Outage probability and ergodic channel capacity of underlay device-to-device communications over $$\kappa -\mu$$ shadowed fading channels

Singh, Indrasen; Singh, Niharika

doi:10.1007/s11276-019-02164-7

Cited by 10 publications

(8 citation statements)

References 25 publications

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“…Here,

ϖ

features channel power that includes path loss,

μ

describes the number of multipath clusters,

m

characterizes shadowing severeness, and

κ

stands for the Rician‐

K

coefficient that characterizes the light of sight impact. Consequently, this paradigm generalizes many essential distributions (viz., Rice, Nakagami‐

m

, one‐sided Gaussian, Hoyt, and Rayleigh) and precisely features realistic wireless channels 24 …”

Section: Introductionmentioning

confidence: 97%

“…For evaluating and analyzing the system performance practically, all these conditions must be integrated in a channel paradigm that well matches field measurements. Numerous works have conceded that the

κ - μ

shadowed fading paradigm features concurrently propagation conditions of wireless channels, namely, fading, shadowing, and path loss 24–26 . Remarkably, this paradigm flexibly and straightforwardly quantifies distinct severeness levels of fading, path loss, and shadowing by a set of parameters

((), ϖ, μ, m, κ)

.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous works have conceded that the κ À μ shadowed fading paradigm features concurrently propagation conditions of wireless channels, namely, fading, shadowing, and path loss. [24][25][26] Remarkably, this paradigm flexibly and straightforwardly quantifies distinct severeness levels of fading, path loss, and shadowing by a set of parameters ϖ, μ, m, κ ð Þ . Here, ϖ features channel power that includes path loss, μ describes the number of multipath clusters, m characterizes shadowing severeness, and κ stands for the Rician-K coefficient that characterizes the light of sight impact.…”

mentioning

confidence: 99%

“…Consequently, this paradigm generalizes many essential distributions (viz., Rice, Nakagami-m, one-sided Gaussian, Hoyt, and Rayleigh) and precisely features realistic wireless channels. 24 In summary, NLESONs can achieve high spectrum-and-energy efficiencies, meeting stringent system design specifications. Moreover, by applying the adaptive operation at SS, exploiting the diversity gain from direct channels (PS-PD and PS-SD), and leveraging the primary interference cancelation, NLESONs can attain high performance.…”

mentioning

confidence: 99%

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Performance evaluation of nonlinear energy scavenging overlay networks

Le-Thanh

Ho-Van

2022

Int J Communication

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This paper investigates a nonlinear energy scavenging overlay network (NLESON) wherein a primary source (PS) communicates with a primary destination (PD) probably under aid of a secondary source (SS) who communicates with a secondary destination (SD). SS is a power-constrained device, and thence, its operation relies on energy harvested by a practical nonlinear energy scavenger. To support PS and exploit the harvested energy at most, SS adaptively switches between single and superposition modes where the single mode allows SS to transmit solely its signal with the entire harvested energy and the superposition mode asks SS to transmit both-its signal and amplified primary signal-with different power fractions. Moreover, for increasing the probability of successfully decoding primary signal at PD and SD, which then reduces considerably primary interference on secondary signal in the superposition mode, we leverage both direct channels (PS-PD and PS-SD) and apply both signal combining paradigms (maximum ratio combining and selection combining).The outage/throughput performance of the NLESON is assessed quickly through the proposed closed-form expressions over κ À μ shadowed fading channels. Various results exposed the effectiveness of the aforementioned solutions for the NLESON and their flexibility in controlling system performance. K E Y W O R D Samplify-and-forward, direct channel, feedback, nonlinear energy scavenging, overlay networks, shadowed fading and motivationsAdvanced communication networks (viz., and Fifth-Generation [5G]) serve a vast quantity of users and hence pressuring significantly communication infrastructure in supplying adequately bandwidth and power. [1][2][3][4] Such a circumstance stimulates researches on initiatives to utilize energy and spectrum efficiently.On one hand, the spectrum can be exploited efficiently with the cognitive radio technology, which enables secondary users (SUs) to opportunistically transmit on the spectrum of primary users (PUs). Toward this end, SUs can operate with underlay, overlay, and interweave paradigms. 5 In both the overlay and underlay paradigms, PUs and SUs operate simultaneously while in the interweave one, SUs operate only when PUs are idle. Nevertheless, the underlay and overlay paradigms are different in that the former controls the transmit power of SUs such that the interference they induce

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“…Here,

ϖ

features channel power that includes path loss,

μ

describes the number of multipath clusters,

m

characterizes shadowing severeness, and

κ

stands for the Rician‐

K

coefficient that characterizes the light of sight impact. Consequently, this paradigm generalizes many essential distributions (viz., Rice, Nakagami‐

m

, one‐sided Gaussian, Hoyt, and Rayleigh) and precisely features realistic wireless channels 24 …”

Section: Introductionmentioning

confidence: 97%

κ - μ

((), ϖ, μ, m, κ)

.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Performance evaluation of nonlinear energy scavenging overlay networks

Le-Thanh

Ho-Van

2022

Int J Communication

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“…Moreover, the κ-μ shadowed fading can be applied to different systems including IoT links [28], satellite channels [29], and underwater links [30]. According to the proposed mobile communication model with κ-μ shadowed fading, the authors of [31] studied the transmission performance by analyzing OP and ergodic channel capacity (ECC). e statistical characteristics of different shadowed κ-μ fading were derived in [32], where the closed-form PDF and cumulative distribution function (CDF) for envelope and signal-to-noise ratio (SNR) were obtained, respectively.…”

Section: Introductionmentioning

confidence: 99%

Secrecy Analysis of Cognitive Radio Networks over Generalized Fading Channels

Sun

Bie

et al. 2020

Security and Communication Networks

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At present, the fifth generation (5G) communication networks are in the time of large-scale deployment principally because its characteristics consists of large bandwidth, fast response, and high stability. As a partner of 5G, the Internet of Things (IoT) involves billions of devices around the world, which can make the wireless communication environment more intelligent and convenient. However, the problem that cannot be ignored is the physical layer security of 5G-IoT networks. Based on this, we perform a security analysis of cognitive radio networks (CRN) for IoT, where the CRN is the single-input multiple-output (SIMO) model experiencing κ-μ shadowed fading with multiple eavesdroppers. To analyze the confidentiality of the system under consideration, we analyze the security performance for the considered IoT systems with the help of the derived secure outage probability (SOP) and probability of strictly positive secrecy capacity (SPSC). As a verification of the theoretical formula, Monte Carlo simulation is also provided. The results of great interest are the factors that can produce better security performance in high SNRs region which consist of smaller M, smaller k, and larger N, and larger μ, smaller IP, and smaller Rth.

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Performance evaluation of NOMA networks powered by harvested energy with antenna selection under $$\kappa -\mu $$ shadowed fading

Ho-Van

2024

Telecommun Syst

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Outage probability and ergodic channel capacity of underlay device-to-device communications over $$\kappa -\mu$$ shadowed fading channels

Cited by 10 publications

References 25 publications

Performance evaluation of nonlinear energy scavenging overlay networks

Performance evaluation of nonlinear energy scavenging overlay networks

Secrecy Analysis of Cognitive Radio Networks over Generalized Fading Channels

Performance evaluation of NOMA networks powered by harvested energy with antenna selection under $$\kappa -\mu $$ shadowed fading

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