Cognitive network

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

Method for ensuring security and privacy in a wireless cognitive network

Abstract: In some embodiments, authentication, confidentiality, and privacy are enhanced for a wireless network of cognitive radios by encryption of network management and control messages as well as data traffic, thereby protecting information pertaining to node identification, node location, node-sensed incumbent transmissions, CRN frequency channel selections, and such like. During initial network registration, a temporary ID can be issued to a node, and then replaced once encrypted communication has been established. This prevents association of initial, clear-text messages with later encrypted transmissions. Elliptic curve cryptography can be used for mutual authentication between subscribers and the base station. ECC-based implicit digital certificates can be embedded in co-existence beacons used by CRN nodes to coordinate use of frequency channels, thereby preventing denial of service attacks due to transmitting of falsified beacons. Similar certificates can be embedded within identity beacons used to protect certain incumbents from interference by the CRN.

Resource management for QoS support in cognitive radio networks

Abstract: Cognitive radio technology is a key enabler to reuse a finite, scarce, and expensive resource: the radio spectrum. Guaranteeing required levels of QoS to cognitive users and ensuring necessary protection to incumbent users are the two main challenges in opportunistic spectrum access. This article identifies the main requirements and challenges for QoS support in cognitive radio networks. A framework for a twofold cognitive manager is presented; one part managing spectrum availability on longer timescales and the other handling resource management on shorter timescales. This article gives particular focus to the functionalities of the latter cognitive manager related to resource management. Finally, we present a few key scenarios and describe how QoS can be managed with the proposed approach without disturbing the communications of incumbent users.

An Optimal Cross-Layer Framework for Cognitive Radio Network Under Interference Temperature Model

Abstract: This paper investigates the optimal scheduling of cognitive radio network links under an interference temperature (IT) model. A link layer model based on the IT model has been developed. A mathematical cross-layered model for the cognitive radio network link scheduling problem under the IT model is presented. The proposed cross-layered model optimizes the performance of the cognitive radio network across several network layers. The objective is to activate as many simultaneous primary/secondary links while the IT constraints are satisfied. The IT-based link layer scheduling can potentially increase the network performance. The proposed model advocates the potential benefits of adopting a location-aware and IT-based MAC protocol in modern wireless networks.

Cognitive Radio Technology Applications for Wireless and Mobile Ad Hoc Networks

Abstract: Dr. Natarajan Meghanathan is a tenured Associate Professor of Computer Science at Jackson State University, Jackson, MS. He graduated with a Ph.D. in Computer Science from The University of Texas at Dallas in May 2005. Dr. Meghanathan has published more than 140 peer-reviewed articles (more than half of them being journal publications). He has also received federal education and research grants from the U. S. National Science Foundation, Army Research Lab and Air Force Research Lab. Dr. Meghanathan has been serving in the editorial board of several international journals and in the Technical Program Committees and Organization Committees of several international conferences. His research interests are Wireless Ad hoc Networks and Sensor Networks, Graph Theory, Network and Software Security, Bioinformatics and Computational Biology. For more information, visit http://www.jsums.edu/cms/nmeghanathan. Released: June 2013 An Excellent Addition to Your Library!

Backoff Algorithm in Cognitive Radio MAC Protocol for Throughput Enhancement

Abstract: In this paper, we have explored a novel concept of the medium access control (MAC) protocol for the distributed cognitive radio network. We have implemented the backoff algorithm in the self-scheduled multichannel cognitive radio MAC (SMC-MAC) protocol for the contention solving among the cognitive users and, hence, reserve the licensed channels for data transmission. In this control channel protocol, the cognitive users share the sensing results with each other, and each channel is divided into four intervals such as idle, sensing–sharing, contention, and data transmission. However, the backoff algorithm has been implemented during the contention interval to enhance the number of successful users and, hence, has increased the throughput of cognitive radio network. The backoff algorithm has significantly minimized the competition and, hence, collision among the cognitive users while reserving the unutilized licensed channels.