Efficient Nonlinear Detector of Binary Signals in Rayleigh Fading and Impulsive Interference

Saaifan, Khodr A.; Hassan, Khaled; Henkel, Werner

doi:10.1109/vtcfall.2012.6399303

Cited by 3 publications

(3 citation statements)

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“…First, we note that for a single observation (L = 1) the considered detectors have an almost optimum performance. This was expected, since we proved in [10] that the conventional coherent detector is still optimum when L = 1 in a complex MCA noise. Second, we note that a significant performance improvement can be obtained by increasing L. Moreover, the gain in performance obtained by employing the optimum or nonlinear combiners is relatively small over the MRC in such a noise environment.…”

Section: Simulation Resultsmentioning

confidence: 62%

“…In this model, z l is a complex-valued noise process. Since the in-phase and quadrature (IQ) components of z l are generated by the same physical process creating the impulse, the noise samples z l = z I,l + jz Q,l can be modeled by a bivariate MCA density as [8], [10] p…”

Section: System Modelmentioning

confidence: 99%

“…The terms β 0 = e −A and β 1 = 1−e −A are the probabilities of being in eah state, respectively. Since σ 2 1 σ 2 0 , we showed in [10] that the two-term model can be approximated as follows:…”

Section: A Nonlinearity For Real Mca Channelsmentioning

confidence: 99%

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A nonlinear diversity combiner of binary signals in the presence of impulsive interference

Saaifan

Henkel

2013

2013 IEEE International Conference on Communications (ICC)

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A Middleton Class-A (MCA) model is one of the most accurate statistical-physical models for narrowband impulse noise. The previous studies show that time diversity can efficiently be used to reduce the impact of MCA noise. The optimum combiner in such noise consists of a nonlinear preprocessor followed by a conventional combiner. Since an MCA noise process consists of an infinite number of noise states, there is no closedform solution of the optimum nonlinearity. In this paper, we adopt a two-term model for the MCA process, which is further approximated to a simpler noise model. Therefore, we introduce a closed-form approximation of the optimum nonlinearity in the presence of real-valued MCA noise. In fading channels, we use a complex extension of an MCA model. We show how the nonlinearity operation maintains the diversity advantage in such a noise model.

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Section: Simulation Resultsmentioning

confidence: 62%

Section: System Modelmentioning

confidence: 99%