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__ The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power,(More)
—Cognitive Radio (CR) systems have been proposed to enable flexible use of the frequency spectrum in future generations of wireless networks. These are expected to detect spectrum bands that are not actively used by licensed (primary) users and provide unlicensed (secondary) users access to these bands. In this context it is important for the CR systems to(More)
In this paper, we consider a network-coded cooperative wireless network, where users mutually pair among themselves to realize network coding. We assume a multiuser environment, where users transmit to a common destination in the absence of dedicated relaying nodes. We address the important problem of the mutual pairing of users, which directly governs the(More)
—Spectrum sensing and awareness are challenging requirements in cognitive radio (CR). To adequately adapt to the changing radio environment, it is necessary for the CR to detect the presence and classify the on-the-air signals. The wireless industry has shown great interest in orthogonal frequency division multiplexing (OFDM) technology. Hence,(More)
—In this paper, likelihood-based algorithms are explored for linear digital modulation classification. Hybrid Likelihood Ratio Test (HLRT)-and Quasi HLRT (QHLRT)-based algorithms are examined, with signal amplitude, phase, and noise power as unknown parameters. The algorithm complexity is first investigated, and findings show that the HLRT suffers from very(More)
—Automatic classification of the modulation type of an unknown communication signal is a challenging task, with applications in both commercial and military contexts, such as spectrum surveillance, cognitive radio, and electronic warfare systems. Most of the automatic modulation classification (AMC) algorithms found in the literature assume that the signal(More)
The sensing of the radio frequency environment has important commercial and military applications and is fundamental to the concept of cognitive radio. The detection and classification of low signal-to-noise ratio signals with relaxed a priori information on their parameters are essential prerequisites to the demodulation of an intercepted signal. This(More)