Blind Identification of SFBC-OFDM Signals Based on the Central Limit Theorem

• Published in: IEEE transactions on wireless communications Vol. 18; no. 7; pp. 3500 - 3514
• Main Authors: Gao, Mingjun, Li, Yongzhao, Dobre, Octavia A., Al-Dhahir, Naofal
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Blind identification; Block codes; Central limit theorem; Computer simulation; Frequency domain analysis; Identification; multiple-input multiple-output; OFDM; orthogonal frequency division multiplexing; Receiving antennas; Redundancy; Selective fading; space-frequency block code; Statistical analysis; Statistical tests; support vector machine (SVM); Support vector machines; Synchronism; Synchronization; Theorems
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2019.2914687

Previous approaches for blind identification of space-frequency block codes (SFBCs) do not perform well for short observation periods due to their inefficient utilization of frequency-domain redundancy. This paper proposes a hypothesis test (HT)-based algorithm and a support vector machine (SVM)-based algorithm for the SFBC signals' identification over frequency-selective fading channels to exploit two-dimensional space-frequency domain redundancy. Based on the central limit theorem, space-domain redundancy is used to construct the cross-correlation function of the estimator and frequency-domain redundancy is incorporated in the construction of the statistics. The difference between two proposed algorithms is that the HT-based algorithm constructs a chi-square statistic and employs an HT to make the decision, while the SVM-based algorithm constructs a non-central chi-square statistic with unknown mean as a strongly distinguishable statistical feature and uses SVM to make the decision. Both the algorithms do not require knowledge of the channel coefficients, modulation type, or noise power, and the SVM-based algorithm does not require timing synchronization. The simulation results verify the superior performance of the proposed algorithms for short observation periods with comparable computational complexity to conventional algorithms, as well as their acceptable identification performance in the presence of transmission impairments.