Correlation-Based Detection of OFDM Signals in the Angular Domain

• Published in: IEEE transactions on vehicular technology Vol. 61; no. 3; pp. 951 - 958
• Main Authors: Turunen, V., Kosunen, M., Vaarakangas, M., Ryynanen, J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Autocorrelation; cognitive radio; Correlation; Detection; Detection algorithms; Detection, estimation, filtering, equalization, prediction; Detectors; digital signal processing; Energy use; Estimation; Exact sciences and technology; Feature extraction; field-programmable gate arrays; Information, signal and communications theory; Multiplexing; OFDM; Orthogonal Frequency Division Multiplexing; orthogonal frequency-division multiplex (OFDM); Radio; Radiocommunication specific techniques; Radiocommunications; Signal and communications theory; Signal processing; Signal representation. Spectral analysis; Signal, noise; Studies; Telecommunications; Telecommunications and information theory; Utilization; Vectors; Performance evaluation; Digital processing; orthogonal frequency-division multiplex (OFDM); Non stationary process; Implementation; Correlation method; cognitive radio; Performance requirement; Spectrum analysis; Correlation detection; Radio spectrum; Signal detection; digital signal processing; detection algorithms; Measurement sensor; Field programmable gate array; field-programmable gate arrays; Pattern recognition; Algorithm; Integrated circuit; Orthogonal frequency division multiplexing; Signal processing; Autocorrelation; Digital signal processor; Signal analysis; Multiplying circuits; Comparative study; Software radio
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2012.2183009

Spectrum sensing is an essential part of future cognitive radios, as the spectrum sensor provides information about the utilization of the surrounding radio spectrum. Several approaches to implementing spectrum sensing have been proposed in the literature, one of them being the class of feature detectors. Cyclostationary feature detectors are, in general, considered to be superior in performance but suffer from high implementation complexity. Therefore, most studies still utilize energy detectors, which may not reach the performance requirements set for practical implementations. This paper presents angular domain feature detection algorithms that are based on cyclostationary properties. Angular domain signal processing is shown to simplify the implementation considerably while preserving comparable performance. Moreover, a new detection algorithm that leads to multiplier-free implementation and reduces the memory requirements, compared with any previous approaches, is proposed.