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UBC Theses and Dissertations

Bit error rate performance analysis and optimization of suboptimum detection procedures Beaulieu, Norman Charles


Three suboptimum detection schemes are examined. The deterioration in performance, measured in the probability of error sense, of weighted partial decision, binary partial decision, and sample-and-sum detectors are analyzed. Even though these schemes are inferior to the digital matched filter, they can be used in systems with more modest computational capabilities. Analytic expressions are obtained for the penalties. The effects on the penalties of the signalling waveform employed, the number of samples processed, and the signal-to-noise ratio are considered in detail. Included are the penalties for the optimum weighted partial decision detector. The effects of dependence among the samples on the detector losses are investigated. It is shown that, in some cases, the losses of the suboptimum procedures can be reduced by processing more, dependent, samples. The amount of the loss that can be recovered depends on the prefilter characteristic and the sampling rate, as well as the detection algorithm. The structure of the optimum detector for hard-limited data signals is presented and its performance is compared with those of some commonly used schemes. Performance in Impulsive as well as Gaussian noise environments is considered. The optimum receiver for M-ary signalling based on received signal samples quantized to an arbitrary number of levels is derived and compared to another common detector. The fundamental loss in signal detectability due to hard-limiting in a sampled system operating in Gaussian noise is investigated. The relation of the loss to the signal-to-noise ratio and the number of samples is analyzed.

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