Unique word detection using quantized soft-decision data

Hiroyuki Sasai*, Masato Takeyabu, Ken Minomo, Fumio Takahata, Junichi Ogikubo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The efficacy of applying quantized soft decision data to unique word (UW) detection, which plays an important role in frame synchronization in digital radio transmission systems, is discussed considering hardware implementation. This UW detection method represents the received signal vector using representative points within a multidimensional space and measures the Euclidean distance from the vector point corresponding to the UW pattern. Probability calculations are employed for obtaining theoretically UW detection characteristics such as missed detection and false detection, assuming that white Gaussian noise is added to the signal during transmission. These various characteristics are then compared quantitatively with the characteristics obtained by the conventional UW detection method using hard decision data. In addition, the UW detection characteristics obtained experimentally using hardware are presented. As a result of the quantitative evaluations, it has been clarified that the application of soft decision data is effective in reducing the UW length required for objectives of the UW detection performance associated with frame synchronization characteristics.

Original languageEnglish
Pages (from-to)80-93
Number of pages14
JournalElectronics and Communications in Japan, Part I: Communications (English translation of Denshi Tsushin Gakkai Ronbunshi)
Issue number2
Publication statusPublished - 1994 Feb
Externally publishedYes

ASJC Scopus subject areas

  • Computer Networks and Communications


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