| 1. |
- Peric, B. M., et al.
(author)
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Soft decision metrics for turbo-coded FH M-FSK ad hoc packet radio networks
- 2005
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In: Vehicular Technology Conference, VTC-Spring. 2005. Vol. 2. - 0780388879 ; , s. 724-727
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Conference paper (peer-reviewed)abstract
- This paper addresses turbo-coded non-coherent FH M-FSK ad hoc networks with a Poisson distribution of interferers where multiple access interference can be modeled as symmetric α-stable (SaS) noise and α is inversely proportional to the path loss exponent. The Bayesian Gaussian metric does not perform well in non-Gaussian (α≠2) noise environments and therefore an optimum metric for Cauchy (α=1) noise and a generalized likelihood ratio (GLR) Gaussian metric requiring less side information (amplitude, dispersion) are presented. The robustness of the metrics is evaluated in different SoS noise environments and for mismatched values of the interference dispersion and channel amplitude in an interference-dominated network with no fading or independent Rayleigh fading. Both the Cauchy and GLR Gaussian metric exhibit significant performance gain over the Bayesian Gaussian metric, while the GLR Gaussian metric does so without the knowledge of the dispersion or amplitude. The Cauchy metric is more sensitive to the knowledge of the amplitude than the dispersion, but generally maintains better performance than the GLR Gaussian metric for a wide range of mismatched values of these parameters. Additionally, in an environment consisting of non-negligible Gaussian thermal noise along with multiple access interference, increasing the thermal noise level degrades the performance of the GLR Gaussian and Cauchy metric while for the observed levels both maintain better performance than the Bayesian Gaussian metric.
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| 2. |
- Souryal, M. R., et al.
(author)
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Soft-decision metrics for coded orthogonal signaling in symmetric alpha-stable noise
- 2005
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). - 0780388747 ; , s. III-697-III-700
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Conference paper (peer-reviewed)abstract
- This paper derives new soft decision metrics for coded orthogonal signaling in symmetric α-stable noise, which has been used to model impulsive noise. In addition to the optimum metrics for Gaussian (α=2) noise and Cauchy (α=1) noise, a class of generalized likelihood ratio (GLR) metrics with lower side information requirements is derived. Through numerical results for a turbo code example, the Cauchy decoder is found to be robust for a wide range of α, and GLR metrics are found which provide performance gains relative to the Gaussian metric, but with lower complexity and less a priori information.
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