Correlation-Aware User Selection for Cooperative Spectrum Sensing in Cognitive Radio Ad Hoc Networks

Cacciapuoti, Angela Sara; Akyildiz, Ian F.; Paura, Luigi

doi:10.1109/jsac.2012.120208

Cited by 114 publications

(81 citation statements)

References 15 publications

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“…An adaptation algorithm is proposed such that network utility is maximized even in case of dynamic changes in the network. Cacciapuoti, Akyildiz et al (2012) have also proposed a correlated based spectrum sensing scheme. The proposed distributed approach recommends selection of non-correlated users for cooperation during spectrum sensing.…”

Section: Research Issues In Crahnmentioning

confidence: 99%

A Study of Research Trends and Issues in Wireless Ad Hoc Networks

Islam¹,

Shaikh

2016

Mobile Computing and Wireless Networks

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Ad hoc network enables network creation on the fly without support of any predefined infrastructure. The spontaneous erection of networks in anytime and anywhere fashion enables development of various novel applications based on ad hoc networks. However, at the same ad hoc network presents several new challenges. Different research proposals have came forward to resolve these challenges. This chapter provides a survey of current issues, solutions and research trends in wireless ad hoc network. Even though various surveys are already available on the topic, rapid developments in recent years call for an updated account on this topic. The chapter has been organized as follows. In the first part of the chapter, various ad hoc network's issues arising at different layers of TCP/IP protocol stack are presented. An overview of research proposals to address each of these issues is also provided. The second part of the chapter investigates various emerging models of ad hoc networks, discusses their distinctive properties and highlights various research issues arising due to these properties. We specifically provide discussion on ad hoc grids, ad hoc clouds, wireless mesh networks and cognitive radio ad hoc networks. The chapter ends with presenting summary of the current research on ad hoc network, ignored research areas and directions for further research.Keywords: Ad hoc network, research issues, ad hoc grid, ad hoc cloud, wireless mesh network, cognitive radio ad hoc network INTRODUCTIONDuring last few years, extensive developments have been observed in the domain of wireless network. Different communication technologies i.e. general packet radio service (GPRS), enhanced data rates for GSM evolution (EDGE) and worldwide interoperability for microwave access (WIMAX) etc. have evolved and newer form of computing devices i.e. personal digital assistant (PDA), tablets and smart phones are appearing in the market. The wireless computing has progressed from 1G to 4G communication networks. During this progression, various modes of wireless networking have emerged. The simplest form of wireless networking is communication among two or more fixed hosts in open air. The conventional television system operates on this mode. Another approach is wireless networking with access point. There are different wireless hosts that are allowed to move while the basic infrastructure is supported by set of fixed nodes called base stations or access points. However, this approach doesn't provide the flexibility to be used in emergency situations requiring quick deployment or networking in adversarial surroundings. The evolution of technologies has lead to development a new mode of wireless networking where the nodes arrange themselves on the fly in the form of a network without any infrastructure support. Such networks are called ad hoc networks. Properties of ad hoc networkFormally, Ad hoc Network G(N,E) is defined as a collection of nodes N={n 1 ,n 2 ,n 3 ,…} connected by edges ‫ܧ‬ ⊆ ܰ × ܰ (Islam and Shaikh 2012). The nodes are us...

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Section: Research Issues In Crahnmentioning

confidence: 99%

A Study of Research Trends and Issues in Wireless Ad Hoc Networks

Islam¹,

Shaikh

2016

Mobile Computing and Wireless Networks

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“…Then, they jointly optimize the guard distance and the sensing time to maximize the reuse of spectrum opportunities. In [10], the authors develop a correlation-aware user selection to address the dynamic changes in the spatial correlation experienced by mobile CR users, with the objective to increase the performance of cooperative spectrum sensing. The proposed user selection is location-unaware, fully distributed and adaptive.…”

Section: Related Workmentioning

confidence: 99%

Optimal Primary-User Mobility Aware Spectrum Sensing Design for Cognitive Radio Networks

Cacciapuoti

Akyildiz

Paura

2013

IEEE J. Select. Areas Commun.

