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Abstract-Given the ever growing demand for radio spectrum,cognitive radio has recently emerged as an attractive wireless technology. Since orthogonal frequency division multiplexing (OFDM) is one of the major wideband transmission techniques, detection of OFDM signals in low signal-to-noise-ratio (SNR)scenario is an important research problem. In this paper, it is shown that the cyclic prefix correlation...
Spectrum sensing is an essential part of the cognitive radio systems which can be the solution for radio spectrum shortage. There are various methods of the signal detection; many of them are based on the energy detector. Another group of methods is based on known detected signal parameters as the method for DVB-T signal detection described in this paper. Because DVB-T uses OFDM with cyclic prefix,...
Spectrum sensing is the step stone of cognitive radios. There are several methods of detecting signals, among which the auto-correlation method is promising. In this paper, three classes of auto-correlation detection algorithms (signal matrix-based, signal vector-based, and signal function-based) are introduced and compared. The advantages and disadvantages of these algorithms are given also.
Spectrum sensing has continued to emerge as an essential topic for the cognitive networks where two kinds of users primary and secondary will share the band. This paper proposes a method for real-time detection of secondary users at the base stations. Cognitive radios may hide themselves in between the primary users to avoid being charged for using spectrum. To deal with such scenario, a cyclostationary...
One of the unique feature of cognitive radio systems is they can make use of temporarily idle spectral bands in an opportunistic manner. To achieve this however, robust sensing algorithm is required which otherwise incumbent services could suffer from interference. In this paper sensing algorithms based on energy detection and self-correlation detection are presented and compared. The self-correlation...
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