Cognitive network

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

Spectrum sensing and energy detection in cognitive networks

Abstract: It is worth mentioning that the use of wireless systems has been increased in recent years and supposed to highly increase in the few coming years because of the increasing demands of wireless applications such as mobile phones, Internet of Things (IoT), wireless sensors networks (WSNs), mobile applications and tablets. The scarcity of spectrum needs to be into consideration when designing a wireless system specially to answer the two following questions; how to use efficiently the spectrum available for the available networks in sharing process and how to increase the throughput delivered to the serving users. The spectrum sharing between several types of wireless networks where networks are called cognitive networks is used to let networks cooperate with each other by borrowing some spectrum bands between them especially when there is an extra band that is not used. In this project, the simulation of spectrum sensing and sharing in cognitive networks is performed between two cognitive networks. This project discusses the performance of probability of energy detected (Pd) with different values of false alarm (Pf) and Signal-To-Noise Ratio (SNR) values to evaluate the performance of the sensing and sharing process in cognitive networks. The results show that when the request of sharing spectrum increased, the full sharing process occurs for a long time and the error rate decreases for small values of SNR.

Throughput analysis of cognitive wireless networks with Poisson distributed nodes based on location information

Abstract: This paper provides a statistical characterization of the individual achievable rates in bits/s/Hz and the spatial throughput of bipolar Poisson wireless networks in bits/s/Hz/m2. We assume that all cognitive transmitters know the distance to their receiver's closest interferers and use this side-information to autonomously tune their coding rates to avoid outage events for each spatial realization. Considering that the closest interferer approximates the aggregate interference of all transmitters treated as noise, we derive closed-form expressions for the probability density function of the achievable rates under two decoding rules: treating interference as noise, and jointly detecting the strongest interfering signals treating the others as noise. Based on these rules and the bipolar model, we approximate the expected maximum spatial throughput, showing the best performance of the latter decoding rule. These results are also compared to the reference scenario where the transmitters do not have cognitive ability, coding their messages at predetermined rates that are chosen to optimize the expected spatial throughput - regardless of particular realizations - which yields outages. We prove that, when the same decoding rule and network density are considered, the cognitive spatial throughput always outperforms the other option.

List multi-coloring based fair channel allocation policy for self coexistence in cognitive radio networks with QoS provisioning

Abstract: Recently cognitive radio has gain considerable interest by research community as a viable solution to mitigate the problems of spectrum scarcity and spectrum under-utilization. A cognitive radio selects a vacant channel opportunistically and perform its own transmission on it. Detecting an incumbent user along with self-coexistence has become one of the important aspects of the cognitive radio. The former problem is solved by spectrum sensing while the latter problem requires complex techniques. To this end we propose a graph coloring based fair channel allocation policy for self-coexistence in cognitive radio networks. The proposed scheme allows multiple cognitive radio network operating over a given region to allocate channels on non-interfering basis with a certain grade of QoS. The scheme allows fair allocation of channels among multiple participating opportunistic networks with varying priorities. Simulation analysis has been done to show the effectiveness of the proposed approach.

Radio environment maps for military cognitive networks: Construction techniques vs. map quality

Abstract: In this paper we present the concept of the Radio Environment Map (REM). The architecture of REM supporting military communications systems is described. The map construction techniques based on spatial statistics and transmitter location determination and the problem of REM quality and relevant metrics are discussed. The results of field tests taken for UHF range with sensor network are discussed and exemplary maps with different interpolation algorithms are presented. Finally, the problem of REM construction techniques vs. map quality is analyzed.

Cognitive Sensor Technology for Structural Health Monitoring

Abstract: Current paper presents artificial neural network architecture based on Cognitive Sensor technology which may be used for development of intelligent SHM systems. Dynamic Artificial Neural Network (DANN) has time dependent structure which is defined by experience of processing input data streams. Advantages of proposed model include ability to learn both linear and non-linear patterns on the basis of processing data streams. Evolution of DANN architecture includes stage of autonomous growth of subnets developed by separate Cognitive Sensors and stage of cooperative growth of resulting network. Example application of proposed cognitive technology for solution of Structural Health Monitoring problems is discussed.