SER Performance Improvement in OFDM System Over Generalized K-fading Channel

Tiwari, Keerti; Bharti, Bindu; Saini, Davinder S.

doi:10.1007/978-981-10-6005-2_20

Cited by 2 publications

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“…A review of recent applications revealed that the use could be classified into six major areas. Modeling fading channels, shadowing effects [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ] and attenuation in wireless networks [ 12 ]; Other forms of modeling such as: binary error modeling [ 13 ], beamforming [ 14 ], spatial deployment modeling [ 15 ], delay [ 16 ], source localization [ 17 ], line of sight interference power [ 18 ], atmospheric turbulence [ 19 , 20 ] and color texture characterization [ 21 ]. Modeling by the direct use of gamma distribution fit via parameter estimation [ 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

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Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

Okagbue

Adamu

Anake

2020

Heliyon

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The use of quantile functions of probability distributions whose cumulative distribution is intractable is often limited in Monte Carlo simulation, modeling, and random number generation. Gamma distribution is one of such distributions, and that has placed limitations on the use of gamma distribution in modeling fading channels and systems described by the gamma distribution. This is due to the inability to find a suitable closed-form expression for the inverse cumulative distribution function, commonly known as the quantile function (QF). This paper adopted the Quantile mechanics approach to transform the probability density function of the gamma distribution to second-order nonlinear ordinary differential equations (ODEs) whose solution leads to quantile approximation. Closed-form expressions, although complex of the QF, were obtained from the solution of the ODEs for degrees of freedom from one to five. The cases where the degree of freedom is not an integer were obtained, which yielded values closed to the R software values via Monte Carlo simulation. This paper provides an alternative for simulating gamma random variables when the degree of freedom is not an integer. The results obtained are fast, computationally efficient and compare favorably with the machine (R software) values using absolute error and Kullback-Leibler divergence as performance metrics.

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Section: Introductionmentioning

confidence: 99%

“…Modeling fading channels, shadowing effects [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ] and attenuation in wireless networks [ 12 ];…”

Section: Introductionmentioning

confidence: 99%

Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

Okagbue

Adamu

Anake

2020

Heliyon

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MIMO Systems in a Composite Fading and Generalized Noise Scenario: A Review

Tiwari¹

2021

ENG

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: Multiple-input multiple-output (MIMO) systems have been endorsed to enable future wireless communication requirements. The efficient system designing appeals an appropriate channel model, that considers all the dominating effects of wireless environment. Therefore, some complex or less analytically acquiescent composite channel models have been proposed typically for single-input single-output (SISO) systems. These models are explicitly employed for mobile applications, though, we need a specific study of a model for MIMO system which can deal with radar clutters and different indoor/outdoor and mobile communication environments. Subsequently, the performance enhancement of MIMO system is also required in such scenario. The system performance enhancement can be examined by low error rate and high capacity using spatial diversity and spatial multiplexing respectively. Furthermore, for a more feasible and practical system modeling, we require a generalized noise model along with a composite channel model. Thus, all the patents related to MIMO channel models are revised to achieve the near optimal system performance in real world scenario. This review paper offers the methods to improve MIMO system performance in less and severe fading as well as shadowing environment and focused on a composite Weibull-gamma fading model. The development is the collective effects of selecting the appropriate channel models, spatial multiplexing/detection and spatial diversity techniques both at the transmitter and the receivers in the presence of arbitrary noise.

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SER Performance Improvement in OFDM System Over Generalized K-fading Channel

Cited by 2 publications

References 18 publications

Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

MIMO Systems in a Composite Fading and Generalized Noise Scenario: A Review

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