Blind Equalization with Differential Detection for Channels with ISI and Fading

Our fi& Notre refdrence The author has granted a non-L'auteur a accordé une Licence non exclusive licence allowing the exclusive permettant à la National Library of Canada to Bibliothèque nationaie du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/^, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor substantial extracts fkom it Ni la thèse ni des extraits substantiels may be printed or otheMrise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. Using coherent detection with carrier tracking and adaptive equalization with training sequence can achieve good performance in equalizing time-varying channels at the expense of complexity and feasibility. Thus, differential detection and blind equalization , which eliminate PLL and training sequence, are proposed. Decision feedback is dso added to equalize null and fading channels. In this thesis, Godard and Modified Constant Modulus Algorithms (MCMA) axe used. New systems are set up by combining coherent and noncoherent detection with these two algorithms. It is found that the use of noncoherent detection degrades the system performance. For MCMA, as it can track the carrier, neither noncoherent detection nor PLL is required. Contrarily, Godard needs either noncoherent detection or PLL to correct phase error. Thus, the proposed system combining differentid detection, blind equalization and decision feedback c m indeed equalize different channels, though the robustness of the system is compromised. Further investigations must be done to deal with this problem. Special thanks to Ali Masoomzadeh-Fard, for helping me to start my work, and for his patience when answering my never-ending questions. Last but not least, my family and friends, whose understanding and support are forever appreciated.