• Title/Summary/Keyword: cognitive algorithms

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A Comparison of Spectrum-Sensing Algorithms Based on Eigenvalues

  • Ali, Syed Sajjad;Liu, Jialong;Liu, Chang;Jin, Minglu
    • Journal of information and communication convergence engineering
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    • v.13 no.4
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    • pp.241-247
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    • 2015
  • Cognitive radio has been attracting increased attention as an effective approach to improving spectrum efficiency. One component of cognitive radio, spectrum sensing, has an important relationship with the performance of cognitive radio. In this paper, after a summary and analysis of the existing spectrum-sensing algorithms, we report that the existing eigenvalue-based semi-blind detection algorithm and blind detection algorithm have not made full use of the eigenvalues of the received signals. Applying multi-antenna systems to cognitive users, we design a variety of spectrum-sensing algorithms based on the joint distribution of the eigenvalues of the received signal. Simulation results validate that the proposed algorithms in this paper are able to detect whether the signal of the primary user exists or not with high probability of detection in an environment with a low signal-to-noise ratio. Compared with traditional algorithms, the new algorithms have the advantages of high detection performance and strong robustness

A Cognitive Mental Algorithm based on Psychoanalysis Theory: Theoretical study for design the mental model of a next intelligent robot (정신분석에 기반한 Cognitive Mental Algorithm: 차세대 지능로봇의 Mental Model 설계를 위한 이론적 배경)

  • Park, Kyung-Sook;Kwon, Dong-Soo
    • The Journal of Korea Robotics Society
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    • v.2 no.1
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    • pp.9-20
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    • 2007
  • This paper presents a theoretical study for making intelligent robots with human-like mind. For the development of a cognitive mental model, we developed three algorithms based on the cognitive process for human psychoanalysis. Specifically, the concept of id, ego and superego from the theory of Sigmund Freud was adopted and the procedural algorithms were presented.

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A survey on Rendezvous Algorithms in Cognitive Radio Networks Under Jamming Attacks (재밍 공격 상황을 고려한 인지무선 네트워크에서의 랑데뷰 알고리즘들에 관한 분석)

  • Martin, Robin;Kim, Yongchul
    • Convergence Security Journal
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    • v.21 no.1
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    • pp.209-219
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    • 2021
  • The problem of congestion in the licensed radio channels spectrum can be solved by Cognitive Radio Networks (CRN). Several algorithms exist to ensure the rendezvous between Secondary Users (SUs), they are increasingly efficient, allowing faster rendezvous under multiple scenarios. In parallel, several jamming algorithms are developed to counter rendezvous which are also improving. The goal in CRN is to ensure the rendezvous by warding such jammers with robust algorithms. In this paper, we classify various jamming techniques and analyze the performance of various well-known rendezvous algorithms under jamming attacks.

Policy-based Channel Sensing Architecture and Algorithms for Cognitive Radio Networks (지능형 무선 인지 기술 기반 네트워크 환경에서 정책기반 채널 센싱 구조 및 알고리즘)

  • Na, Do-Hyun;Hao, Nan;Yoo, Sang-Jo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.7B
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    • pp.538-549
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    • 2008
  • Recently IEEE 802.22 WG has considered Cognitive Radio (CR) technology to overcome shortage of communication channels. For using CR technology, accurate and rapid sensing method selection is extremely important. According to the channel sensing method, it is of the utmost importance because it can affect the incumbent system protection. So, optimum selection of channel sensing method is very important. IEEE 802.22 gives the solution, name of fine sensing, but the solution can not adapt to various networks. So in this paper we propose Policy-based Channel Sensing Architecture and Algorithms for Cognitive Radio Networks. The proposed channel sensing architecture and algorithms can reduce both primary system detection time and quiet time in our simulation. Among the proposed sensing algorithm, channel division round robin sensing reduce average detection time up to 70% compare to fine sensing method in IEEE 802.22.

