Ergodic Capacity of Generalized Fading Channels With Mobility

Aalo, Valentine A.; Bithas, Petros S.; Efthymoglou, George P.

doi:10.1109/ojvt.2021.3131321

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…The authors of [9] analysed the physical layer security over αη-µ fading scenario in terms of the lower bound secure outage probability (SOP). In [10], the ACC of a mobile user over α-η-µ fading channel was investigated via employing the random waypoint (RWP) mobility approach. The composite of α-η-µ/Gamma and α-η-λ-µ/Gamma distributions were investigated in [11] and [12], respectively, with applications to the ACC with optimum rate adaptation (ORA) and constant transmit power, channel inversion with fixed rate (CIFR), and truncated inversion and fixed rate (TIFR) adaptive transmission protocols.…”

Section: Introductionmentioning

confidence: 99%

Extended α-η-μ Fading Distribution: Statistical Properties and Applications

2022

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In this paper, the impact of the non-linearity of the propagation medium on the extended η-µ fading distribution is studied. In particular, the extended α-η-µ fading model in which the parameter α represents the non-linearity of the propagation environment is presented via providing the exact and asymptotic of the statistical properties, namely, the probability density function (PDF), cumulative distribution function (CDF), and generalized-moment generating function (G-MGF). To this effect, exact closedform mathematically tractable expressions of the outage probability (OP), average symbol error probability (ASEP), amount of fading (AoF), channel quality estimation index (CQEI) and effective rate (ER) are obtained. The asymptotic behaviour at high average signal-to-noise (SNR) values is also analysed to gain further insights into the influence of the index α on the performance metrics of the wireless communication systems. Moreover, the average channel capacity (ACC) under different adaptive transmission techniques, such as, optimum rate and adaptation (ORA), capacity of the channel with inversion and fixed rate (CIFR), and truncated inversion and fixed rate (TIFR) are derived. The validation of the derived expressions is verified via comparing the numerical results with the Monte-Carlo simulations as well as some previous works for different scenarios.INDEX TERMS Extended α-η-µ fading, statistical properties, outage probability, average symbol error probability, effective rate, average channel capacity.

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Section: Introductionmentioning

confidence: 99%

Extended α-η-μ Fading Distribution: Statistical Properties and Applications

2022

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“…The impact of mobility on system performance was presented in [31] for a more complex η-µ fading distribution used to model the dynamic behavior of non-homogeneous fading, while the mobile receiver was described using the RWP mobility model. The analytical results for the ergodic channel capacity for generalized fading distribution were presented in [41], and the effects of mobility were evaluated in [42] for the k-µ generalized fading model (including Nakagami-m and Rician fading distribution as special cases); in both papers, the movement of the mobile receiver was described using the RWP model. Another mobile wireless network with Rician fading distribution was discussed in [43], and closed-form expressions for the outage probability in an interference-limited environment with a Rician fading channel were derived.…”

Section: Related Workmentioning

confidence: 99%

“…In [44], the impact of mobility on a generalized α-µ fading distribution was analyzed. The authors of [28,31,41,45] analyzed the effects of mobility on the performances of communication systems by engaging the RWP model, while the influence of the RD mobility model was assessed in [46,47]. A comparison of these two models' impact on performance was described in [27,48].…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility

Kozić

Blagojević

Cvetković

et al. 2023

Sensors

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The relentless expansion of communications services and applications in 5G networks and their further projected growth bring the challenge of necessary spectrum scarcity, a challenge which might be overcome using the concept of cognitive radio. Furthermore, an extremely high number of low-power devices are introduced by the concept of the Internet of Things (IoT), which also requires efficient energy usage and practically applicable device powering. Motivated by these facts, in this paper, we analyze a wirelessly powered underlay cognitive system based on a realistic case in which statistical channel state information (CSI) is available. In the system considered, the primary and the cognitive networks share the same spectrum band under the constraint of an interference threshold and a maximal tolerable outage permitted by the primary user. To adopt the system model in realistic IoT application scenarios in which network nodes are mobile, we consider the randomly moving cognitive user receiver. For the analyzed system, we derive the closed-form expressions for the outage probability, the outage capacity, and the ergodic capacity. The obtained analytical results are corroborated by an independent simulation method.

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“…Success probability performance of D2D communication system over Rician faded channel using stochastic geometry is discussed by authors in [13]. In [14], authors discussed ergodic channel capacity (ECC) of various generalized fading channels for mobile communication based on the random waypoint mobility model. Authors derived analytical expressions for the ECC in the mobile communication.…”

Section: Introductionmentioning

confidence: 99%

Relay-Assisted D2D Communication over Extended η-μ Fading Channels

Hussain

Mehdi

Saleem

2022

Mobile Information Systems

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In this paper, two cases of Device-to-Device (D2D) communication over a recently introduced extended η-μ fading channel are analyzed. Case A considers a direct D2D communication. While in case B, amplify-and-forward relay-assisted D2D communication is discussed. The effects of cochannel interference at the relay and D2D destination are also included. To combat fading, selection combining- and maximal ratio combining-based diversity schemes are also incorporated at the receiver. Power harvesting based on power splitting technique is also engulfed. Expressions of success and outage probabilities are derived with the help of characteristic function approach. Success and outage probability expressions are functions of path loss, distance between various devices and channel parameters. Based on these expressions, numerical results are presented and discussed.

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Ergodic Capacity of Generalized Fading Channels With Mobility

Abstract: where he is currently a Professor. His main research interests are in the area of digital communication systems with emphasis on the performance analysis of wireless systems in the presence of fading, interference, and mobility.

Cited by 4 publications

References 18 publications

Extended α-η-μ Fading Distribution: Statistical Properties and Applications

Extended α-η-μ Fading Distribution: Statistical Properties and Applications

Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility

Relay-Assisted D2D Communication over Extended η-μ Fading Channels

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