Cognitive radio sensor networks

Akan, Özgür B.; Karli, O.; Ergül, Özgür

doi:10.1109/mnet.2009.5191144

Cited by 552 publications

(323 citation statements)

References 8 publications

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“…Recently, several studies on CR-WSN's protocols have been proposed and some of the papers also published which have already done a review on CRSN. Advantage and issues related to the CRSN have been discussed in [3,4]. The survey presented mainly concentrates on some of the origin cognitive frameworks and cognitive radio architectures/engines are compared.…”

Section: Related Workmentioning

confidence: 99%

“…Some of the issues that directly affect the energy efficiency or consumption are discussed herein [11] (packets collision, idle listening). Energy efficient design is required at each layer of the communication protocol stack [4]. The CR based physical layer extra task is spectrum sensing and altering the transmission parameters (like operating frequency, modulation, and power) according to spectrum negotiation and the decision by CR engine.…”

Section: Energy-efficient Protocol Designmentioning

confidence: 99%

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An Overview of Medium Access Control Protocols for Cognitive Radio Sensor Networks

Maisuria

Mehta²

2018

The 4th International Electronic Conference on Sensors and Applications

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-In recent year, the most emerging and growing field of research and development is "Internet of Things" (IoT). This is due to advancement in wireless sensor network (WSN) which operate in the unlicensed industrial, scientific and medical (ISM) spectrum band. However, many wireless technologies operate in the same unlicensed spectrum, make it overcrowded and hence resulted in spectrum scarcity among those bands, the performance of WSN will degrade as their popularity increases. According to FCC report, most of the licensed spectrum is underutilized, sharing of underutilized licensed spectrum among unlicensed devices is a promising solution to the spectrum scarcity issue. Cognitive Radio (CR) is one of the capable technology that allows sensor nodes (as a Secondary Users (SUs)) to detect and use the underutilized licensed spectrum temporarily when Primary Users (PUs) not using it. With recent advances in Cognitive Radio (CR) technology, possible to apply the Dynamic Spectrum Access (DSA) model in WSNs to get access to underutilized licensed spectrum, possibly with better propagation characteristics, but as the existing protocols and algorithms developed for CRNs and WSNs are not directly applicable to CR-based WSNs and required new protocols. In this paper, we present a survey on the novel design of CRbased MAC, identify the main advantages and challenges of using CR technology, and compare the different method of improving energy efficiency. We believe that CR-WSN is the next-generation WSN. In this paper, we also discussed the open issues to motivate new research interest in this field.

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Section: Related Workmentioning

confidence: 99%

Section: Energy-efficient Protocol Designmentioning

confidence: 99%

An Overview of Medium Access Control Protocols for Cognitive Radio Sensor Networks

Maisuria

Mehta²

2018

The 4th International Electronic Conference on Sensors and Applications

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“…Nevertheless, it is subject to failure when the sink node breaks down, and it suffers from high energy consumption as well as high end-to-end delay because of multi-hop transmissions to the CR. Akan et al [12] and Joshi et al [13], described a CR sensor network (CRSN) where the conventional wireless sensor nodes are equipped with CR functionality. The CRSN requires highly complicated sensor nodes, so the high cost of a CRSN makes it impractical.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Infrastructure Sensor Network for Ad Hoc Cognitive Radio Network

2016

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Abstract-We propose an energy-efficient network architecture that consists of ad hoc (mobile) cognitive radios (CRs) and infrastructure wireless sensor nodes. The sensor nodes within communications range of each CR are grouped into a cluster and the clusters of CRs are regularly updated according to the random mobility of the CRs. We reduce the energy consumption and the end-to-end delay of the sensor network by dividing each cluster into disjoint subsets with overlapped sensing coverage of primary user (PU) activity. Respective subset of a CR provides target detection and false alarm probabilities. Substantial energy efficiency is achieved by activating only one subset of the cluster, while putting the rest of the subsets in the cluster into sleep mode. Additional gain in energy efficiency is obtained by two promising propositions : selecting nodes from the active subset for actual sensing and switching the active subset to sleep mode by scheduling. The sensor nodes for actual spectrum sensing are chosen considering their respective time durations for sensing. Even the only active subset is switched to sleep mode for a certain number of time slots, utilizing the history of PU activity. We compare the proposed CR network with existing approaches to demonstrate the network performance in terms of the energy consumption and the end-to-end delay.Index Terms-ad hoc cognitive radio network, cluster and subsets, infrastructure sensor network, subset scheduling, spectrum sensing, sensor network-based spectrum sensing I. INTRODUCTIONCCORDING to the Federal Communications Commission (FCC), utilization of the statically assigned spectrum varies from 15% to 85%, depending upon spatio-temporal variations [1,2]. In order for a secondary user, which cannot be active when the primary user (PU) is active, to utilize the spectrum licensed to a PU, the activity of the PU should be closely monitored [3]. One possible approach is to use cognitive radio (CR) transceivers for spectrum sensing and sending their observations to a fusion center to determine the presence of the PU signal [4,5]. However, this approach incurs high cost and high energy consumption.A more appealing approach is to perform sensing via cost-effective and dedicated sensor network [6,7]. Use of the sensor network for spectrum sensing is being explored by regulatory bodies like the FCC, which has invited experts to draft proposals for the use of a sensor network with low cost/energy/delay for enhanced spectrum sensing [8]. Energy-efficient spectrum sensing by a sensor network offers advantages such as more effective detection of a weak PU signal (by location diversity of the sensor nodes) and better protection of the PU due to high reliability in detection. Furthermore, this approach is more appropriate for mobile CRs where cooperative spectrum sensing is more difficult in the absence of a fusion center and cooperation between the CR users cannot be easily achieved. However, there are still certain challenges/disadvantages in such a network, which are yet to be re...

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“…One promising solution is to exploit opportunistic spectrum access approaches via cognitive radios (CRs) [3] to circumvent the coexisting interference over the 2.4 GHz ISM band. As a smart combination of CR and WSN, cognitive radio sensor network (CRSN) is recently considered as one of the most attractive topics in the fields of both WSNs and CR networks [4].…”

Section: Introductionmentioning

confidence: 99%

Utility‐based opportunistic spectrum access for cognitive radio sensor networks: joint spectrum sensing and random access control

et al. 2016

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This study formulates a novel optimisation problem for joint spectrum sensing and random access control (JS 2 RAC) in cognitive radio sensor networks (CRSNs). The JS 2 RAC is formulated as a network utility maximisation problem, which aims to maximise the sum of utilities over all links in the network but subject to the primary user protection constraint, the energy constraint, and the physical constraint. Due to the non-separable and non-convex nature of the JS 2 RAC problem, the authors propose a primal-decomposition-based iterative (PDI) algorithm which decomposes the JS 2 RAC problem into a spectrum sensing subproblem and a random access control subproblem, and solve the two subproblems iteratively. Then, the authors prove the convergence of the PDI algorithm and show its distributed implementation in practice. Simulations demonstrate the fast convergence and the near-optimal nature of the PDI algorithm and show its significant improvement in the network utility of CRSNs in comparison with the method of optimising spectrum sensing and random access separately.

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Cognitive radio sensor networks

Cited by 552 publications

References 8 publications

An Overview of Medium Access Control Protocols for Cognitive Radio Sensor Networks

An Overview of Medium Access Control Protocols for Cognitive Radio Sensor Networks

Energy-Efficient Infrastructure Sensor Network for Ad Hoc Cognitive Radio Network

Utility‐based opportunistic spectrum access for cognitive radio sensor networks: joint spectrum sensing and random access control

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