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Compressed Wideband Spectrum Sensing Based on Discrete Cosine Transform

机译:基于离散余弦变换的压缩宽带光谱感应

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Discrete cosine transform (DCT) is a special type of transform which is widely used for compression of speech and image. However, its use for spectrum sensing has not yet received widespread attention. This paper aims to alleviate the sampling requirements of wideband spectrum sensing by utilizing the compressive sampling (CS) principle and exploiting the unique sparsity structure in the DCT domain. Compared with discrete Fourier transform (DFT), wideband communication signal has much sparser representation and easier implementation in DCT domain. Simulation result shows that the proposed DCT-CSS scheme outperforms the conventional DFT-CSS scheme in terms of MSE of reconstruction signal, detection probability, and computational complexity.
机译:离散余弦变换(DCT)是一种特殊类型的变换,广泛用于压缩语音和图像。但是,它对频谱感测的使用尚未得到广泛的关注。本文旨在通过利用压缩采样(CS)原理并利用DCT域中的独特稀疏结构来缓解宽带光谱感测的采样要求。与离散傅里叶变换(DFT)相比,宽带通信信号具有很多稀疏表示,并且在DCT域中更容易实现。仿真结果表明,所提出的DCT-CSS方案在重建信号,检测概率和计算复杂性的MSE方面优于传统的DFT-CSS方案。

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