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McLeish Distribution: Performance of Digital Communications Over Additive White McLeish Noise (AWMN) Channels

dc.contributor.authorYilmaz, Ferkan
dc.date.accessioned2026-06-27T14:27:40Z
dc.date.issued2020
dc.description.abstractThe objective of this article is to propose and statistically validate a more general additive non-Gaussian noise distribution, which we term McLeish distribution, whose random nature can model different impulsive noise environments commonly encountered in practice and provides a robust alternative to Gaussian noise distribution. In particular, for the first time in the literature, we establish the laws of McLeish distribution and therefrom derive the laws of the sum of McLeish distributions by obtaining closed-form expressions for their probability density function (PDF), cumulative distribution function (CDF), complementary CDF ((CDF)-D-2), moment-generating function (MGF) and higher-order moments. Further, for certain problems related to the envelope of complex random signals, we extend McLeish distribution to complex McLeish distribution and thereby propose circularly/elliptically symmetric (CS/ES) complex McLeish distributions with closed-form PDF, CDF, MGF and higher-order moments. For generalization of one-dimensional distribution to multi-dimensional distribution, we develop and propose both multivariate McLeish distribution and multivariate complex CS/ES (CCS/CES) McLeish distribution with analytically tractable and closed-form PDF, CDF, (CDF)-D-2 and MGF. In addition to the proposed McLeish distribution framework and for its practical illustration, we theoretically investigate and prove the existence of McLeish distribution as additive noise in communication systems. Accordingly, we introduce additive white McLeish noise (AWMN) channels. For coherent/non-coherent signaling over AWMN channels, we propose novel expressions for maximum a priori (MAP) and maximum likelihood (ML) symbol decisions and thereby obtain closed-form expressions for both bit error rate (BER) of binary modulation schemes and symbol error rate (SER) of various M-ary modulation schemes. Further, we verify the validity and accuracy of our novel BER/SER expressions with some selected numerical examples and some computer-based simulations.en
dc.description.urihttps://doi.org/10.1109/access.2020.2967742
dc.identifier.doi10.1109/access.2020.2967742
dc.identifier.endpage19195
dc.identifier.issn2169-3536
dc.identifier.startpage19133
dc.identifier.urihttps://hdl.handle.net/20.500.14981/60866
dc.identifier.volume8
dc.identifier.wos000525387900001
dc.language.isoeng
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofIEEE ACCESS
dc.rightsopenAccess
dc.subjectAdditive white McLeish noise channels
dc.subjectcoherent
dc.subjectnon-coherent signaling
dc.subjectconditional bit error rate
dc.subjectconditional symbol error rate
dc.subjectMcLeish distribution
dc.subjectMcLeish Q-function
dc.subjectmultivariate McLeish distribution
dc.subjectNon-Gaussian noise
dc.subjectBIT-ERROR-PROBABILITY
dc.subjectSTATISTICAL-PHYSICAL MODELS
dc.subjectIMPULSIVE NOISE
dc.subjectWIRELESS NETWORKS
dc.subjectCOGNITIVE RADIO
dc.subjectPOISSON FIELD
dc.subjectNARROW-BAND
dc.subjectTHERMAL AGITATION
dc.subjectLIGHTWAVE SYSTEMS
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleMcLeish Distribution: Performance of Digital Communications Over Additive White McLeish Noise (AWMN) Channels
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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