Energy-based Bayesian spectrum sensing over α-κ-μ fading channels

Gurugopinath, Sanjeev; Shobitha, S

doi:10.1109/comsnets.2017.7945363

Cited by 9 publications

(8 citation statements)

References 19 publications

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“…is paper provides a framework within a computational reach utilising a SMN construction within the fading environment, which could now be implemented by the practitioner when field data justify it. Further, as a potential future point of departure, these scale mixture density representations situated within the fading environment may provide particular advances within Bayesian computing, especially in the case of the Gibbs sampler, where this hierarchical representation may lessen the computational strain within implementation of Bayesian statistical inference (see, for example, [25,26]). Furthermore, the SMN (α − μ) model can be extended and implemented, for example, within the cascaded α − μ fading environment [3].…”

Section: Resultsmentioning

confidence: 99%

An Enriched α − μ Model as Fading Candidate

Ferreira

Bekker

Marques

et al. 2020

Mathematical Problems in Engineering

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This paper introduces an enriched α − μ distribution which may act as fading model with its origins via the scale mixture construction. The distribution’s characteristics are visited and its feasibility as a fading candidate in wireless communications systems is investigated. The analysis of the system reliability and some performance measures of wireless communications systems over this enriched α − μ fading candidate are illustrated. Computable representations of the Laplace transform for this scale mixture construction are also provided. The derived expressions are explored via numerical investigations. Tractable results are computed in terms of the Meijer G-function. This unified scale mixture approach allows access to previously unconsidered underlying models that may yield improved fits to experimental data in practice.

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Section: Resultsmentioning

confidence: 99%

An Enriched α − μ Model as Fading Candidate

Ferreira

Bekker

Marques

et al. 2020

Mathematical Problems in Engineering

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“…The α − κ − μ fading model and its variants were explored by a few authors in the literature. A unified performance evaluation of ED over α − η − μ and α − κ − μ fading channels was considered in the works of Bhatt and Soni and Kumar et al Using a Bayesian framework, Gurugopinath and Shobitha studied the performance of ED for spectrum sensing through an infinite series expression for the total error probability. Based on the generalized α − κ − μ and α − η − μ fading models, the performance analysis of maximum eigenvalue‐based detector (MED) for spectrum sensing was considered in the work of Samudhyatha et al Using the moment generating function (MGF) approach, Huang and Yuan derived expressions for the average probability of detection as well as the AUC for cooperative spectrum sensing (CSS) based on the α − κ − μ distribution.…”

Section: Introductionmentioning

confidence: 99%

An integrated performance evaluation of ED‐based spectrum sensing over α−κ−μ and α−κ−μ‐Extreme fading channels

Rasethuntsa

Kumar

2019

Trans Emerging Tel Tech

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This paper presents a comparative performance evaluation of energy detector (ED) under the assumption that the propagation signal experiences fading modeled by the nonlinear generalized α−κ−μ or α−κ−μ‐Extreme fading channels. Novel closed‐form analytical expressions for the average probability of detection and the average area under the receiver operating characteristic (ROC) curve (AUC) are derived in terms of the now highly prevalent bivariate Fox H‐function under single‐user spectrum sensing, cooperative spectrum sensing, and square law selection diversity reception. The results derived in the present work are generic as both channel models are compound distributions containing as special cases several other well‐known fading models such as the Nakagami‐m, Rice, the one‐sided Gaussian distribution, and the Weibull distribution, among others. The performance of ED is evaluated by employing the traditional ROC and AUC curves over additive white Gaussian noise by varying model parameters and observing system performances. Analytical results are verified via Monte Carlo simulations in MATLAB®.

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“…α − κ − μ fading have recently become popular as it includes some realistic fading channels such as κ − μ , Rayleigh, Nakagami‐ m , Weibull, and Rice . Furthermore, there are only a few studies that deal with the performance of wireless communications over α − κ − μ fading channels . In the works of Moualeu et al and Salahat and Hakam, analytical expressions for OP, average error rate, and CC of a single‐input–single‐output system were derived in the presence of α − κ − μ fading.…”

Section: Introductionmentioning

confidence: 99%

“…In the works of Moualeu et al and Salahat and Hakam, analytical expressions for OP, average error rate, and CC of a single‐input–single‐output system were derived in the presence of α − κ − μ fading. The second‐order statistics of α − κ − μ distribution were considered in the work of Papazafeiropoulos and Kotsopoulos, whereas Samudhyatha et al and Gurugopinath and Shobitha studied on the spectrum sensing over α − κ − μ fading channels.…”

Section: Introductionmentioning

confidence: 99%

On the performance of dual‐branch selection diversity combining in α−κ−μ fading environments

Kapucu

2019

Trans Emerging Tel Tech

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In this paper, the performance of a dual-branch selection combining (SC) system is analyzed over − − fading channels. First, an outage probability (OP) expression is presented for a dual-branch diversity with the SC scheme in − − fading channels by using cumulative distribution function (CDF). By using the probability density function (PDF) and CDF of − − distribution, the PDF of total output instantaneous signal-to-noise ratio (SNR) is obtained which is subsequently utilized for the analysis of the considered system. Based on this PDF expression, bit error probability (BEP) expressions are derived with the use of a simple and tight upper bound approximation of Gaussian Q-function. In addition to these, we propose analytical effective capacity (EC) expressions for a dual-branch SC system under − − fading conditions. Then, we present simplified expressions for the OP, BEP, and EC at high SNR. Finally, we illustrate the OP, BEP (for binary phase shift keying and quadrature phase shift keying modulation formats), and EC performances for different configurations of , , and parameters. In order to validate our analytical results, comparisons between the exact simulations and analytical results are also provided.Trans Emerging Tel Tech. 2019;30:e3719.wileyonlinelibrary.com/journal/ett

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Energy-based Bayesian spectrum sensing over α-κ-μ fading channels

Cited by 9 publications

References 19 publications

An Enriched α − μ Model as Fading Candidate

An Enriched α − μ Model as Fading Candidate

An integrated performance evaluation of ED‐based spectrum sensing over α−κ−μ and α−κ−μ‐Extreme fading channels

On the performance of dual‐branch selection diversity combining in α−κ−μ fading environments

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