Cognitive network

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

Cooperative beamforming in Cognitive Radio networks

Abstract: In this paper, the problem of cooperative beamforming is investigated in a heterogeneous underlay cognitive network. A major difference exists between a conventional cooperative beamforming problem and cooperative beamforming in a CR (Cognitive Radio)network due to the interference constraints imposed by primary network. These constraints can greatly icrease the complexity of the related optimization problem and make it much more challenging. Here, we have assumed a typical CR network where a set of cognitive relay nodes collaboratively assist the secondary transmitter to relay its message signal to the destination in the presence of a primary transmitter-receiver pair. Each relay employs the Amplify-and-Forward (AF) protocol to retransmit the signal. In fact, the relays comprise a distributed beamformer to beamform the signal towards its destination while maintaining the QoS in the primary user. The objective is designing the beamformer in order to maximize the target SINR in the cognitive network subject to the network power limitations and interference constraints on the primary network. First, the cooperative beamforming problem has been solved and the improved performance in terms of target SINR in the secondary network has been investigated by simulations. Secondly, a parameter has been derived to demonstrate the distance between the optimal beamweights in this problem and the beamweights in a conventional beamforming problem. Simulations show that the target SINR can be dramatically increased by using cooperative beamforming. Moreover, they show that there is a great distinction between the optimal solutions in conventional cooperative beamforming and cooperative beamforming in cognitive radios.

Spectrum allocation using genetic algorithm in cognitive radio networks

Abstract: Cognitive radio allows unlicensed operation in licensed bands to meet the growing demand for radio spectrum. The intelligent device, in a spectral environment, must detect free frequencies to create a cognitive network without interfering licensed users. In this paper, we are interested in finding the optimal spectrum to be allocated to users in cognitive radio networks by ensuring quality of service satisfying. The problem is started by studying the possibility of using genetic algorithm (GA) to accommodate the secondary users in best possible space in the spectrum by interacting with the dynamic radio environment. The main advantage of GA over other soft computing techniques is its multi-objective handling capability. The cognitive radio will sense the radio frequency parameter from the environment and the reasoning engine in the cognitive radio will take the required decisions in order to provide new spectrum allocation as demanded by the user. GA defines a radio in the form of chromosomes and genes and the user's quality of service needs are given as input to the GA procedure. We analyze the impact of both parameters, available spectrum resources size which is defined by the GA as a population size, and the number of defined chromosome's genes in the efficiency of spectrum allocation. The performance analysis results are showed in Matlab.

Performance of Adaptive Link Selection with Buffer-Aided Relays in Underlay Cognitive Networks

Abstract: In this paper, we investigate the performance of a three-node dual-hop cognitive radio network with a half-duplex decode-and-forward buffer-aided relay. We derive expressions for the average rate and symbol error rate (SER) performance of an adaptive link selection based channel-aware buffer-aided relay scheme that imposes peak-power and peak-interference constraints on the secondary nodes, and compare them with those of conventional non-buffer-aided relay and conventional buffer-aided relay schemes for a delay-tolerant system. For a finite-sized buffer, we analyze the performance of a modified threshold-based scheme for fixed-rate transmission. We analyze the tradeoffs between the delay, throughput, and SER. Computer simulation results are presented to demonstrate accuracy of the derived expressions.

Wireless Sensor Networks: A Cognitive Perspective

Abstract: With classical techniques for data transmission soon reaching their limitations, cognitive approaches may offer a solution to user requirements for better coverage, connectivity, security, and energy efficiency at lower cost. Wireless Sensor Networks: A Cognitive Perspective presents a unified view of the state of the art of cognitive approaches in telecommunications. A benchmark in the field, it brings together research that has previously been scattered throughout conference and journal papers. Cutting-Edge Topics in Cognitive Communications After a review of the cognitive concept and approaches, the book outlines a generic architecture for cognition in wireless sensor networks. It then targets specific issues that need to be addressed through cognition, from cognitive radio and spectrum access to routing protocols. The book also explores how to use weighted cognitive maps to improve network lifetime through optimizing routing, medium access, and power control while fulfilling end-to-end goals. The final chapter discusses the implementation of hardware for GPS/INS-enabled wireless sensor networks. This addresses an important need for real-time node position information in many wireless sensor network applications and communication protocols. Real-World Applications of Wireless Sensor Networks using the Cognitive Concept Written in a tutorial style, the book supplies an in-depth survey of each topic, accompanied by detailed descriptions of the algorithms and protocols. It also provides a step-by-step analysis of the various communications systems through extensive computer simulations and illustrations. Examples cover environmental monitoring, vehicular communications, tracking, and more. A comprehensive overview of cognitive communications in wireless sensor networks, this work lays the foundations for readers to participate in a new era of research in this emerging field.