2011
DOI: 10.1587/transfun.e94.a.1772
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Reliability of Generalized Normal Laplacian Distribution Model in TH-BPSK UWB Systems

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Cited by 4 publications
(9 citation statements)
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“…An MME, which is computationally simple, is considered for parameter estimation of the GNL distribution parameters [5]. In the GN L(μ, σ 2 , α, β, ρ) distribution, μ is a location parameter and σ 2 is a scale parameter influencing on the spread of the GNL distribution.…”
Section: Gnl Receivermentioning
confidence: 99%
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“…An MME, which is computationally simple, is considered for parameter estimation of the GNL distribution parameters [5]. In the GN L(μ, σ 2 , α, β, ρ) distribution, μ is a location parameter and σ 2 is a scale parameter influencing on the spread of the GNL distribution.…”
Section: Gnl Receivermentioning
confidence: 99%
“…Recently, a normal-Laplace (NL) distribution function has been generalized to a new probability distribution case, which is called a generalized normalLaplace (GNL) distribution [3,4]. In [5], the GNL distribution has been considered for analyzing the performance of the conventional single-user correlation receiver in multi-user UWB systems. In this letter, an improved multi-user UWB receiver based on the GNL distribution is introduced for TH UWB signal detection.…”
Section: Introductionmentioning
confidence: 99%
“…With the assumption of the symmetric GNL distribution case (α = β), the resulting estimates are defined as a = b = 20g 4 /g 6 , r = 100g 3 4 /3g 2 6 , σ 2 = γ 2 /ρ − 2/α 2 and μ = γ 1 /ρ. Here γ u , u = 1, 2, 4, 6, can be obtained through the Taylor series expansion of the sample cumulant generating function, which are given as γ 1 = r 1 , g 2 = r 2 − r 2 1 , g 4 = r 4 − 6r 4 1 + 12r 2 1 r 2 − 3r 2 2 − 4r 1 r 3 and g 6 = r 6 − 120r 7 1 + 30r 3 2 − 10r 2 3 − 6r 1 r 5 − 15r 2 r 4 + 30r 2 1 r 4 − 30r 1 r 2 2 − 36r 2 1 r 3 − 84r 3 1 r 3 − 228r 2 1 r 2 2 + 360r 4 1 r 2 + 120r 1 r 2 r 3 [10]. Fig.…”
Section: Generalised Normal-laplace Model For Non-gaussian Noisementioning
confidence: 99%
“…The conventional matched filter (CMF) receiver based on a Gaussian approximation (GA), which has been widely employed for UWB signal detection, underestimates its bit error rate (BER) performance under multiple access interference (MAI)-plus-noise environments [2][3][4][5]. In the recent contributions, better statistical probability models for the MAI-plus-noise than the GA have been introduced for developing enhanced multiuser UWB receivers [6][7][8][9][10][11][12]. In [6], a Laplace distribution has been used to model the MAI in the time-hopping (TH) UWB systems.…”
Section: Introductionmentioning
confidence: 99%
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