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This paper proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. An existing statistical hypothesis test for the presence of cyclostationarity is extended to multiple cyclic frequencies and its asymptotic distributions are established. Collaborative test statistics are proposed for the fusion of(More)
Cognitive radios sense the radio spectrum in order to find underutilized spectrum and then exploit it in an agile manner. Spectrum sensing has to be performed reliably in challenging propagation environments characterized by shadowing and fading effects as well as heavy-tailed noise distributions. In this paper, a robust computationally efficient(More)
Cognitive radios sense the radio spectrum in order to find unused frequency bands and use them in an agile manner. Transmission by the primary user must be detected reliably even in the low signal-to-noise ratio (SNR) regime and in the face of shadowing and fading. Communication signals are typically cyclostationary, and have many periodic statistical(More)
This paper focuses on the performance analysis and comparison of hard decision (HD) and soft decision (SD) based approaches for cooperative spectrum sensing in the presence of reporting channel errors. For cooperative sensing (CS) in cognitive radio networks, a distributed detection approach with displaced sensors and a fusion center (FC) is employed. For(More)
A simple and efficient spectrum sensing scheme for orthogonal frequency division multiplexing (OFDM) signals of primary user in cognitive radio systems is proposed in this paper. A detector exploiting the well-known autocorrelation property of cyclic prefix (CP) based OFDM signals is developed. The proposed scheme is then extended to the case of many(More)
In this paper a distributed multiagent, multiband reinforcement learning based sensing policy for cognitive radio ad hoc networks is proposed. The proposed sensing policy employs secondary user (SU) collaboration through local interactions. The goal is to maximize the amount of available spectrum found for secondary use given a desired diversity order, i.e.(More)
The main focus of this paper is to present a performance limitation of collaborative spectrum sensing in cognitive radios with imperfect reporting channels. We consider hard decision (HD) based cooperative sensing (CS), in which each SU sends a one-bit binary decision corresponding to the absence or the presence of primary user (PU) to a fusion center (FC).(More)
In this paper, a system for automatically recognizing radar waveforms is introduced. This type of techniques are needed in various spectrum management, surveillance and cognitive radio or radar applications. The intercepted radar signal is classified to eight classes based on the pulse compression waveform: linear frequency modulation (LFM), discrete(More)
— In this paper the classification of pulse compression radar waveforms using features extracted from the Choi-Williams time-frequency distribution is studied. In addition, a feature based on the symmetry properties of polyphase waveforms is introduced. The pulse compression waveforms examined are the Frank, P1, P2, P3, and P4 codes. The discrimination(More)
In this paper the problem of estimating a common modulation from a group of intercepted radar pulses is addressed. A robust M-estimation technique is proposed. The M-estimation approach provides tolerance against preprocessing errors as well as to other model failures. The performance of the M-estimation technique is compared to a maximum likelihood(More)