This paper focuses on the issue of collaborative spectrum sensing in cognitive ultra wideband（CUWB） impulse radio. We employ energy-based signal detection method and apply the Neyman-Pearson（NP） decision rule to d...This paper focuses on the issue of collaborative spectrum sensing in cognitive ultra wideband（CUWB） impulse radio. We employ energy-based signal detection method and apply the Neyman-Pearson（NP） decision rule to determine the optimum threshold. Two cooperative spectrum sensing schemes are developed in this paper. The decision fusion scheme is based on hard decision, in which each cooperating cognitive user（CU） sends its own local decision to the fusion center（FC）. The FC then makes a final decision according to the majority voting rule. Alternatively, the data fusion scheme is based on soft decision, in which each local CU sends its observed value directly to the FC. The FC combines these values, compares to a threshold and then makes the final decision. The performances of both schemes are studied by using analytical tools and computer simulations. The receiver operating characteristics（ROC）, which reveal the probability of detection versus false-alarm curve, are employed to evaluate the system performance under different scenarios. Simulation results demonstrate that the data fusion scheme outperforms the decision fusion scheme and verify that the collaborative spectrum sensing has practical importance in CUWB networks.展开更多
This paper presents a unified theoretical analysis of the energy detection of Gaussian and M-PSK signals in κ-μ,α-μ,and η-μ fading channels at the output of an energy detector subject to impulsive noise（Bernoul...This paper presents a unified theoretical analysis of the energy detection of Gaussian and M-PSK signals in κ-μ,α-μ,and η-μ fading channels at the output of an energy detector subject to impulsive noise（Bernoulli-Gaussian model）. As a result, novel, simple, and accurately approximated expressions for the probability of detection are derived. More precisely, the generalized Gauss-Laguerre quadrature is applied to approximate the probability of detection as a simple finite sum. Monte Carlo simulations corroborate the accuracy and precision of the derived approximations. The results are further extended to cooperative energy detection with hard decision combining information.展开更多
文摘This paper focuses on the issue of collaborative spectrum sensing in cognitive ultra wideband（CUWB） impulse radio. We employ energy-based signal detection method and apply the Neyman-Pearson（NP） decision rule to determine the optimum threshold. Two cooperative spectrum sensing schemes are developed in this paper. The decision fusion scheme is based on hard decision, in which each cooperating cognitive user（CU） sends its own local decision to the fusion center（FC）. The FC then makes a final decision according to the majority voting rule. Alternatively, the data fusion scheme is based on soft decision, in which each local CU sends its observed value directly to the FC. The FC combines these values, compares to a threshold and then makes the final decision. The performances of both schemes are studied by using analytical tools and computer simulations. The receiver operating characteristics（ROC）, which reveal the probability of detection versus false-alarm curve, are employed to evaluate the system performance under different scenarios. Simulation results demonstrate that the data fusion scheme outperforms the decision fusion scheme and verify that the collaborative spectrum sensing has practical importance in CUWB networks.
基金the Institute for Advanced Studies in Communications (Iecom) for supporting this researchfunding from the Brazilian Ministry of Education through the Brazilian Scientific Mobility Program CAPES-grant 88888.037310/2013-00
文摘This paper presents a unified theoretical analysis of the energy detection of Gaussian and M-PSK signals in κ-μ,α-μ,and η-μ fading channels at the output of an energy detector subject to impulsive noise（Bernoulli-Gaussian model）. As a result, novel, simple, and accurately approximated expressions for the probability of detection are derived. More precisely, the generalized Gauss-Laguerre quadrature is applied to approximate the probability of detection as a simple finite sum. Monte Carlo simulations corroborate the accuracy and precision of the derived approximations. The results are further extended to cooperative energy detection with hard decision combining information.
