Cognitive network

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

Power Efficiency Maximization in Cognitive Radio Networks

Abstract: Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the existence of optimal combination of parameters such that the power efficiency is maximized. Then we reformulate the objective function to incorporate the throughput. According to different constraints or degree of significance, we may put proper weight to each term so that we could obtain more preferable combination of parameters. Computer simulations have given the optimal solution curve for different weights. We can draw the conclusion that if we put more emphasis on power efficiency, the transmit power is a more critical parameter, however if throughput is more important, the effect of sensing time is significant.

Self-Organize Network Architecture for Multi-agent Cognitive Radio Systems

Abstract: this paper presents self-organize network architecture for cognitive radio (CR). In order to increase the flexibility of CR, a division method and corresponding network keeping strategy is proposed in this paper, whose key part is finding the cutting edge in the interface graph. The TFCE (Tarjan-find-cutting-edge) algorithm is also given to find the cutting edge. On the basis of the division method a spectrum allocation model is introduced to research the effectiveness of the method for CR. The result shows the self-organize method could effectively add group's flexibility without affecting spectrum allocation utility or increasing system traffic.

Cognitive Communication in Rail Transit: Awareness, Adaption, and Reasoning

Abstract: Wireless communication plays a vital role in the operations of modern rail transportation. The characteristics of rapid train motion make the wireless spectrum environment unstable, discontinuous, and unpredictable. These uncertainties, coupled with inherent spectrum scarcity, result in inefficiencies in wireless communication. Applying cognitive radio in railway wireless communication systems is a cutting-edge research field. Most rail cognitive radio studies focus only on solving spectrum scarcity. The authors’ improved rail cognitive radio model uses a Bayesian network with numerous channel contextual features to probabilistically infer the likelihood of spectrum accessibility. This scheme provides a completely new way to solve the problem of low spectral efficiency of cognitive radio in rail transit.