Spectrum sensing is the key and premise of cognitive radio( CR). Current parallel cooperative spectrum sensing strategies have some problems,such as large number of cooperative secondary users and lack of consideratio...Spectrum sensing is the key and premise of cognitive radio( CR). Current parallel cooperative spectrum sensing strategies have some problems,such as large number of cooperative secondary users and lack of consideration for the sensing overhead and the transmission gain. To solve those problems,an optimized parallel cooperative spectrum sensing strategy based on iterative KuhnMunkres( KM) algorithm was proposed. To maximize the total system profit,it considers the tradeoff between the sensing overhead and the transmission gain. Iterative KM algorithm was applied to obtaining the optimal assignment,which indicated when and which channels secondary users should sense. Furthermore,the required detection probability was introduced to avoid unnecessary waste when the accuracy met the system requirement. Monte Carlo simulations show that the proposed strategy can obtain higher total system profit with fewer cooperative secondary users.展开更多
A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encod...A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encoding scheme is adopted for KKT multipliers,and then the complementarity slackness problem is simplified to successive quadratic programming problems,which can be solved by many algorithms available.Based on 0-1 binary encoding,an orthogonal genetic algorithm,in which the orthogonal experimental design with both two-level orthogonal array and factor analysis is used as crossover operator,is proposed.Numerical experiments on 10 benchmark examples show that the orthogonal genetic algorithm can find global optimal solutions of quadratic bilevel programming problems with high accuracy in a small number of iterations.展开更多
针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资...针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资源,使得飞机编队对组网雷达系统的协同干扰效能始终保持最优。首先,根据雷达网不同的工作状态和信息融合规则,构建基于检测概率和瞄准概率的双因子干扰效能评估函数,然后考虑干扰资源约束建立关于目标选择和功率分配的双变量非凸优化模型,并基于此提出了一种结合改进布谷鸟搜索(improved cuckoo search,ICS)算法与KKT(Karush-Kuhn-Tucker,KKT)优化条件的求解方法。最后,仿真结果证明了所提联合资源自适应调度策略的有效性。展开更多
基金Young Scientists Fund of the National Natural Science Foundation of China(No.61101141)Fundamental Research Funds for the Central Universities of China(No.HEUCF130807)Heilongjiang Province Natural Science Foundation for the Youth,China(No.QC2012C070/F010106)
文摘Spectrum sensing is the key and premise of cognitive radio( CR). Current parallel cooperative spectrum sensing strategies have some problems,such as large number of cooperative secondary users and lack of consideration for the sensing overhead and the transmission gain. To solve those problems,an optimized parallel cooperative spectrum sensing strategy based on iterative KuhnMunkres( KM) algorithm was proposed. To maximize the total system profit,it considers the tradeoff between the sensing overhead and the transmission gain. Iterative KM algorithm was applied to obtaining the optimal assignment,which indicated when and which channels secondary users should sense. Furthermore,the required detection probability was introduced to avoid unnecessary waste when the accuracy met the system requirement. Monte Carlo simulations show that the proposed strategy can obtain higher total system profit with fewer cooperative secondary users.
基金supported by the National Natural Science Foundation of China (60873099)
文摘A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encoding scheme is adopted for KKT multipliers,and then the complementarity slackness problem is simplified to successive quadratic programming problems,which can be solved by many algorithms available.Based on 0-1 binary encoding,an orthogonal genetic algorithm,in which the orthogonal experimental design with both two-level orthogonal array and factor analysis is used as crossover operator,is proposed.Numerical experiments on 10 benchmark examples show that the orthogonal genetic algorithm can find global optimal solutions of quadratic bilevel programming problems with high accuracy in a small number of iterations.
文摘针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资源,使得飞机编队对组网雷达系统的协同干扰效能始终保持最优。首先,根据雷达网不同的工作状态和信息融合规则,构建基于检测概率和瞄准概率的双因子干扰效能评估函数,然后考虑干扰资源约束建立关于目标选择和功率分配的双变量非凸优化模型,并基于此提出了一种结合改进布谷鸟搜索(improved cuckoo search,ICS)算法与KKT(Karush-Kuhn-Tucker,KKT)优化条件的求解方法。最后,仿真结果证明了所提联合资源自适应调度策略的有效性。
