Performance analysis of power line communication systems with diversity combining under correlated lognormal fading and Nakagami noise

Abou-Rjeily, Chadi

doi:10.1049/iet-com.2016.0802

Cited by 11 publications

(16 citation statements)

References 30 publications

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“…For SISO–PLC systems corrupted by Nakagami‐ m noise, an approximate expression of the conditional BER was derived in [5] as follows:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ P_{e | h}^{(SISO)} = K_{m, 1}^{'} Γ (m - \frac{1}{2}, \frac{m h^{2} A^{2}}{normalΩ}), \end{matrix}

where

normalΓ false(., . false)

stands for the upper incomplete gamma function while

K_{m, 1}^{'}

is a constant that can be calculated as follows:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ K_{m, M}^{'} ≜ \frac{1}{2} {(][, \frac{K_{m} Γ (m - (1 / 2))}{\sqrt{π} Γ (m)})}^{M} \frac{1}{Γ (m - (1 / 2))}; M = 1, 2, \end{matrix}

where

K_{m}

is a constant that depends on m as follows [5]:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ K_{m} ≜ \sum_{k = 0}^{+ \infty} α_{m, k} \frac{Γ (m - k - (1 / 2))}{Γ (m - (1 / 2))} \end{matrix}

with

α_{...}

…”

Section: Performance Analysis Of Siso and Mimo Systemsmentioning

confidence: 99%

“…In the case of MRC, the conditional BER can be approximated by the following expression [5]:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ P_{e | h}^{(MRC)} = K_{m, 2}^{'} Γ (m - \frac{1}{2}, \frac{m {()(, h_{1}^{2} + h_{2}^{2})}^{2} A^{2}}{(h_{1}^{2} + h_{2}^{2}) Ω}), \end{matrix}

where

K_{m, 2}^{'}

is defined in (9).…”

Section: Performance Analysis Of Siso and Mimo Systemsmentioning

confidence: 99%

“…The Nakagami noise model was adopted in a large number of contributions that targeted the performance analysis of PLC systems. The probability density function (PDF) of the real part of the Nakagami‐ m background noise was derived in [4] for

m < 1

and later extended to the case

m \geq 1

Section: Introductionmentioning

confidence: 99%

“…The probability density function (PDF) of the real part of the Nakagami‐ m background noise was derived in [4] for

m < 1

and later extended to the case

m \geq 1

in [5]. The derived PDF was used in [6] for evaluating the performance of single‐channel PLC systems in the absence of fading and in [5] for evaluating the performance of two‐channel PLC systems in the presence of lognormal fading. The bit error rate (BER) of binary phase shift keying (BPSK) was studied in [7, 8] under Nakagami background noise and in [9] under a mixture of Nakagami background noise and Middleton impulsive noise.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Power line communications under Rayleigh fading and Nakagami noise: novel insights on the MIMO and multi‐hop techniques

Abou-Rjeily

2018

IET Communications

Self Cite

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“…For SISO–PLC systems corrupted by Nakagami‐ m noise, an approximate expression of the conditional BER was derived in [5] as follows:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ P_{e | h}^{(SISO)} = K_{m, 1}^{'} Γ (m - \frac{1}{2}, \frac{m h^{2} A^{2}}{normalΩ}), \end{matrix}

where

normalΓ false(., . false)

stands for the upper incomplete gamma function while

K_{m, 1}^{'}

is a constant that can be calculated as follows:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ K_{m, M}^{'} ≜ \frac{1}{2} {(][, \frac{K_{m} Γ (m - (1 / 2))}{\sqrt{π} Γ (m)})}^{M} \frac{1}{Γ (m - (1 / 2))}; M = 1, 2, \end{matrix}

where

K_{m}

is a constant that depends on m as follows [5]:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ K_{m} ≜ \sum_{k = 0}^{+ \infty} α_{m, k} \frac{Γ (m - k - (1 / 2))}{Γ (m - (1 / 2))} \end{matrix}

with

α_{...}

…”

Section: Performance Analysis Of Siso and Mimo Systemsmentioning

confidence: 99%

“…In the case of MRC, the conditional BER can be approximated by the following expression [5]:

\begin{matrix} right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3pt \\ P_{e | h}^{(MRC)} = K_{m, 2}^{'} Γ (m - \frac{1}{2}, \frac{m {()(, h_{1}^{2} + h_{2}^{2})}^{2} A^{2}}{(h_{1}^{2} + h_{2}^{2}) Ω}), \end{matrix}

where

K_{m, 2}^{'}

is defined in (9).…”

Section: Performance Analysis Of Siso and Mimo Systemsmentioning

confidence: 99%

m < 1

and later extended to the case

m \geq 1

Section: Introductionmentioning

confidence: 99%

“…The probability density function (PDF) of the real part of the Nakagami‐ m background noise was derived in [4] for

m < 1

and later extended to the case

m \geq 1

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Power line communications under Rayleigh fading and Nakagami noise: novel insights on the MIMO and multi‐hop techniques

Abou-Rjeily

2018

IET Communications

Self Cite

View full text Add to dashboard Cite

“…The latest research hotspots model power line channel fading into a lognormal (LogN) model [16]. In [9], the effect of AF forwarding on the average channel capacity in the PLC channel is studied based on Bernoulli-Gaussian impulse noise and fading.…”

Section: Introductionmentioning

confidence: 99%

Improved EXIT Algorithm Based on Gaussian Mixture Model and its Application to LDPC Construction in Coding Cooperative Systems With Hybrid Fading

Chen

et al. 2020

IEEE Access

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In this study, an EXIT algorithm based on Gaussian mixture coding and multi-dimensional node information calculation is proposed. The objective is to solve the problem of performance analysis of cooperative communication and LDPC code construction under hybrid fading and impulse noise. First, Gaussian mixture model estimation of the decoding initialization information is performed by the expectation maximized algorithm. In addition, key parameters, such as weight, mean, and variance of the Gaussian mixture model are obtained. Then, the multi-dimensional information processing is performed on the variable node and the check node information in the traditional EXIT algorithm based on the multi-dimensional Gaussian mixture model and system symmetry analysis. Finally, the objective function of LDPC code optimization is constructed, the constraints are given, and the optimal LDPC code degree distribution is obtained by the differential evolution algorithm. The simulation results show that compared with the traditional regular and other irregular LDPC codes, the newly constructed degree distribution has better performance in waterfall characteristics and error floor characteristics. Such distribution provides a necessary method to analyze and optimize the performance of cooperative coding system under hybrid media or hybrid fading. INDEX TERMS Expectation maximization (EM), Gaussian mixture, hybrid fading, low-density paritycheck (LDPC) codes, multi-dimensional EXIT.

show abstract

Superimposing theta structure on a generalized modular relation

Dixit

Kumar

2021

Res Math Sci

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Performance analysis of power line communication systems with diversity combining under correlated lognormal fading and Nakagami noise

Cited by 11 publications

References 30 publications

Power line communications under Rayleigh fading and Nakagami noise: novel insights on the MIMO and multi‐hop techniques

Power line communications under Rayleigh fading and Nakagami noise: novel insights on the MIMO and multi‐hop techniques

Improved EXIT Algorithm Based on Gaussian Mixture Model and its Application to LDPC Construction in Coding Cooperative Systems With Hybrid Fading

Superimposing theta structure on a generalized modular relation

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