Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-090809-120824


Document Typethesis
Author NameBobrowski, Kevin Matthew
URNetd-090809-120824
TitlePractical Implementation Considerations for Spectrally Agile Waveforms in Cognitive Radio
DegreeME
DepartmentElectrical & Computer Engineering
Advisors
  • Professor Alexander M. Wyglinski, Advisor
  • Professor Xinming Huang, Committee Member
  • Professor Donald Richard Brown, Committee Member
  • Keywords
  • NC-OFDM
  • cognitive radio
  • OFDM
  • software defined radio
  • Date of Presentation/Defense2009-09-08
    Availability unrestricted

    Abstract

    As the demand for bandwidth increases, the inefficient use of the spectrum becomes more apparent and limiting. Currently, secondary (unlicensed) users can not use sparsely occupied portions of radio spectrum that are not allocated to them. In prior research, a variant of Orthogonal Frequency Division Multiplex (OFDM) called Non-Contiguous OFDM (NC-OFDM) was found to be a suitable transmission technique for enabling Dynamic Spectrum Access, which allows for multiple secondary users to share the spectrum. This thesis presents an algorithm for the synchronization of NC-OFDM. Moreover, a hardware architecture is proposed for the synchronization, and a pruned FFT/IFFT core is designed.

    At present, there has been minimal research into synchronization for NC-OFDM systems. As with any modulation scheme, synchronization is an important part for receiving the transmission successfully. The current synchronization scheme is simulated in variety of wireless channels to show that it can successfully communicate in the tested channels.

    Additionally a hardware architecture is laid out for the practical implementation of the synchronization algorithm. Since NC-OFDM does not use all of the carriers for transmission, the FFT and IFFT can have their computations reduced. Since the FFT and IFFT are important parts to the receiver and the transmitter, a pruned FFT/IFFT in hardware makes the most sense to be able to reduced the computation. The number of butterfly computations is reduced at the expense of a large increase in resource usage.

    Files
  • bobrowksi.pdf

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