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Abstract-A key issue of the spectrum sensing functionality in Cognitive Radio (CR) networks is the ability of tuning the sensing time parameters, i.e., the sensing time and the transmission time, according to the Primary User (PU) network dynamics. In fact, these parameters influence both the spectrum sensing efficiency and the PU interference avoidance. This issue becomes even more challenging in presence of PU mobility. In this paper, an optimal spectrum sensing design for mobile PU scenarios is proposed with the aim to achieve the following important features: i) to determine the optimal mobility-aware transmission time, i.e., the transmission time value that jointly maximizes the spectrum sensing efficiency and satisfies the PU interference constraint; ii) to determine the optimal mobility-aware sensing time threshold, i.e., the maximum sensing time value assuring efficient spectrum sensing. First, closed-form expressions of both the optimal transmission time and the optimal sensing time threshold are analytically derived for a general PU mobility model. Then, the derived expressions are specialized for two widely adopted mobility models, i.e., the Random Walk mobility Model with reflection and the Random Way-Point mobility Model. Practical rules for the sensing parameter tuning are provided with reference to the considered mobility models. The analytical results are finally validated through simulations.

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“…As an illustration, consider the example network shown in Figure 1. Here, if the SBS has to select a set of 3 SUs for sensing, then some choices for selecting the sensing nodes are as follows: (i) Selecting nodes with maximum individual accuracy: say, {n 3 , n 4 , n 5 }; (ii) Selecting nodes with maximum distance among nodes: say, {n 1 , n 3 , n 6 }; (iii) Selecting nodes with high RSSI value of the primary user signal [6]: say, {n 3 , n 4 , n 5 }; and (iv) Selecting nodes with minimum correlation among them [7]: say, {n 1 , n 3 , n 6 }. However, it is important to select secondary users so that both the PUs can be detected with high accuracy.…”

Section: The Objective Of This Paper Is To Design a Solution To Enablmentioning

confidence: 99%

“…This may leave other PUs on the same channel as unmonitored (as seen in example network in Section I). Authors in [16], [12], [7] have proposed using correlation to select the best nodes for sensing. However, they do not consider the effect of probability of false positives on the accuracy of readings.…”

Section: Related Workmentioning

confidence: 99%

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DISCERN: Cooperative whitespace scanning in practical environments

Bansal

Chen

Sinha

2013

2013 Proceedings IEEE INFOCOM

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Abstract-Cognitive radio devices opportunistically operate on whitespace channels, provided those channels are not in use by the primary users. This opportunistic reusing of channels requires secondary users to perform fast and efficient sensing to determine the unused channels. Although individual secondary clients may be unwilling to frequently sense all the channels, their density could be exploited for tasking the individual devices to collaboratively extract useful information on spectrum usage. It is critical to determine how the sensing tasks should be assigned to different secondary users. This is particularly challenging in practical networks due to the variability in the sensing accuracy of different users that may arise because of multipath effects on the signal and varying distances from the primary transmitters. Further, presence of multiple Primary Users on the same channel makes it challenging to select the best users for sensing. Finally, to reduce the sensing overhead, it is beneficial to limit the number of channel sensing tasks that can be performed within a given time period. We propose a novel metric that captures the sensing accuracy of a given sensing assignment. Using our metric, we design an algorithm DISCERN for computing the sensing assignment that maximizes the sensing accuracy. Our algorithm is the first to take into account the limitations in practical networks. Our work is motivated by experimental measurements. Tracedriven simulations show that DISCERN increases the sensing accuracy by at least 30%. Theoretical analysis shows that the sensing assignment computed by DISCERN performs within 63% of the exponential-time optimal solution.

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Correlation-Aware User Selection for Cooperative Spectrum Sensing in Cognitive Radio Ad Hoc Networks

Cited by 114 publications

References 15 publications

A Study of Research Trends and Issues in Wireless Ad Hoc Networks

A Study of Research Trends and Issues in Wireless Ad Hoc Networks

Optimal Primary-User Mobility Aware Spectrum Sensing Design for Cognitive Radio Networks

DISCERN: Cooperative whitespace scanning in practical environments

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