Blind Synchronization and Detection of Nyquist Pulse Shaped QAM Signals

This thesis proposes a blind receiver for the Nyquist pulse shaped quadratureamplitude modulation (QAM) signals. The focus is on single carrier signals. The blind receiver includes the estimation of the symbol rate, the roll-off factor of the filter, the optimal sample phase, the frequency offset, the phase offset and as well as the correction of frequency and phase offsets. The blind receiver is proposed for the cognitive radio applications. Cognitive radios are intelligent devices which can adapt themselves according to its user and its environment, i.e. they are aware of the user and the environment. Another importance of cognitive radios is they can detect the incoming signal and demodulate it and also respond to the transmitting node with the same parameters. In order to demodulate the signal and to respond the transmitter node, there are some parameters which are needed to be known. The estimation starts with the bandwidth and carrier frequency, continued by the estimation of the symbol rate, which is a crucial factor. After the estimation and restrictions of these parameters, the roll-off factor of the filter is estimated for match filtering to remove the inter symbol interference (ISI) effect. Then the optimal sample phase is detected and the signal is downsampled. The following procedures include the modulation identification and estimation and correction of both frequency and phase offsets. The estimation algorithms performance is compared to the performances of the other algorithms available in the literature. These simulation results are presented and discussed in this thesis.

Grantor dc:publisher

Digital Commons @ University of South Florida

Year dc:date

2009

Author dc:creator

• Terzi, Evren

• Symbol rate
• Baud rate
• Frequency offset
• Phase offset
• Modulation identification
• American Studies
• Arts and Humanities

Statement dc:rights

• default

Repository record dc:identifier

https://digitalcommons.usf.edu/etd/48

OAI identifier oai:identifier

oai:digitalcommons.usf.edu:etd-1047