In cognitive radio networks, spectrum sensing is used to sense the unused spectrum in an opportunistic manner. In this paper, we propose an energy detector utilizing adaptive double threshold (ED_ADT) for spectrum sensing, which improves detection performance as well as overcomes sensing failure problem. The detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of secondary user. Numerical results show that proposed ED_ADT scheme outperforms conventional energy detector by 12.8% at -8 dB signal-to-noise ratio (SNR) in terms of probability of detection alarm (P d ). While utilizing cooperative spectrum sensing (CSS) with ED_ADT scheme, it is further found that adaptive double threshold improves detection performance around 26.8% and 7.6% as compared to CSS with single threshold and hierarchical with quantization method at -10 dB SNR, respectively, under the case when a small number of sensing nodes are used in spectrum sensing.
Cognitive radio (CR) is a regulated technique for opportunistic access of idle resources. In CR, spectrum sensing is one of the key functionalities. It is used to sense the unused spectrum in an opportunistic manner. In this paper, we have proposed two-stage detectors for spectrum sensing in cognitive radio networks (CRN). The first stage consists of multiple energy detectors (MED), where each energy detector (ED) is having single antenna with fixed threshold (MED FT) for making a local binary decision, and if required, the second stage comprised of ED with adaptive double threshold (ED ADT) is invoked. The detection performance of the proposed scheme is compared with cyclostationary-based sensing method and adaptive spectrum sensing scheme. Numerical results show that the proposed scheme improves detection performance and outperforms the cyclostationary-based sensing method and adaptive spectrum sensing by 12.3% and 14.4% at signal to noise ratio (SNR) setting of as low as −8 dB, respectively. Performance was also measured in terms of sensing time. It is shown that the proposed scheme yields smaller sensing time than cyclostationary detection and adaptive spectrum sensing scheme in the order of 4.3 ms and 0.1 ms at −20 dB SNR, respectively.
Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficientrealization of a distinctneuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable .FPGA comprehension of ANNs through a hugeamount of neurons is mainlyan exigentassignment. This workconverses the reviews on various research articles of neural networks whose concernsfocused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution isprojected to adjust signed decimal facts. A detailed review of many research papers have been done for the <br /> proposed work.
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