The Impact of Channel Randomness on Coverage and Connectivity of Ad Hoc and Sensor Networks

Miorandi, Daniele; Altman, Eitan; Alfano, G.

doi:10.1109/twc.2007.060842

Cited by 101 publications

(90 citation statements)

References 44 publications

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“…In all cases, ξ = 10 dB, and this corresponds to keeping the SINR threshold fixed. The figure suggests that the presence of lognormal shadowing improves the connectivity properties of the network, as predicted by the results in [24,25]. Furthermore, the link probability of success is monotonically increasing in the lognormal spread σ so that it can be concluded that, even though the presence of a deep fades impacts the received power on the link, it has globally a beneficial impact on the link SINR.…”

Section: The Log-normal Fading Link Modelmentioning

confidence: 57%

Cross-Layering between Physical Layer and Routing in Wireless Ad-Hoc Networks

Dricot

Ferrari

Doncker

2009

Communication and Networking

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Abstract.Routing is a key issue in wireless ad-hoc networks. The goal of an efficient routing strategy is to set up routes so that the overall quality of communications will be the best possible. While the Open Systems Interconnection (OSI) reference model advocates for a clear separation of routing, access, and physical layers, in this paper we show that in scenarios with faded communications, cross-layer interactions have to be carefully considered. More precisely, we compare the performance of the Ad-hoc On-demand Distance Vector (AODV) routing algorithm with that of one of its physical layer-oriented variants, denoted as AODVϕ . It will be clearly shown that no single routing strategy is always optimal and that an intelligent adaptation should be performed.

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Section: The Log-normal Fading Link Modelmentioning

confidence: 57%

Cross-Layering between Physical Layer and Routing in Wireless Ad-Hoc Networks

Dricot

Ferrari

Doncker

2009

Communication and Networking

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“…To begin with, with the introduction of mission-critical WSN applications, various researchers investigated the probability of full connectivity in ad-hoc networks to identify and prevent the occasions that a node is isolated from the rest of the network [3], [4]. One of the first works on this subject is [3] in which the connectivity and the impact of mobility in a large set of nodes is investigated.…”

Section: Related Workmentioning

confidence: 99%

“…One of the first works on this subject is [3] in which the connectivity and the impact of mobility in a large set of nodes is investigated. The same topic is extended in [4] by taking the channel randomness into account.…”

Section: Related Workmentioning

confidence: 99%

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Connectivity Analysis in Clustered Wireless Sensor Networks Powered by Solar Energy

Mekikis

Kartsakli

Antonopoulos

et al. 2018

IEEE Trans. Wireless Commun.

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Emerging 5G communication paradigms, such as machine-type communication, have triggered an explosion in ad-hoc applications that require connectivity among the nodes of wireless networks.Ensuring a reliable network operation under fading conditions is not straightforward, as the transmission schemes and the network topology, i.e., uniform or clustered deployments, affect the performance and should be taken into account. Moreover, as the number of nodes increases, exploiting natural energy sources and wireless energy harvesting (WEH) could be the key to the elimination of maintenance costs, while also boosting immensely the network lifetime. In this way, zero-energy wireless-powered sensor networks (WPSNs) could be achieved, if all components are powered by green sources. Hence, designing accurate mathematical models that capture the network behavior under these circumstances is necessary to provide a deeper comprehension of such networks. In this paper, we provide an analytical model for the connectivity in a large-scale zero-energy clustered WPSN under two common transmission schemes, namely unicast and broadcast. The sensors are WEH-enabled, while the network components are solar-powered and employ a novel energy allocation algorithm. In our results, we evaluate the tradeoffs among the various scenarios via extensive simulations and identify the conditions that yield a fully connected zero-energy WPSN.

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“…This parameter m is called the 'shape factor' of the Nakagami-m or the gamma distribution. The value results in the widespread Rayleigh-fading model [28], while values of m less than one correspond to fading more severe than Rayleigh fading and values of m greater than one correspond to fading less severe than Rayleigh fading. Where, X i, i = 1,2,………n are independent and identically distributed (i.i.d.)…”

Section: Nakagami-m Fading Modelmentioning

confidence: 99%

Impact of Nakagamim Fading Model on Multihop Mobile Ad Hoc Network

Tarique¹,

Tanvir²

2011

IJCA

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Several theoretical and experimental based models have been proposed to predict the fading envelope of the received signal in multipath condition. In this paper, we considered a model named Nakagami-m model. Nakagami-m can model a variety of fading environments, where it closely approximates the Nakagami-q (Hoyt) and the Nakagami-n (Rice) models, and has the Rayleigh and one sided Gaussian models as special cases. This model provides the best fit to land-mobile system like wireless mobile ad hoc Network (MANET). Under Nakagami-m fading model, received packet may not be clearly understood by the receiving node, which affects the routing protocol as well as the medium access control protocol of a network. The severity of Nakagami-m fading model on the network performance has been presented in this paper which is demonstrated via simulation results. Simulation results illustrate that the performance of a network may become unable to meet the expectation if Nakagami-m fading model is used in contrast to the simple two-ray model. A physical layer solution and a Medium Access Control (MAC) layer solution been proposed in this paper to overcome the effects of Nakagami-m fading model. Simulation results prove that these two solutions condense the Nakagami-m fading effect and improve network performance.

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The Impact of Channel Randomness on Coverage and Connectivity of Ad Hoc and Sensor Networks

Cited by 101 publications

References 44 publications

Cross-Layering between Physical Layer and Routing in Wireless Ad-Hoc Networks

Cross-Layering between Physical Layer and Routing in Wireless Ad-Hoc Networks

Connectivity Analysis in Clustered Wireless Sensor Networks Powered by Solar Energy

Impact of Nakagamim Fading Model on Multihop Mobile Ad Hoc Network

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