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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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Book ChapterDOI
08 Aug 2016
TL;DR: Novel routing metrics that estimate both the future spectrum availability and the average transmission time are introduced and two routing algorithms for multi-hop CRNs are proposed that attempt to reduce the probability of spectrum handoff and rerouting upon PU’s arrival.
Abstract: Cognitive radio networks (CRNs) are considered as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows secondary users (SUs) to utilize wireless spectrum resources which belong to primary users (PUs) with minimal interference to PUs. Due to the dynamic spectrum availability and quality, routing for SUs in multi-hop CRNs is a challenge. In this paper, we introduce novel routing metrics that estimate both the future spectrum availability and the average transmission time. Then, we propose two routing algorithms for multi-hop CRNs that attempt to reduce the probability of spectrum handoff and rerouting upon PU’s arrival. Finally, we conduct simulations, whose results show that our proposed algorithms lead to a significant performance improvement over the reference algorithm.

14 citations

Proceedings ArticleDOI
12 Nov 2012
TL;DR: A trust based security algorithm enabling cognitive radio to access the distributed computation, storage, and resources available in cognitive radio environment is proposed, based on the location awareness and distance between the mobile user.
Abstract: Wireless spectrum is precious, so there are always requirements of dynamic shared spectrum techniques and an intelligent wireless communication system, such as Cognitive Radio Network (CRN). Although, CRN provides awareness, reliability, adaptability, high quality services and flexibility to its users but it has also opens the door for lots of threats and attacks. In this paper, various possible attacks and threats along with the possible solutions are discussed. This article has also proposed a trust based security algorithm enabling cognitive radio to access the distributed computation, storage, and resources available in cognitive radio environment. Proposed trust based algorithm is based on the location awareness and distance between the mobile user. Trust is calculated from the actual received power and trust metrics are determined by combining the requirements of the trustworthiness and the QoS of the links with the route. In this algorithm, three dimensional (3D) coordinates system is used to verify the location of the primary user and malicious user. Proposed algorithm has defined the trust factor of various users on the basis of trustworthiness. The simulation results have demonstrated the effectiveness of the proposed trust algorithm for all three types of user i.e. primary, secondary and malicious user, in the terms of both security and performance.

14 citations

Journal ArticleDOI
TL;DR: This study proposes two distinct data models for creating ML-ready datasets using feature engineering and evaluated the accuracy and efficiency of each ML algorithm over these datasets, which show a maximum prediction accuracy of 96.2% using MLP algorithm.

14 citations

Journal ArticleDOI
TL;DR: This paper proposes two procedures to construct the network in situations where only historical data are available, and a regularization method that is coupled with a nonsynaptic backpropagation algorithm that outperforms the LTCN model and other state-of-the-art methods in terms of accuracy.
Abstract: Modeling a real-world system by means of a neural model involves numerous challenges that range from formulating transparent knowledge representations to obtaining reliable simulation errors. However, that knowledge is often difficult to formalize in a precise way using crisp numbers. In this paper, we present the long-term grey cognitive networks which expands the recently proposed long-term cognitive networks (LTCNs) with grey numbers. One advantage of our neural system is that it allows embedding knowledge into the network using weights and constricted neurons. In addition, we propose two procedures to construct the network in situations where only historical data are available, and a regularization method that is coupled with a nonsynaptic backpropagation algorithm. The results have shown that our proposal outperforms the LTCN model and other state-of-the-art methods in terms of accuracy.

14 citations

01 Jan 2013
TL;DR: The basics and origin of software defined radio, cognitive radio, Cognitive radio network, cognitive cycle, performance metrics and the concept of cross layer design are covered.
Abstract: Radio spectrum is the most valuable resource in wireless communication. The cognitive radio and cognitive based networking are transforming the static spectrum allocation based communication systems in to dynamic spectrum allocation. Cognitive radios are intelligent devices with ability to sense environmental conditions and can change its parameters according to the requirements to get the optimized performance at the individual nodes or at network level. This paper covers the basics and origin of software defined radio, cognitive radio, cognitive radio network, cognitive cycle, performance metrics and the concept of cross layer design. The performance metrics explain the node and network level performance measurements. This paper also covers the different network paradigms.

14 citations


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