The initial code acquisition techniques for direct sequence code division multiple access (DS/CDMA) communication networks are investigated in this thesis. Conventional methods of code acquisition, which are basically based on the auto correlation and cross correlation properties of spreading codes, fail in the presence of multiple access interference (MAI) and the near-far effect. This fact motivates the study for interference resistant acquisition algorithms in the hostile channel environment. Training-based acquisition is investigated and the effect of training sequence structure on acquisition performance is discussed. A new training sequence architecture is proposed which results in a shorter acquisition time. Demands for high bit rate services and needs for more efficient exploitation of resources lead to the study of acquisition algorithms that do not need the preamble or training sequences. In this context, blind adaptive algorithms for code acquisition are investigated. The mismatch problem of blind algorithms is addressed and a novel method of mismatch problem handling for Constraint Minimum Output Energy (C-MOE) is proposed. The algorithm results in good acquisition performance under different channel conditions and system loadings. The idea of joint acquisition and demodulation of data, where the outcome of the acquisition mode is an interference suppressor filter, is also discussed. It is shown that in this class of receivers, a one-step constraint acquisition process is not sufficient for handling both the mismatch problem and exploiting the multi-path diversity. Therefore, a novel receiver is proposed which is able to handle the mismatch problem as well as the channel diversity. This receiver is based on a two- step constraint minimum output energy algorithm and comparatively provides a good acquisition and demodulation performance.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:274333 |
| Date | January 2003 |
| Creators | Neda, Naaser |
| Publisher | University of Surrey |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://epubs.surrey.ac.uk/842876/ |
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