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A Survey of Spectrum Sensing Algorithms
- A Survey of Spectrum Sensing Algorithms The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey
CR_MC_SIGNAL
- 认知无线电系统中多载波信号带外干扰的抑制，采用载波加权的方法降低认知无线电系统中认知用户信号对主用户信号的干扰 -Cognitive radio system in multi-carrier signal-band interference suppression, the use of carrier-weighted ways to reduce cognitive cognitive radio system users on the primary user signal sign
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- Cognitive radio frequency spectrum detection-The spectrum sensing of a wideband frequency range is studied by dividing it into multiple subbands. It is assumed that in each subband either a primary user (PU) is active or absent in a additive white
detection
- 认知无线电中频谱感知技术的两种频谱检测方法-Two kinds of spectrum detection methods of spectrum sensing technology in cognitive radio
spectrum-sensing
- 介绍了认知无线电技术中的频谱感知，以及各种频谱感知的方法和优缺点-Cognitive radio technology introduced in the spectrum sensing, and a variety of methods and advantages and disadvantages of spectrum sensing
Spectrum-Sensing-in-CR
- 谱感知技术是认知无线电(CR)的关键技术,频谱检测的可靠度和精度决定了是否会影响主用户的正常通信及认知用户能否有效利用频谱.在频谱检测的众多方法中,能量检测法是一种常用的方法,但能量检测器的门限很容易受到噪声功率变化的影响,影响主用户的正常通信.笔者提出一种自适应背景噪声的门限设置方法,通过引入门限评价指数作为衡量频谱感知效率和频谱资源利用率的度量指标,使得认知用户在不同的应用环境中能自适应地设置频谱感知门限,达到更充分利用频谱资源和更有效传送信号的目的.仿真证明,该方法确定的门限能够随着噪声条
Kuschner-BayesianNetwork-feature
- Kuschner论文，贝叶斯网络方法在质谱数据特征选择。其中关于机器学习中贝叶斯分类器部分有完整原理分析，可以用于认知无线电网络的频谱感知等新领域。含有matlab程序大于100页，子函数很多。-Kuschner paper, Bayesian network methods of feature selection in mass spectrometry data. One of the Bayes classifier machine learning part of a complete
A-survey-of-spectrum-sensing-algorithms-for-cogni
- The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologie
认知无线网络中的协作频谱感知综述
- 认知无线网中频谱感知的综述，介绍了频谱感知技术的主要分类，几种检测方法的技术特定，以及研究趋势。(A review of spectrum sensing in cognitive radio networks, the main categories of spectrum sensing techniques, the technical specificity of several detection methods, and the research trends are introdu