Graduation Year
2009
Document Type
Thesis
Degree
M.S.E.E.
Degree Granting Department
Electrical Engineering
Major Professor
Huseyin Arslan, Ph.D.
Committee Member
Wilfrido Moreno, Ph.D.
Committee Member
Paris H.Wiley, Ph.D.
Keywords
Symbol rate, Baud rate, Frequency offset, Phase offset, Modulation identification
Abstract
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.
Scholar Commons Citation
Terzi, Evren, "Blind Synchronization and Detection of Nyquist Pulse Shaped QAM Signals" (2009). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/48