Cognitive network

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

Modeling and Analysis Framework for Multi-Interface Multi-Channel Cognitive Radio Networks

Abstract: The concept of a multi-interface multi-channel cognitive radio is both novel and promising. Indeed, such opportunistic access to the spectrum, over multiple channels in a simultaneous manner, will provide much higher data rates and better seamless communication while decreasing the possibility of interference to licensed users. In this vein, this paper proposes a detailed modeling and analysis of multi-interface multi-channel cognitive radio networks. The analytical efforts lead to the representation of each cognitive node with a 2-D Markov chain. Among the findings of the proposed modeling and analysis is the probability mass function of the secondary user (SU)'s queue length, from which any higher moment can be extracted. In addition, the stability condition, beyond which the network cannot be considered operative any longer, is derived. Statistical tests are conducted to determine the characteristics of the queue length's tail distribution. The accuracy of the analytical results is corroborated with simulation experiments. The proposed modeling is fairly practical as it takes into account issues such as sensing faults and channel imperfections, asynchronism among SUs, distance, and the primary activity level. In addition, the model is useful for the performance analysis and design of other types of cognitive networks as well, including cognitive-radio-based wireless regional area networks.

Metacognition and the next generation of cognitive radio engines

Abstract: Much of the previous research on cognitive radio has focused on developing algorithms based on artificial neural networks, the genetic algorithm, and reinforcement learning, each with its pros and cons. In this research, we present a new approach based on metacognition. We believe that the metacognitive framework can be the foundation for the next generation of CRs and further the performance improvements in CR. In this work, we present the elements involved in metacognitive radio, discuss the challenges in their development, present solutions to the challenges along with a possible meta-CR architecture, and show results from our implementation. Each cognitive engine (CE) algorithm has strengths and limitations that make it more suitable for certain operating scenarios (channel conditions, operating objective, available hardware, etc.) than other algorithms. A meta-CE can adapt faster and improve performance by exploiting the characteristics and expected performance of the individual CE algorithms. It understands the operational scenarios and utilizes the most appropriate algorithm for the current operational scenario by switching between the algorithms or adjusting them as necessary.

Cognitive tactical network models

Abstract: Unlike commercial MANET applications, tactical networks are typically hierarchical and involve heterogeneous types of radio communications. Future tactical networks also require cognitive functions across the protocol stack to exploit scarce spectrum and dynamically adapt functions and configuration settings. In this work we highlight the need for novel design tools for cognitive tactical networks. We define a system design model that will provide the foundation for generic network design problem formulations via the use of cognitive techniques covering both dynamic frequency adaptations and machinelearning- related aspects of cognition. We use the system model to identify several potential cognitive design knobs and describe how the different design knobs can potentially be adjusted at different timescales of operation. These knobs are used in formulating a cognitive network design problem. Finally, we discuss how a network designer can potentially benefit from the proposed model result, a cognitive network design toolset we have recently developed.

Analysing the development of cooperation in MANETs using evolutionary game theory

Abstract: A wireless mobile ad hoc network is an autonomous system of mobile nodes, which have to cooperate in packet relaying in order to provide the necessary network functionality. Packet relaying based on reciprocity generates strong cooperation incentives even among purely self-regarding nodes. The necessary distinction between selfish and cooperative participants is provided to a node by its trust system. In this article we analyse the particular case where a reputation system is not present in the network, i.e. nodes use solely their local trust systems. In such a case, whether the cooperation is based on direct or on indirect reciprocity, depends on the information type used by trust systems of the network participants. The influence of two factors on the development of cooperation--the network size and the type of participating nodes--is analysed using evolutionary game theory. Computational experiments demonstrate that, in a small network or in a network with many non-cooperative nodes, the cooperation is more likely to be developed on the basis of both reciprocity mechanisms. On the other hand, a large network and the existence of many unconditionally cooperative nodes favour the development of cooperation on the basis of direct reciprocity.

Information Theoretic Analysis of Cognitive Radio Systems

Abstract: Cognitive radios have recently emerged as a prime candidates for exploiting the increasingly flexible licensing of wireless spectrum. Regulatory bodies have come to realize that most of the time, large portions of certain licensed frequency bands remain empty [17]. To remedy this, legislators are easing the way frequency bands are licensed and used. In particular, new regulations would allow for devices which are able to sense and adapt to their spectral environment, such as cognitive radios, to become secondary users. 4 Such users are wireless devices that opportunistically employ the spectrum already licensed to primary users. Primary users generally associate with the primary spectral license holder, and thus have a higher priority right to the spectrum. The intuitive goal behind secondary spectrum licensing is to increase the spectral efficiency of the network, while, depending on the type of licensing, not affecting higher priority users. The exact regulations governing secondary spectrum licensing are still being formulated [18], but it is clear that networks consisting of heterogeneous devices, both in terms of physical capabilities and in the right to the spectrum, will emerge. Among the many questions that remain to be answered about cognitive networks, is that of the fundamental limits of possible communication. Although this may be defined in various ways, information theory is an ideal tool and approach from which to explore the underlying, implementationindependent limits of such heterogeneous networks. In this chapter, we will