, Deep learning model, Preference leveled evaluation functions, Received signal strength, Reconstruction, Signal detection, Smart antenna.