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In this paper we consider the spectrum sensing performance and requirements for detecting legacy users (LU) in cognitive radios (CR) with periodic scanning. The performance and requirements are studied based on the temporal spectral occupancy statistics of the LU and the sensing signal to noise ratio levels in order to achieve a certain level of detection probability. We model the temporal statistics...
Energy efficiency is a critical consideration in the design of low cost sensor networks. This paper studies the problem of extending the lifetime of the sensor networks as far as possible while maintaining the quality of network coverage. A systematical analysis on the relationship between the network lifetime and cover sets alternation is given, and by introducing the concept of time weight factor,...
In this paper we describe a new cooperating sensing method using double threshold energy detection technique for cognitive radio. Each secondary cognitive user takes a local decision on spectrum occupancy based on two threshold energy detection and uses 1 bit information to convey its decision to the fusion center that collects decisions from all cooperating users who are able to detect presence or...
In this paper, a novel method combining cooperative spectrum sensing with quantized soft decision combining is introduced. In order to allow cognitive radios and cognitive networks to opportunistically use spectrum, it is a prerequisite that the license owner or primary user of the spectrum will not be harmfully interfered and the spectrum band will be vacated as soon as the primary user starts its...
Collaborative sensing in cognitive radio networks can significantly improve the probability of detecting the transmission of primary users. In current collaborative sensing schemes, all collaborative secondary users are assumed to be honest. As a consequence, the system is vulnerable to attacks in which malicious secondary users report false detection results. In this paper, we investigate how to...
Compressed sensing, viewed as a type of random undersampling, considers the acquisition and reconstruction of sparse or compressible signals at a rate significantly lower than that of Nyquist. Exact reconstruction from incompletely acquired random measurements is, under certain constraints, achievable with high probability. However, randomness may not always be desirable in certain applications. Taking...
A network model using Self-organizing map (SOM) and Outputs Modifiable Radial Basis Function (OMRBF) is proposed to identify acoustic fault of underwater vehicles. This model integrates unsupervised SOM with supervised OMRBF to accomplish incremental learning. The outputs neurons of this model can be modified on-line, and SOM is utilized to determine the optimal number of hidden neurons. Experiment...
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