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Cognitive network

About: Cognitive network is a research topic. Over the lifetime, 4213 publications have been published within this topic receiving 107093 citations.


Papers
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Proceedings ArticleDOI
02 Aug 2006
TL;DR: The first wireless Internet standard that is based on Cognitive Radio techniques, namely IEEE 802.22 is described, and its performance with respect to one aspect of cognitive radios, namely operation over multiple frequency channels is discussed.
Abstract: Spectrum agile radios, also known as cognitive radios, have received much attention from researchers recently. Although the promise of cognitive radios in terms of increased access to spectrum was widely recognized very early, specific applications that utilize cognitive radio techniques have only recently began to develop.In this paper we briefly describe the first wireless Internet standard that is based on Cognitive Radio techniques, namely IEEE 802.22, and discuss its performance with respect to one aspect of cognitive radios, namely operation over multiple frequency channels.Furthermore, we discuss the evolution of cognitive radios beyond IEEE 802.22 by identifying some of the key factors that affect it, which in turn guide our research in cognitive radio PHY and MAC design.

33 citations

Journal ArticleDOI
TL;DR: A virtualized and cognitive network architecture is proposed, wherein network functionalities are implemented via software instances in the cloud, and the underlying architecture can adapt to the application of interest as well as to changes in channels and traffic conditions.
Abstract: Cellular networks have preserved an application agnostic and base station (BS) centric architecture1 for decades. Network functionalities (e.g. user association) are decided and performed regardless of the underlying application (e.g. automation, tactile Internet, online gaming, multimedia). Such an ossified architecture imposes several hurdles against achieving the ambitious metrics of next generation cellular systems. This article first highlights the features and drawbacks of such architectural ossification. Then the article proposes a virtualized and cognitive network architecture, wherein network functionalities are implemented via software instances in the cloud, and the underlying architecture can adapt to the application of interest as well as to changes in channels and traffic conditions. The adaptation is done in terms of the network topology by manipulating connectivities and steering traffic via different paths, so as to attain the applications’ requirements and network design objectives. The article presents cognitive strategies to implement some of the classical network functionalities, along with their related implementation challenges. The article further presents a case study illustrating the performance improvement of the proposed architecture as compared to conventional cellular networks, both in terms of outage probability and handover rate.

33 citations

Journal ArticleDOI
TL;DR: The proposed method aims at evaluating the various candidate configurations that a cognitive transmitter may operate in, by associating a capability e.g., achievable bit-rate, with each of these configurations, and increases the certainty about the configuration evaluations by considering past experience and knowledge through the use of Bayesian networks.
Abstract: This paper proposes enhancements to the channel(-state) estimation phase of a cognitive radio system. Cognitive radio devices have the ability to dynamically select their operating configurations, based on environment aspects, goals, profiles, preferences etc. The proposed method aims at evaluating the various candidate configurations that a cognitive transmitter may operate in, by associating a capability e.g., achievable bit-rate, with each of these configurations. It takes into account calculations of channel capacity provided by channel-state estimation information (CSI) and the sensed environment, and at the same time increases the certainty about the configuration evaluations by considering past experience and knowledge through the use of Bayesian networks. Results from comprehensive scenarios show the impact of our method on the behaviour of cognitive radio systems, whereas potential application and future work are identified.

33 citations

01 Jan 2009
TL;DR: In this article, the authors developed a framework for applying cognitive radio technology to mobile WiMAX net-works to increase capacity and simplify network operations, where base stations are equipped with sensitive detectors and assign channels to subscriber stations dynamically based on spectrum availability.
Abstract: Cognitive radios have the ability to sense the radio spectrum environment and to switch dynamically to available frequency ranges. Mobile WiMAX is an emerging wireless networking standard that could potentially benefit from cognitive radio technology. We develop a framework for applying cognitive radio technology to mobile WiMAX net- works to increase capacity and simplify network operations. In the proposed cognitive WiMAX architecture, base stations are equipped with sensitive detectors and assign channels to subscriber stations dynamically based on spectrum availability. Power control is employed to increase frequency reuse in conjunction with spectrum sensing. Using computer simula- tion, we evaluate the performance of Bcognitive channel assignment( relative to conventional dynamic channel assign- ment. Our numerical results show that cognitive radios can substantially increase the capacity of emerging WiMAX net- works by exploiting inherent spectrum hole opportunities. The key performance parameters determining the achievable capacity of cognitive WiMAX networks are the detection and interference range, which depend in turn on characteristics of the radio propagation environment.

33 citations

Proceedings ArticleDOI
08 Dec 2008
TL;DR: The use of swarm intelligence is proposed as a way to dynamically find and manage control channels in cognitive radio networks and is able to independently identify viable control channels and adapt in presence of changing spectrum.
Abstract: In recent years, a variety of algorithms for cognitive radio networks have been proposed. Many of these algorithms rely on the exchange of control information among the cognitive radio nodes and often require the presence of a globally available control channel. This requirement however poses a problem in a practical deployment: First, due to spectrum fluctuations such common control channel may be unknown at deployment stage. Second, when designating a fixed, dedicated control channel (for example in licensed spectrum), this will increase costs and expose vulnerability to the operation of the cognitive radio network. Thus, to overcome this difficulty, control channels should be dynamically assigned and managed in cognitive radio networks. In this paper, we propose the use of swarm intelligence as a way to dynamically find and manage such control channels in cognitive radio networks. The system we describe is able to independently identify viable control channels and adapt in presence of changing spectrum. We formalize the problem of control channel assignments to the multi-commodity flow problem, measure the performance of our approach in a hardware implementation and software simulation and compare the results against the theoretically optimal solution.

33 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202317
202234
202175
2020104
2019121
2018134