Energy-Efficient Multichannel Cooperative Sensing Scheduling With Heterogeneous Channel Conditions for Cognitive Radio Networks

Eryigit, Salim; Bayhan, Suzan; Tuǧcu, Tuna

doi:10.1109/tvt.2013.2247070

Cited by 74 publications

(71 citation statements)

References 18 publications

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“…The concept of excessive channel switching should be optimized to reduce energy consumption in CR networks [27,30].To enable secondary user to achieve maximum energy efficiency an optimal sensing order design has been proposed by applying a dynamic programming solution [28][29].…”

Section: Energy Consumption (Ec)mentioning

confidence: 99%

A Study on Quantitative Parameters of Spectrum Handoff in Cognitive Radio Networks

J¹,

Murugesh²

2017

IJWMN

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The innovation of wireless technologies requires dynamic allocation of spectrum band in an efficient manner. This has been achieved by Cognitive Radio (CR) networks which allow unlicensed users to make use of free licensed spectrum, when the licensed users are kept away from that spectrum. The cognitive radio makes decision, switching from primary user to secondary user and vice-versa, based on its built-in interference engine. It allows secondary users to makes use of a channel based on its availability i.e. on the absence of the primary user and they should vacate the channel once the primary user re-enters and continue their communication on another available channel and this process in the cognitive radio isknown as spectrum mobility. The main objective of spectrum mobility is that, there is no interruption caused due to the channel occupied by secondary users and maintains a good quality of service. In order to achieve better spectrum mobility, it is mandatory to choose an effective spectrum handoff strategy with the capability of predicting spectrum mobility. The handoff strategy with its parameters and its impact is an important concept in spectrum mobility but fairly explored. In this paper an empirical study on quantitative parameters involved in spectrum mobility prediction are discussed in detail. These parameters are studied extensively because they play a vital role in the spectrum handoff process moreover the impact of these parameters in various handoff methods can be used to predict the effectiveness of the system.

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Section: Energy Consumption (Ec)mentioning

confidence: 99%

A Study on Quantitative Parameters of Spectrum Handoff in Cognitive Radio Networks

J¹,

Murugesh²

2017

IJWMN

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“…S is the maximum number of sensor nodes in a subset that satisfies the false alarm constraint [28,29]. Hence, from equation (7), S is given as max max log(1 )…”

Section: Subset Formationmentioning

confidence: 99%

“…Time duration for sensing is a function of SNR [29]. It means, for a given detection probability and a given false alarm probability, a sensor node with a comparatively clean channel causing a higher SNR takes less time for sensing an event.…”

Section: A Minimizing Energy Consumption During the Sensing Stagementioning

confidence: 99%

“…It means, for a given detection probability and a given false alarm probability, a sensor node with a comparatively clean channel causing a higher SNR takes less time for sensing an event. The time duration for sensing by the j-th node in a subset can be expressed in terms of SNR, detection probability, and false alarm probability [29] as follows: 2 11 ( ) ( ) 2 1…”

Section: A Minimizing Energy Consumption During the Sensing Stagementioning

confidence: 99%

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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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“…In [19], the authors studied energy-efficient CR systems by jointly determining the sensing and transmission durations. An energy-efficient multichannel cooperative sensing scheduling with heterogeneous channel conditions was analyzed in [20].…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient design of channel sensing in cognitive radio networks

Zhang

et al. 2015

Computers & Electrical Engineering

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Energy-Efficient Multichannel Cooperative Sensing Scheduling With Heterogeneous Channel Conditions for Cognitive Radio Networks

Cited by 74 publications

References 18 publications

A Study on Quantitative Parameters of Spectrum Handoff in Cognitive Radio Networks

A Study on Quantitative Parameters of Spectrum Handoff in Cognitive Radio Networks

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

Energy-efficient design of channel sensing in cognitive radio networks

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