Cognitive network

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

Cognitive communication network system and communicating method thereof

Abstract: Object: To provide a mechanism and a function of a system that can determine a communication method and the like effectively utilizing frequency resources, considering priority of each communication, in a cognitive communication network system of a frequency shared type or the like assuming that a given frequency band is shared by a plurality of systems in use. Solution: In a configuration in which a cognitive communication network system has a plurality of radio access networks 23 and a superior communication network 10 that provides a common platform at least to the radio access networks, in a plurality of base stations 23 a on at least a part of the radio access network 23 , base-station state obtaining means 232 that collect information relating to a state of the base station itself in the base station or a communication state and base-station communication reconfiguration managing means 231 that reconfigure at least one of either a selection of the base station to be used in the communication or a communication condition in the base station on the basis of the information collected by the base-station state obtaining means are provided.

High-Level Design Approach for the Specification of Cognitive Radio Equipments Management APIs

Abstract: Cognitive Radio (CR) equipments are radio devices that support the smart facilities offered by future cognitive networks Even if several categories of equipments exist (terminal, base station, smart PDA, etc), each requiring different processing capabilities (and associated cost or power consumption), these equipments have to integrate also a set of new capabilities as regards CR support, in addition to the usual radio signal processing elements This implies real-time radio adaptation and sensing capabilities, but not only We assert that it is necessary to add inside the radio equipments some management facilities for that purpose, and we propose in this paper a high-level design approach for the specification of a management framework This includes a set of designing rules, based on hierarchical units that are distributed over three levels, and the associated APIs necessary to efficiently manage CR features inside a CR equipment The proposed architecture is called HDCRAM (Hierarchical and Distributed Cognitive Architecture Management) HDCRAM is an extension of a former hierarchical and distributed reconfiguration management (HDReM) architecture, which is derived from our previous research on Software Defined Radio (SDR) The HDCRAM adds to the HDReM's reconfiguration management facilities the necessary new management features, which enable the support of sensing and decision making facilities It consists in the combination of one Cognitive Radio Management Unit (CRMU) with each Reconfiguration Management Unit (ReMU) distributed within the equipment Each of these CRMU is in charge of the capture, the interpretation and the decision making according to its own goals In this Cognitive Radio context, the term "decision" refers to the adaptation of the radio parameters to the equipment's environment This paper details the HDCRAM's management functionality and structure Moreover, in order to facilitate the early design phase of the management specification, which is new in radio design, HDCRAM has also been modeled with a meta-programming language based on UML But beyond the first objective of high-level specification, we have also derived a simulator from the obtained meta-model, thanks to the use of an executable language This gives the opportunity to specify the CR needs and play a wide variety of scenarios, in order to validate the CR equipment's design This approach provides high-level design facilities for the specification of cognitive management APIs inside a cognitive radio equipment

Optimization of Cooperative Inter-Operability in Heterogeneous Networks with Cognitive Ability

Abstract: This letter studies the problem of maximizing the spectral efficiency for multi-radio access (MRA) with a limited transmission power constraint in cognitive heterogeneous networks, where multiple radio access technologies (RATs) coexist and MRA transmissions over several RATs are possible. By assuming each multi-mode mobile terminal (MMT) has ability to access multi-RAT simultaneously, analysis of an optimal solution for MRA appears with proposed spectrum and power allocation algorithm that maximizes the total system capacity. Numerical results show that the proposed algorithm satisfies the power-limited conditions of its own RAT and has capacity increase for high load ratios of MRA.

Leveraging the Algebraic Connectivity of a Cognitive Network for Routing Design

Abstract: In this paper, we consider the implications of spectrum heterogeneity on connectivity and routing in a Cognitive Radio Ad Hoc Network (CRAHN). We study the Laplacian spectrum of the CRAHN graph when the activity of primary users is considered. We introduce the cognitive algebraic connectivity, i.e., the second smallest eigenvalue of the Laplacian of a graph, in a cognitive scenario. Throughout this notion we provide a methodology to evaluate the connectivity of CRAHNs and consequently introduce a utility function that is shown to be effective in capturing key characteristics of CRAHN paths. This model provides a unique metric that captures network connectivity, path length, and impact of primary users. Moreover, the proposed metric penalizes paths where spectrum band switchings are highly probable. We design all the components of our routing framework, named Gymkhana, and we present a twofold performance verification: one from a topological perspective to show all the potentialities of the proposed routing approach, and the other considering network traffic to evaluate the performance in terms of end-to-end delay and packet delivery ratio.