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Compressed wideband spectrum sensing based on discrete cosine transform.

Yulin Wang1, Gengxin Zhang1

  • 1Institute of Communication Engineering, PLA University of Science and Technology, Yudao Street 14, Nanjing 210007, China.

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This study introduces a novel Discrete Cosine Transform (DCT) based compressive sensing (CS) scheme for wideband spectrum sensing. The DCT-CS method offers improved performance and efficiency over traditional DFT-CS approaches.

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Telecommunications

Background:

  • Discrete Cosine Transform (DCT) is primarily used for data compression.
  • Wideband spectrum sensing traditionally faces high sampling requirements.
  • The application of DCT in spectrum sensing remains underexplored.

Purpose of the Study:

  • To reduce sampling needs in wideband spectrum sensing.
  • To leverage the sparsity of signals in the DCT domain.
  • To propose and evaluate a novel DCT-based compressive sensing (DCT-CS) scheme.

Main Methods:

  • Utilizing the compressive sampling (CS) principle.
  • Exploiting the unique sparsity structure of wideband signals in the DCT domain.
  • Comparing the proposed DCT-CS scheme with the conventional Discrete Fourier Transform-based CS (DFT-CS) scheme.

Main Results:

  • Wideband communication signals exhibit sparser representation in the DCT domain compared to the DFT domain.
  • The DCT-CS scheme demonstrates superior performance over DFT-CS.
  • Improvements observed in Mean Squared Error (MSE) of the reconstructed signal, detection probability, and computational complexity.

Conclusions:

  • The DCT-CS scheme is an effective method for wideband spectrum sensing.
  • DCT offers advantages over DFT for spectrum sensing applications due to signal sparsity.
  • The proposed DCT-CS scheme alleviates sampling requirements and enhances sensing efficiency.