The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared eta-mu variates, applicable to the output statistics of maxim...
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ISBN:
(纸本)9781467363372
The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared eta-mu variates, applicable to the output statistics of maximal ratio combining (MRC) receiver operating over eta-mu fading channels that includes the Hoyt and the Nakagami-m models as special cases, is presented in closed-form in terms of the Fox's (H) over bar function. Further analysis, particularly on the bit error rate via PDF-based approach, is also represented in closed form in terms of the extended Fox's (H) over bar function ((H) over cap). The proposed new analytical results complement previous results and are illustrated by extensive numerical and Monte Carlo simulation results.
The probability distribution function (PDF) and cumulative density function of the sum of L independent but not necessarily identically distributed gamma variates, applicable to maximal ratio combining receiver output...
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ISBN:
(纸本)9781467309714
The probability distribution function (PDF) and cumulative density function of the sum of L independent but not necessarily identically distributed gamma variates, applicable to maximal ratio combining receiver outputs or in other words applicable to the performance analysis of diversity combining receivers operating over Nakagami-m fading channels, is presented in closed form in terms of Meijer G-function and Fox (H) over bar -function for integer valued fading parameters and non-integer valued fading parameters, respectively. Further analysis, particularly on bit error rate via PDF-based approach, too is represented in closed form in terms of Meijer G-function and Fox (H) over bar -function for integer-order fading parameters, and extended Fox (H) over bar -function ((H) over cap) for non-integer-order fading parameters. The proposed results complement previous results that are either evolved in closed-form, or expressed in terms of infinite sums or higher order derivatives of the fading parameter m.
作者：
Imran Shafique AnsariFerkan YilmazMohamed-Slim AlouiniComputer
Electrical and Mathematical Sciences and Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST) Al-Khawarizmi Applied Math. Building (Bldg. #1) Thuwal 23955-6900 Makkah Province Kingdom of Saudi Arabia
The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared η-μ variates, applicable to the output statistics of maxima...
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ISBN:
(纸本)9781467363365
The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared η-μ variates, applicable to the output statistics of maximal ratio combining (MRC) receiver operating over η-μ fading channels that includes the Hoyt and the Nakagami-m models as special cases, is presented in closed-form in terms of the Fox's H function. Further analysis, particularly on the bit error rate via PDF-based approach, is also represented in closed form in terms of the extended Fox's H function (H). The proposed new analytical results complement previous results and are illustrated by extensive numerical and Monte Carlo simulation results.
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