title: Compressed wideband spectrum sensing based on discrete cosine transform.
abstract: 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.
authors: Institute of Communication Engineering, PLA University of Science and Technology, Yudao Street 14, Nanjing 210007, China.
authors: Yulin
authors: Y
authors: Wang
authors: Institute of Communication Engineering, PLA University of Science and Technology, Yudao Street 14, Nanjing 210007, China.
authors: Gengxin
authors: G
authors: Zhang
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical