Channel allocation and reallocation for cognitive radio networks

Jiang, Tigang; Wang, Honggang; Leng, Supeng

doi:10.1002/wcm.1162

Cited by 13 publications

(8 citation statements)

References 23 publications

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“…One application is a QoEdriven cross-layer design for CR multimedia networks. A case study of cross-layer approach has been conducted in our previous work [13], [14] for second users (SUs) that have different QoE requirements. In multimedia communications, there are many types of traffic, such as voice, image, and video (i.e., variable bitrate (VBR), constant bitrate (CBR), etc.).…”

Section: Discussion On Applicationsmentioning

confidence: 99%

Implementation of Cognitive Radio Network Testbed for Multimedia Communications

DaSilva¹,

Ghising²,

Patil³

et al. 2019

ICST Transactions on Mobile Communications and Applications

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A cognitive radio is a form of wireless communication in which a transceiver can intelligently detect which communication channels are in use and which are not, and instantly move into vacant channels while avoiding occupied ones. This intelligently avoids interference amongst users and provides the ability to use up all available bandwidth on the RF spectrum. There are many ways in which the communication can be demonstrated. This paper examines how we have implemented a cognitive radio network testbed using software defined radios (SDRs) for multimedia communications, where components that have been traditionally implemented in hardware are instead implemented by means of software on a personal computer or embedded system to communicate and transfer a file between each other. We attempt to demonstrate potential use of SDRs for future multimedia applications.

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Section: Discussion On Applicationsmentioning

confidence: 99%

Implementation of Cognitive Radio Network Testbed for Multimedia Communications

DaSilva¹,

Ghising²,

Patil³

et al. 2019

ICST Transactions on Mobile Communications and Applications

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“…In this context, channel aggregation (also known as channel assembling) means that two or more idle channels are combined together as one channel to provide higher data rate and, thus, reduce the total transmission time of secondary elastic traffic calls [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. On the contrary, elastic traffic may flexibly adjust downward the number of assembled channels to provide, for instance, immediate access to secondary real-time traffic when needed [10][11][12][13][14][15][16][17][18][19][20][21][22][23]. 1 Additionally, other relevant mechanisms are identified in the literature to overcome the impact of service interruption of SUs in CRNs [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

“…Surprisingly, transmission delay has not been previously considered as performance metric [10][11][12][13][14][15][16][17][18][19][20][21][22][23]28]. Moreover, previous studies that address CRNs with heterogeneous traffic and spectrum adaptation [10][11][12][13][14][15][16][17][18][19][20][21][22][23] have not considered the use of call buffering, which is a relevant mechanism to exploit the elasticity of best effort traffic in benefit of both real-time and elastic secondary sessions. Exception of this are [28,33,34]; however, in these works, neither Erlang capacity nor transmission delay is considered.…”

Section: Introductionmentioning

confidence: 99%

Analysis and performance evaluation of resource management mechanisms in heterogeneous traffic cognitive radio networks

Castellanos-Lopez¹,

Cruz-Perez

Hernandez-Valdez³

et al. 2017

J Wireless Com Network

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In this paper, the Erlang capacity achieved by the separate or joint use of several resource management mechanisms commonly considered in the literature (spectrum aggregation, spectrum adaptation, call buffering, channel reservation, selective interruption, and preemptive prioritization) to mitigate the effects of secondary call interruptions in cognitive radio networks (CRNs) is evaluated and compared. Heterogeneous traffic is considered, and service differentiation between real-time and elastic (data) traffic is done in terms of their different delay tolerance characteristics. The aim of our investigation is to identify the most relevant resource management mechanisms to improve the performance of the considered networks. As such, both the individual and joint effect of each resource management mechanisms on system performance are evaluated with the objective of comparing the gains in capacity achieved by each resource management mechanism studied in this work. For this purpose, the different resource management mechanisms studied are carefully combined and, for each resulting strategy, optimization of its configuration is presented to maximize the achievable Erlang capacity. For the performance evaluation of the considered strategies in heterogeneous traffic CRNs, a general teletraffic analysis is developed. Numerical results show that spectrum adaptation and call buffering are the mechanisms that best exploit the elasticity of delay-tolerant traffic in heterogeneous traffic CRNs and, therefore, most significantly improve system performance.

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“…Through cognitive radio networks (CRNs), the dynamic spectrum access [6,7] can be easily implemented. An efficient allocation of bandwidth being one of the major concerns in CRNs [10,11] is dynamic in nature. It is widely used in health care and also in e-health environment [8].…”

Section: Introductionmentioning

confidence: 99%

“…The defense advanced research projects agency has also initiated a wireless network after next program aiming toward creating a flexible architecture for military communication, based on CRNs [5]. An efficient allocation of bandwidth being one of the major concerns in CRNs [10,11] is dynamic in nature. Signal to interference plus noise ratio (SINR) [12][13][14] also plays an important role for the efficient utilization of the channels.…”

Section: Introductionmentioning

confidence: 99%

CCRA: channel criticality based resource allocation in cognitive radio networks

Kumar

Minz

2015

Int J Communication

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In cognitive radio networks, signal to interference plus noise ratio (SINR) is a quantity that is used to analyze the bounds of the capacity of a channel. This is the reason for SINR being one of the important parameters toward evaluating the performance of spectrum sharing in every network. To maximize the channel utilization in any network, the SINR of a channel should be considered to be within a threshold. This also leads to lesser power consumption, and the quality of service for the licensed users is maintained. Further, reduced SINR leads to an improvement in the quality of communication in the network. In this paper, a graph theoretic measure for the efficient utilization of channels in cognitive radio networks has been proposed and is named as channel criticality based resource allocation (CCRA). Using the SINR as the weight of the graph, a novel concept of channel criticality has also been introduced in this work. The proposed CCRA technique has also been compared with the existing interference aware channel assignment (IACA) technique in terms of the channel utilization. Through simulations, the CCRA has been observed to outperform the IACA scheme. The average channel utilization of the proposed CCRA was observed to have increased by 8%, when the secondary users were introduced in the network as compared with the IACA technique. Copyright Int. J. Commun. Syst. 2017; 30: e3012 V. KUMAR AND S. MINZThe betweenness of the link k for the source and destination pair .a; b/ is given by of 12 6

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Channel allocation and reallocation for cognitive radio networks

Cited by 13 publications

References 23 publications

Implementation of Cognitive Radio Network Testbed for Multimedia Communications

Implementation of Cognitive Radio Network Testbed for Multimedia Communications

Analysis and performance evaluation of resource management mechanisms in heterogeneous traffic cognitive radio networks

CCRA: channel criticality based resource allocation in cognitive radio networks

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