ANN Based Spectrum Sensing Technique for Cognitive Radio Applications

S. Pattanayak, P. Venkateswaran, R. Nandi
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Abstract

An ANN based spectrum sensing technique for audio FM and the wireless microphone signals in TV band is proposed. The artificial neural network (ANN) model trained with the autocorrelation peaks of the signal in channel identifies it as a white space or a primary signal. The performance of this technique is efficient in terms of false alarm rate and probability of detection; the proposed method presents less mathematical complexity as compared to other recent spectrum sensing techniques. Simulation results are presented.
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基于神经网络的认知无线电频谱感知技术
提出了一种基于人工神经网络的音频调频和电视频段无线麦克风信号频谱感知技术。利用信道中信号的自相关峰进行训练的人工神经网络(ANN)模型将其识别为空白信号或主信号。在虚警率和检测概率方面,该技术的性能是有效的;与其他最新的频谱传感技术相比,该方法具有较低的数学复杂度。给出了仿真结果。
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