Enhanced Adaptive Beamforming and Null Steering Algorithms in Cognitive Radio System

  • Zhuang, Zhili;Sohn, Sung-Hwan;Kim, Jae-Moung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.11A
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    • pp.822-830
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    • 2009
  • The spectrum efficiency of mobile communication networks can be improved dramatically adopting multiple antennas technologies. In order to guarantee the licensed rights of primary user (PU), the cognitive radio system should perform in a relatively low interference manner when it gets access to the spectrum of licensed networks. In this paper, we explore a uniformly distributed circular antenna array to implement beamforming algorithm that is accomplished by optimization method at the base station of cognitive radio networks, and therefore we can suppress the interference to PU by steering quite low transmission power toward PU and constructing a narrow beam toward cognitive user (CU). By reducing the constraint number of the optimization problem, we also propose a null steering algorithm that steers rather low radiation power toward PU, while the other areas in the same cell are covered by radiation power except the local area around PU. It is pursued to reduce the computation load and enlarge the capacity of cognitive radio networks extremely. The simulation results demonstrate that the proposed algorithms process superior performance.

Effects of the Problem-based Learning Utilizing Cognitive Algorithms in Elementary Mathematics Education (인지 기제 활용 문제 기반 학습의 수학 교육 효과 분석)

  • Lee, Myung-Geun;Kang, Su-Yeon
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.11
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    • pp.145-152
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    • 2011
  • The study analyzed effects of the problem-based learning utilizing cognitive algorithms in elementary mathematics education in terms of academic achievement and math attitude changes. In order to solve the research questions, a cognitive algorithm-based PBL model was derived based on N. Landa's algorithm-based instructional design theory. And the model was applied to a part of second semester math curriculum for 4th grade of an elementary school located in Seoul. The results showed that the PBL utilizing algorithms can be said to have effects on academic achievement. The PBL model is also considered to have positive effects in enhancing mathematical attitudes of the learners.

Biform Game Based Cognitive Radio Scheme for Smart Grid Communications

  • Kim, Sungwook
    • Journal of Communications and Networks
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    • v.14 no.6
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    • pp.614-618
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    • 2012
  • Smart grid is widely considered to be a next generation power grid, which will be integrated with information feedback communications.However, smart grid communication technologies are subject to inefficient spectrum allocation problems. Cognitive radio networks can solve the problemof spectrumscarcity by opening the under-utilized licensed bands to secondary users. In this paper, adaptive cognitive radio spectrum sensing and sharing algorithms are developed for smart grid environments. Simulation results are presented to demonstrate the effectiveness of the proposed scheme in comparison with other existing schemes.

인지 무선 통신망을 위한 인지 알고리즘 및 엔진

  • Song Myeong-Seon;Reed Jeffrey H.;Kim Chang-Ju
    • The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.2 s.58
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    • pp.19-27
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    • 2006
  • Technologies to utilize the limited frequency resource more efficiently in spatial and temporal are accelerated. In this paper cognitive algorithms as brain of cognitive radio, kind and characteristics of databases which are necessary parts for algorithm were reviewed and summarized. And an example of cognitive engine on which database and algorithm are executed was described also. Because the current status of development of technologies relating to cognitive radio is at the initial stage, the best database, algorithm and engine for a cognitive radio were not suggested, but the direction of development and factors to be considered during development of relating technologies were explained.

Minimum BER Power Allocation for OFDM-based Cognitive Radio Networks

  • Xu, Ding;Li, Qun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2338-2353
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    • 2015
  • In this paper, the optimal power allocation algorithm that minimizes the aggregate bit error rate (BER) of the secondary user (SU) in a downlink orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) system, while subjecting to the interference power constraint and the transmit power constraint, is investigated under the assumption that the instantaneous channel state information (CSI) of the interference links between the secondary transmitter and the primary receiver, and between the primary transmitter and the secondary receiver is perfectly known. Besides, a suboptimal algorithm with less complexity is also proposed. In order to deal with more practical situations, we further assume that only the channel distribution information (CDI) of the interference links is available and propose heuristic power allocation algorithms based on bisection search method to minimize the aggregate BER under the interference outage constraint and the transmit power constraint. Simulation results are presented to verify the effectiveness of the proposed algorithms.

Minimizing Sensing Decision Error in Cognitive Radio Networks using Evolutionary Algorithms

  • Akbari, Mohsen;Hossain, Md. Kamal;Manesh, Mohsen Riahi;El-Saleh, Ayman A.;Kareem, Aymen M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.9
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    • pp.2037-2051
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    • 2012
  • Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.