A modeling framework for supporting and evaluating connectivity in cognitive radio ad hoc networks with beamforming

An, Beongku

doi:10.1007/s11276-016-1252-9

Cited by 10 publications

(4 citation statements)

References 12 publications

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“…In addition, that method is based on static network topology with full topological information of SUs and PUs, which may not always available in CRAHNs. Local connectivity of large scale CRAHNs, taken into account the influences of aggregated interference and beamforming were studied in [19] and [20], respectively. More importantly, the connectivity of CRAHNs in all aforementioned works is investigated in the viewpoint of connectivity of whole network (or the probability of having connected graph), and without taking into account the neighbouring node selection criteria in routing algorithm.…”

Section: Related Work and Motivationsmentioning

confidence: 99%

A Simulation Analysis of the Connectivity of Multi-hop Path between Two Arbitrary Nodes in Cognitive Radio Ad Hoc Networks

Dung¹,

Nguyen²,

Hoang³

2019

EAI Endorsed Transactions on Industrial Networks and Intelligen

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The connectivity of multi-hop path is one of the key factors that influence the performance of multi-hop wireless networks. In this paper, assuming that secondary users (SUs) and primary users (PUs), using same licensed frequency bands, are uniformly distributed in square network area, we investigate the connectivity of multi-hop path in cognitive radio ad-hoc networks (CRAHNs). Specifically, we propose an algorithm to find all available multi-hop paths between arbitrary source node and destination node in CRAHNs with random node distribution and PU activity. Then, we use statistical simulation method to intensively evaluate the connectivity of multi-hop path compared with that in conventional ad-hoc networks (AHNs) by using huge number of random network topologies with different network parameters such as the number of SUs and PUs, network size, network operating frequency, and the average active rates of PU. The simulation results reveal many interesting and distinguishing features of the connectivity of multi-hop path in CRAHNs. Moreover, from the simulation graphs in this paper, network designers can select optimal network parameters so that the reliability of network topology is high while saving network resources. Finally, the simulation results can be used to verify mathematical models of the connectivity of multi-hop path in CRAHNs in future research.

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Section: Related Work and Motivationsmentioning

confidence: 99%

A Simulation Analysis of the Connectivity of Multi-hop Path between Two Arbitrary Nodes in Cognitive Radio Ad Hoc Networks

Dung¹,

Nguyen²,

Hoang³

2019

EAI Endorsed Transactions on Industrial Networks and Intelligen

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“…Thus, using directional antennas in CRNs can significantly reduce the interference as indicated in [8]- [10]. However, most recent studies only consider using directional antennas at either PUs [9] or SUs [8], [10], [11] but not both. The partial deployment of directional antennas in CRNs cannot fully realise the benefits of directional antennas.…”

Section: A Related Work and Motivationmentioning

confidence: 99%

“…Different from omni-directional antennas, directional antennas can concentrate radio signals on desired directions and consequently reduce the interference. Thus, using directional antennas in CRNs can significantly reduce the interference as indicated in [8]- [10]. However, most recent studies only consider using directional antennas at either PUs [9] or SUs [8], [10], [11] but not both.…”

Section: A Related Work and Motivationmentioning

confidence: 99%

Connectivity of Underlay Cognitive Radio Networks With Directional Antennas

Wang

Dai

Georgiou

et al. 2018

IEEE Trans. Veh. Technol.

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In cognitive radio networks (CRNs), the connectivity of secondary users (SUs) is difficult to be guaranteed due to the existence of primary users (PUs). Most prior studies only consider cognitive radio networks equipped with omni-directional antennas causing high interference at SUs. We name such CRNs with omni-directional antennas as Omn-CRNs. Compared with an omni-directional antenna, a directional antenna can concentrate the transmitting/receiving capability at a certain direction, consequently resulting in less interference. In this paper, we investigate the connectivity of SUs in CRNs with directional antennas (named as Dir-CRNs). In particular, we derive closed-form expressions of the connectivity of SUs of both Dir-CRNs and Omn-CRNs, thus enabling tractability. We show that the connectivity of SUs is mainly affected by two constraints: the spectrum availability of SUs and the topological connectivity of SUs. Extensive simulations validate the accuracy of our proposed models. Meanwhile, we also show that Dir-CRNs can have higher connectivity than Omn-CRNs mainly due to the lower interference, the higher spectrum availability and the higher topological connectivity brought by directional antennas.

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“…It was shown that the probability of node isolation is improved compared with conventional CRAHNs using omnidirectional antennas due to the reduced PU-to-SU interference and the extended transmission range. A modeling framework for evaluating connectivity in CRAHNs where PUs are equipped with omnidirectional antennas while SUs are equipped with directional antennas, i.e., ULA and UCA antennas, was shown in [18]. It was concluded that UCA is the most suitable antenna for CRAHNs and the optimal number of elements at which the highest connectivity can be achieved is different for each type of directional antenna.…”

Section: Introductionmentioning

confidence: 99%

Connectivity Analysis of Cognitive Radio Ad-Hoc Networks with Multi-Pair Primary Networks

Choi

2019

Sensors

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In this paper, we study the connectivity of cognitive radio ad-hoc networks (CRAHNs) where primary users (PUs) and secondary users (SUs) are randomly distributed in a given area following a homogeneous Poisson process. Moreover, for the sake of more realistic CRAHNs, contrary to previous works in the literature, we consider the case that primary network is comprised of multiple communication pairs which are spatial-temporal distributed in the network area. We also take into consideration the differences in transmission range and interference range of both PUs and SUs. The connectivity of such CRAHN is studied from three viewpoints. First, we mathematically analyze the probability of isolated secondary transmitter and secondary receiver. Second, we derive the approximation expression of the link probability between two adjacent SUs. Third, we investigate the path connectivity between two arbitrary SUs by using the simulation analysis approach. The correctness of our mathematical expressions is confirmed by comparing analytical results with simulation results. The results in this paper provide insights into how multiple communication pairs in primary network affect the connectivity of secondary network, which can be useful guidelines for the design of CRAHNs.

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A modeling framework for supporting and evaluating connectivity in cognitive radio ad hoc networks with beamforming

Cited by 10 publications

References 12 publications

A Simulation Analysis of the Connectivity of Multi-hop Path between Two Arbitrary Nodes in Cognitive Radio Ad Hoc Networks

A Simulation Analysis of the Connectivity of Multi-hop Path between Two Arbitrary Nodes in Cognitive Radio Ad Hoc Networks

Connectivity of Underlay Cognitive Radio Networks With Directional Antennas

Connectivity Analysis of Cognitive Radio Ad-Hoc Networks with Multi-Pair Primary Networks

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