Cognitive network

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

Analysis of security performance of relay selection in underlay cognitive networks

Abstract: Underlay cognitive networks allow unlicenced/secondary users (SUs) to opportunistically access licenced frequency bands, and hence information transmission is undoubtedly wire-tapped by eavesdroppers. This study analyses security performance of a relay selection scheme, which selects a secondary relay to minimise information wire-tapping of eavesdroppers, in underlay cognitive networks. Toward this end, the authors propose approximate and asymptotic intercept outage probability expressions which account for interference power constraint for licenced/primary users, maximum transmit power constraint for SUs, independent non-identical fading channels, and direct channel between secondary source and eavesdropper. Moreover, they determine diversity order and coding gain of this relay selection based on the proposed asymptotic expression. Monte Carlo simulations validate these expressions and numerous results demonstrate that the investigated relay selection prevents the eavesdropper from obtaining full diversity order offered by all relays and source, induces the intercept outage probability saturated at either large maximum transmit power or large maximum interference power, and improves information security performance with respect to the increase in the number of relays.

Messaging and spectrum sharing between ad-hoc cognitive radio networks

Abstract: The efficacy of cognitive radio (CR) networks is defined by the ability of radio terminals and their network management systems to identify and classify co-channel interference and propagation dependent degradation. Isolating these phenomena and gathering statistical information about their behavior is a required step if cognitive control algorithms are to be effective in achieving spectrum sharing in ad-hoc wireless networks such as those operating using license-exempt bands. This paper summarizes the two CR approaches that are being studied in the IEEE 802.16H Task Group on coexistence of LE networks and examines messaging concepts that support CR functionality. In both approaches system architecture plays a defining role in the determining the messaging for these wireless networks.

Spectrum sharing via hybrid cognitive players evaluated by an M/D/1 queuing model

Abstract: We consider a cognitive wireless network in which users adopt a spectrum sharing strategy based on cooperation constraints. The majority of cognitive radio schemes bifurcate the role of players as either cooperative or non-cooperative. In this work, however, we modify this strategy to one in which players are hybrid, i.e., both cooperative and non-cooperative. Using a Stackelberg game strategy, we evaluate the improvement in performance of a cognitive radio network with these hybrid cognitive players using an M/D/1 queuing model. We use a novel game strategy (which we call altruism) to “police” a wireless network by monitoring the network and finding the non-cooperative players. Upon introduction of this new player, we present and test a series of predictive algorithms that shows improvements in wireless channel utilization over traditional collision-detection algorithms. Our results demonstrate the viability of using this strategy to inform and create more efficient cognitive radio networks. Next, we study a Stackelberg competition with the primary license holder as the leader and investigate the impact of multiple leaders by modeling the wireless channel as an M/D/1 queue. We find that in the Stackelberg game, the leader can improve its utility by influencing followers’ decisions using its advertised cost function and the number of followers accepted in the network. The gain in utility monotonically increases until the network is saturated. The Stackelberg game formulation shows the existence of a unique Nash equilibrium using an appropriate cost function. The equilibrium maximizes the total utility of the network and allows spectrum sharing between primary and secondary cognitive users.

Full-Rate Cooperative Spectrum Sharing Scheme for Cognitive Radio Communications

Abstract: In this letter, we propose full-rate cooperative spectrum sharing protocol for bandwidth efficient cognitive networks. Cooperative communication is a newly emerging protocol for multiple-input multiple-output, which offers diversity and hence improves the link performance. We show that the proposed scheme enhances the spectral efficiency of the primary user and improves the spectrum usage of the secondary user through cooperative multiplexing. We present an analytical derivation for the average bit error rate of a proposed scheme with maximum likelihood receiver.

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation

Abstract: The analysis of data represented as graphs is common having wide scale applications from social networks to medical imaging. A popular analysis is to cut the graph so that the disjoint subgraphs can represent communities (for social network) or background and foreground cognitive activity (for medical imaging). An emerging setting is when multiple data sets (graphs) exist which opens up the opportunity for many new questions. In this paper we study two such questions: i) For a collection of graphs find a single cut that is good for all the graphs and ii) For two collections of graphs find a single cut that is good for one collection but poor for the other. We show that existing formulations of multiview, consensus and alternative clustering cannot address these questions and instead we provide novel formulations in the spectral clustering framework. We evaluate our approaches on functional magnetic resonance imaging (fMRI) data to address questions such as: "What common cognitive network does this group of individuals have?" and "What are the differences in the cognitive networks for these two groups?" We obtain useful results without the need for strong domain knowledge.