Browsing by Subject "Noise statistics"

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    Detector randomization and stochastic signaling for minimum probability of error receivers
    (Institute of Electrical and Electronics Engineers, 2012) Dulek, B.; Gezici, Sinan
    Optimal receiver design is studied for a communications system in which both detector randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector randomization cannot achieve a smaller average probability of error than detector randomization with deterministic signaling for the same average power constraint and noise statistics. Then, it is shown that the optimal receiver design results in a randomization between at most two maximum a-posteriori probability (MAP) detectors corresponding to two deterministic signal vectors. Numerical examples are provided to explain the results.
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    Optimal filtering in fractional Fourier domains
    (IEEE, 1995) Kutay, M. Alper; Onural, Levent; Özaktaş Haldun M.; Arıkan, Orhan
    The ordinary Fourier transform is suited best for analysis and processing of time-invariant signals and systems. When we are dealing with time-varying signals and systems, filtering in fractional Fourier domains might allow us to estimate signals with smaller minimum-mean-square error (MSE). We derive the optimal fractional Fourier domain filter that minimizes the MSE for given non-stationary signal and noise statistics, and time-varying distortion kernel. We present an example for which the MSE is reduced by a factor of 50 as a result of filtering in the fractional Fourier domain, as compared to filtering in the conventional Fourier or time domains. We also discuss how the fractional Fourier transformation can be computed in O(N log N) time, so that the improvement in performance is achieved with little or no increase in computational complexity.