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Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, as a key enabling functionality in cognitive radio networks, needs to reliably detect signals from licensed primary radios to avoid harmful(More)
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wideband spectrum sensing technique referred to as <i>multiband</i> <i>joint</i> <i>detection</i> is(More)
Cognitive radio (CR) has recently emerged as a promising technology to revolutionize spectrum utilization in wireless communications. In a CR network, secondary users continuously sense the spectral environment and adapt transmission parameters to opportunistically use the available spectrum. A fundamental problem for CRs is spectrum sensing; secondary(More)
PURPOSE This study examined the effectiveness of early and prolonged mu4D5 (the murine form of trastuzumab/Herceptin) treatment in transgenic mice that overexpress human HER2 (huHER2), under the murine mammary tumor virus promoter, as a model of huHER2-overexpressing breast cancer. EXPERIMENTAL DESIGN Mice were randomly assigned to one of three treatment(More)
Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces a novel wideband spectrum sensing technique, called multiband joint detection, which jointly detects the(More)
Spectrum sensing is one of the enabling functionalities for cognitive radio systems to operate in the spectrum white space. To protect the primary incumbent users from interference, the cognitive radio is required to detect incumbent signals at very low signal-to-noise ratio (SNR). In this paper, we study a spectrum sensing technique based on spectral(More)
We consider a wireless network with distributed processing capabilities for estimation or detection applications. Due to limited communication resources, the network selects only a subset of sensor measurements for estimation or detection as long as the resulting fidelity is tolerable. We present a distributed sampling scheme based on the concept of(More)
Spectrum sensing is a key enabling functionality in cognitive radio (CR) networks, where the CRs act as secondary users that opportunistically access free frequency bands. Due to the effects of channel fading, individual CRs may not be able to reliably detect the existence of a primary radio, who is a licensed user for the particular band. In this paper, we(More)
Consider the problem of signal detection via multiple distributed noisy sensors. We study a linear decision fusion rule of [Z. Quan, S. Cui, and A. H. Sayed, ¿Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks,¿ <i>IEEE J. Sel. Topics Signal Process.</i>, vol. 2, no. 1, pp. 28-40, Feb. 2008] to combine the local statistics from(More)