Implementation and Evaluation of Fuzzy Logic Based Signal Classification for Standard Wireless Technologies

Author : Sepideh Ghorbanloo
Supervisor : Prof. Dr. Uwe Meier
Type : Project work
Short description :

This report presents a Neuro Fuzzy Signal Classifier (NFSC) in order to identify primary user (PU) signals in coexisting environments. The NFSC uses bandwidth, operating frequency, pulse shape, hopping behavior and time behavior of the signals as distinct features to classify the PU signals. The MSP430 microcontroller and CC2500 transceiver from Texas Instruments are used for the implementation.
The evaluation focus mainly on timing issues, i.e. the channel switching delay and the input detection delay. The performance of the NFSC for IEEE 802.11g detection and classification is evaluated in two different scenarios, high load IEEE 802.11g and low load IEEE 802.11g.

Contact Person : Prof. Dr. Uwe Meier