A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with ...A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with the primary user by imposing severe constraints on the transmission power so that the quality of service of the primary user is not degraded by the interference caused by the secondary user. The effect of the cognitive relay node on the proposed cognitive relay network model is studied by evaluating the outage probability under interference power constraints for different fading environments. A relay transmission scheme, namely, decode-and-forward is considered. For both the peak and average interference power constraints, the closed-form outage expressions are derived over different channel fading models. Finally, the analytical outage probability expressions are validated through simulations. The results indicate that the proposed model has better outage probability than direct transmission. It is also found that the outage probability decreases with the increase of interference power constraints. Meanwhile, the outage probability under the average interference power constraint is much less than that under the peak interference power constraint when the average interference power constraint is equal to the peak interference power constraint.展开更多
The bilevel programming is applied to solve hierarchical intelligence control problems in such fields as industry, agriculture, transportation, military, and so on. This paper presents a quadratic objective penalty fu...The bilevel programming is applied to solve hierarchical intelligence control problems in such fields as industry, agriculture, transportation, military, and so on. This paper presents a quadratic objective penalty function with two penalty parameters for inequality constrained bilevel programming. Under some conditions, the optimal solution to the bilevel programming defined by the quadratic objective penalty function is proved to be an optimal solution to the original bilevel programming. Moreover, based on the quadratic objective penalty function, an algorithm is developed to l^nd an optimal solution to the original bilevel programming, and its convergence proved under some conditions. Furthermore, under the assumption of convexity at function without lower level problems is defined and lower level problems, a quadratic objective penalty is proved equal to the original bilevel programming.展开更多
We derive exact near-wall and centerline constraints and apply them to improve a recently proposed LPR model for finite Reynolds number(Re) turbulent channel flows.The analysis defines two constants which are invarian...We derive exact near-wall and centerline constraints and apply them to improve a recently proposed LPR model for finite Reynolds number(Re) turbulent channel flows.The analysis defines two constants which are invariant with Re and suggests two more layers for incorporating boundary effects in the prediction of the mean velocity profile in the turbulent channel.These results provide corrections for the LPR mixing length model and incorrect predictions near the wall and the centerline.Moreover,we show that the analysis,together with a set of well-defined sensitive indicators,is useful for assessment of numerical simulation data.展开更多
基金Supported by National Natural Science Foundation of China (No. 60972039, 60905040 and 60972041 )National High Technology Research and Development Program of China (No. 2009AA01Z241)+3 种基金National Postdoctoral Research Program (No. 20090451239)Important National Science and Technology Specific Projects of China (No. 2009ZX03003-006)Scientific Research Foundation of Nanjing University of Posts and Telecommunications (No. NY210006)Key Teaching Reform Foundation of NUPT (No. JG00210JX01)
文摘A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with the primary user by imposing severe constraints on the transmission power so that the quality of service of the primary user is not degraded by the interference caused by the secondary user. The effect of the cognitive relay node on the proposed cognitive relay network model is studied by evaluating the outage probability under interference power constraints for different fading environments. A relay transmission scheme, namely, decode-and-forward is considered. For both the peak and average interference power constraints, the closed-form outage expressions are derived over different channel fading models. Finally, the analytical outage probability expressions are validated through simulations. The results indicate that the proposed model has better outage probability than direct transmission. It is also found that the outage probability decreases with the increase of interference power constraints. Meanwhile, the outage probability under the average interference power constraint is much less than that under the peak interference power constraint when the average interference power constraint is equal to the peak interference power constraint.
基金supported by the National Natural Science Foundation of China under Grant Nos.11271329 and 10971193
文摘The bilevel programming is applied to solve hierarchical intelligence control problems in such fields as industry, agriculture, transportation, military, and so on. This paper presents a quadratic objective penalty function with two penalty parameters for inequality constrained bilevel programming. Under some conditions, the optimal solution to the bilevel programming defined by the quadratic objective penalty function is proved to be an optimal solution to the original bilevel programming. Moreover, based on the quadratic objective penalty function, an algorithm is developed to l^nd an optimal solution to the original bilevel programming, and its convergence proved under some conditions. Furthermore, under the assumption of convexity at function without lower level problems is defined and lower level problems, a quadratic objective penalty is proved equal to the original bilevel programming.
基金supported by the National Natural Science Foundation of China (Grant Nos. 90716008 and 10921202)the National Basic Research Program of China (Grant No. 2009CB724100)
文摘We derive exact near-wall and centerline constraints and apply them to improve a recently proposed LPR model for finite Reynolds number(Re) turbulent channel flows.The analysis defines two constants which are invariant with Re and suggests two more layers for incorporating boundary effects in the prediction of the mean velocity profile in the turbulent channel.These results provide corrections for the LPR mixing length model and incorrect predictions near the wall and the centerline.Moreover,we show that the analysis,together with a set of well-defined sensitive indicators,is useful for assessment of numerical simulation data.
