New analytical expressions for the performance metrics of wireless communication system over Weibull/Lognormal composite fading

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In this paper, we present an analytical framework to analyse the error probability and the channel capacity of the inverse gamma (I-Gamma) shadowed fading channel. First, the work discusses the utility of the I-Gamma over log-normal (LN) and gamma fading models where the closeness of I-Gamma with other existing shadowing models is carried out. Utilising the probability density function (PDF) of the I-Gamma shadowed fading channel, various metrics of the communication system, namely, the average symbol error probability (SEP), the channel capacity under optimal rate adaptation (ORA), channel inversion with fixed rate (CIFR), and truncated CIFR (TIFR) are derived. Further, the work is extended to derive a novel selection combining (SC) PDF, and the analytical results for the SEP and the channel capacity of SC diversity are presented. Furthermore, we also provide simpler asymptotic expressions for the average SEP. In addition, the simplified high and low signal-to-noise-ratio (SNR) solutions to channel capacity are also provided. The derived mathematical formulations have been endorsed by comparing with Monte Carlo simulations. KEYWORDSBessel K, bit error rate, capacity, distribution, fading Int J Commun Syst. 2019;32:e4083.wileyonlinelibrary.com/journal/dac

“…The instantaneous SEP expression for different noncoherent modulation formats is defined as follows [11,Eq. (18)]: where the parameter A n and B n are defined in Table 3.…”

Section: Average Sep Of Noncoherant Modulation Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Error probability and channel capacity analysis of wireless system over inverse gamma shadowed fading channel with selection diversity

Pant

Chauhan

Soni

2019

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“…Outage probability is defined as the probability of receiving the signal less than desired threshold ( γ 0 ) and can be expressed as

F_{Y} false(γ_{0} false) = true \int_{0}^{γ_{0}} f_{Y} false(γ false) d γ .

…”

Section: Performance Analysismentioning

confidence: 99%

“…The relative measure of the fading severity occurs in wireless communication transmission over the fading distribution is known as AOF. The closed‐form expression for the AOF is deduced by plugging the appropriate rth moment expressions in the definition

A O F = \frac{E false[Y^{2} false]}{{false(E false[Y false] false)}^{2}} - 1

as, eq. (9)

A O F = \frac{normalΓ false(m false) normalΓ false(n false) normalΓ ((), n + \frac{2}{λ}) normalΓ ((), m + \frac{2}{λ})}{{((), normalΓ ((), n + \frac{1}{λ}) normalΓ ((), m + \frac{1}{λ}))}^{2}} - 1 .

…”

Section: Performance Analysismentioning

confidence: 99%

“…Therefore, faithful assessment of the communication system performance required accurate estimation of the channel characteristics. A variety of channel statistics that encompasses both these phenomena has been extensively addressed in the open literature . Bit error rate (BER) analysis of K distribution, an alternative and mathematical less complex structure that closely approximate Rayleigh‐Log‐normal (RLN) composite fading channel, has been carried out in Abdi and Kaveh .…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of wireless communication system over nonidentical cascaded generalised gamma fading channels

Chauhan¹,

Rana

Kumar

et al. 2019

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Summary Multiplicative fading statistics usually encountered in different radio propagation environments. In this context, we evaluate and analyse the performance of a wireless communication system over the nonidentical cascaded generalised Gamma Fading Channels, also known as generalised Bessel‐K fading channel. To this end, the closed‐form expressions for the amount of fading (AOF), the outage probability (OP), the average symbol error probability (SEP), and the channel capacity are derived. In addition approximate expressions for the average SEP with maximal ratio combining (MRC) diversity are also provided. The low‐ and high‐power solutions for the channel capacity are also provided. Furthermore, simplified asymptotic average SEP expressions for MRC and selection combining (SC) are presented to gain the system performance with diversity. The proposed methodologies provide more flexibility to accommodate different radio propagation scenarios. To examine the accuracy of the proposed solutions, numerical and simulation results are compared and shown to fit for variety of fading parameters.

Development of analytical model for energy detectors with SC and MRC diversity over Inverse‐Gamma fading

Maurya

Srivastava

Chauhan

et al. 2020

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Summary An ever‐escalating demand for wireless applications has caused great concern for the proper exploitation of the accessible radio spectrum. Cognitive radio materializes as an auspicious remedy to the present‐day crisis of spectral congestion, by detecting the licensed primary user (PU). This is accomplished with the assistance of the spectrum sensing technique, which provides an indication of the presence of PU over the spectrum. Energy detection is one of the prevailing spectrum sensing techniques due to its low implementation complexity. In the present work, the performance of an energy detector (ED) over Inverse‐Gamma (I‐Gamma) fading distribution is examined. Initially, a closed‐form expression of the probability density function for I‐Gamma distribution with maximal ratio combining diversity reception is derived. Following it, an investigation of an ED‐based cognitive radio device is carried out in the form of the average probability of detection (PD) and average area under the receiver operating characteristic curve (AUC). In addition, we also present a performance analysis of an ED with selection combining diversity. Optimization of the detection threshold is also executed alongside the low signal‐to‐noise ratio analysis. In the end, the resulting expression of the PD is exploited to examine the functioning of cooperative spectrum sensing within the erroneous environment. The validation of derived mathematical forms has been confirmed by comparing it with the Monte‐Carlo simulation and exact numerical results.