Cognitive network

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

On Detecting Spectrum Opportunities for Cognitive Vehicular Networks in the TV White Space

Abstract: We overview the challenges related to spectrum awareness in the vehicular environment, with emphasis on awareness in the TV licensed band. In the vehicular environment the cognitive radio can help to: 1) satisfy capacity demand for Intelligent Transportation Systems (ITS) applications; and 2) offload time insensitive applications from the ITS dedicated spectrum. However, using simple propagation models we show that neither sensing, nor geolocation database lookup alone can provide sufficient incumbent protection. Collaboration among the sensors to take advantage of spatial diversity is difficult due to the rapidly changing network topology. Nevertheless, mobility provides the opportunity to use time diversity at each sensor. We also discuss the influence of sensing subsystem design on the vehicular cognitive network medium access (MAC) sublayer. Whenever appropriate, we evaluate applicability of the requirements imposed by the Federal Communications Commission (FCC) and the IEEE 802.22 standard to the cognitive vehicular networks.

Key techniques in green communication

Abstract: With the rapid increase of modern communication networks, the environmental problem has emerged. Reducing the emission of CO2 has been considered as an important goal in future green communication system design. This paper presents an introduction to the opportunities and challenges in green communication and discusses the key techniques in current research including cognitive networks, network coding and smart grid.

Centralized cooperative spectrum sensing with energy detecion in cognitive radio and optimization

Abstract: In this paper cognitive radio method is used for advanced wireless sensing technology. In cognitive radio, the secondary user utilizes the primary user's spectrum when primary user is not utilizing the band. The sensing of spectrum is of very importance in cognitive radio technology, as interference to the primary user is intolerable. Here in this paper we have used energy detection method for spectrum sensing. The performance of system gets degraded when factors such as fading and noise gets introduced. To further enhance the sensing capability of the system and overcome above issues, we are using centralized cooperative spectrum sensing technique. Cooperative sensing considers the neighboring cognitive radios decision in radio environment, for making final decision of availability of spectrum band. The centralized fusion center enables us to make a firm decision regarding the status of channel and broadcast the signal back to the transmitter. The number of cognitive radios to be considered for final outcome has to be kept limited. Thus we have focused on optimization of number of cognitive radio and optimum threshold required to get best results with minimum resources. The proposed system model designed based on hard decision, sends the fused decision back to the base station, where depending upon understanding between cognitive nodes and service provider assigns the vacant band to one of the needy cognitive radios.

Exact outage analysis of modified partial relay selection in cooperative cognitive networks under channel estimation errors

Abstract: This study first modifies the traditional partial relay selection in cooperative cognitive networks to prevent error propagation and then proposes exact and asymptotic outage analysis for the modified partial relay selection under practical operation conditions such as channel estimation errors (CEEs) on all wireless channels, independent and non-identical fading distributions, interference power constraint, and maximum transmit power constraint. The proposed analysis is useful in assessing system performance in important parameters as well as providing insights into performance limits without exhaustive simulations. Moreover, in order to quantitatively evaluate the performance gain of utilising the direct channel between the source and the destination in relaying communications, the authors extend their proposed analysis to dual-hop cognitive networks. Illustrative results demonstrate that CEEs and outage threshold significantly degrade system performance, and the direct channel dramatically contributes to performance improvement of relaying communications.

Resource allocation algorithm based on hybrid particle swarm optimization for multiuser cognitive OFDM network

Abstract: Model the uplink chance-constrained resource allocation problem.We propose HPSO which combines the SVM and PSO.Utilize SVM to compute the probabilistic interference constraint condition. Resource allocation plays a critical role to enhance the performance of cognitive orthogonal frequency division multiplexing (OFDM) network. However, due to lack the cooperation between cognitive network and primary network, the channel state information (CSI) between cognitive radio (CR) user and primary user (PU) could not be estimated precisely. In this work, a resource allocation problem over the power and subcarrier allocation based on chance-constrained programming is formulated to maximize the average weighted sum-rate throughput and guarantee the probabilistic interference constraint condition for PU. In order to solve the above resource allocation problem, the probabilistic interference constraint condition is computed by support vector machine (SVM) and we combine particle swarm optimization (PSO) and SVM to develop hybrid particle swarm optimization (HPSO). Simulation results verify HPSO not only yields the higher average weighted sum-rate throughput than other algorithms, but also satisfies the probabilistic interference constraint condition.