Spatial-Frequency Block Coding Automatic Recognition with Non-Gaussian Interference for Cognitive MIMO-OFDM Systems

Zhang, Junlin; Liu, Mingqian; Zhao, Nan; Chen, Yunfei

Abstract

Space-time/frequency block coding (STBCs/SFBCs) scheme is a crucial technique for enhancing the effectiveness and reliability of multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with cognitive radio (CR) capability. Automatic recognition of STBCs/SFBCs is a prerequisite for achieving dynamic spectrum sharing in cognitive MIMO-OFDM systems. In contrast to existing works, this paper proposes a weighted cross-correlation function-based algorithm to recognize SFBCs for cognitive MIMO-OFDM systems with Gaussian noise and non-Gaussian impulsive interference. The proposed algorithm extracts the space-frequency redundancy information of different OFDM subcarriers on different receiver antenna pairs by using weighted cross-correlation functions. Then, the weighted cross-correlation feature vectors are constructed by exploiting the multi-antenna system so as to design the detection statistics and thresholds based on the central limit theorem. Finally, a decision tree method is adopted to discriminate between several SFBCs. The proposed algorithm does not require prior information such as channel coefficients, modulation schemes, noise power, or interference power. Simulation results show that the proposed algorithm is robust against non-Gaussian impulsive interference and achieves high recognition performance in the case of a small number of samples and a low signal-to-noise ratio. Index Terms-Cognitive radio, multiple-input multiple-output, non-Gaussian impulsive interference, orthogonal frequency division multiplexing, parameter recognition, space-frequency block coding.

Citation

Zhang, J., Liu, M., Zhao, N., & Chen, Y. (in press). Spatial-Frequency Block Coding Automatic Recognition with Non-Gaussian Interference for Cognitive MIMO-OFDM Systems. IEEE Transactions on Cognitive Communications and Networking,

• Journal Article Type: Article
• Acceptance Date: Jun 14, 2024
• Deposit Date: Jul 15, 2024
• Journal: IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Issue: 1
• Public URL: https://durham-repository.worktribe.com/output/2588797