煤炭码头船货匹配下泊位动态分配多目标优化模型及算法

本文针对输出型煤炭码头船货匹配下泊位动态分配问题,构建了堆场-取装线-泊位-船舶联合分配优化数学模型,并设计了采用仿真推演策略解码的遗传算法求解。首先,综合考虑船舶、泊位、堆场、取装线、煤种、航道开放时间和装船作业规则等要素,以船舶在港时间最短和作业效率最大为目标建立了相应的多约束多目标优化模型。然后,综合多目标优化、遗传算法以及仿真推演技术,设计了相应的遗传算法求解,包括:组合式编码、采用仿真推演策略的解码方法,追加了具有合法性检查的染色体生成算法,设计了采用多种策略的遗传操作等。最后实例表明,本算法的执行效率高而且优化效果好。     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

认知雷达抗干扰中的博弈论分析综述

雷达对抗的核心研究内容主要是干扰策略与抗干扰策略之间的对抗博弈,其作为电子战研究领域的热点一直备受学者们关注.该文综述了学者们利用合作与非合作博弈方法来分析雷达在进行目标探测和干扰抑制时所使用的策略,主要通过不同体制的雷达利用认知技术感知和学习外界复杂的电磁环境,合理地分配发射功率、控制编码序列、设计波形、研究检测和跟踪方法以及分配雷达通信资源等.这样雷达既节约发射所消耗的功率,又可以自适应地搜索和跟踪目标而不被敌方所发现,从而使雷达在复杂多变的现代战场环境中达到自身最优的性能.最后,对认知雷达抗干扰中的博弈论分析研究进行总结和展望,并指出了一些博弈论在认知雷达抗干扰策略应用中所面临的潜在问题和挑战.     

REATMENT AND RESOURCE REUSE OF 1,2,4-ACID PRODUCING EFFLUENT WITH MACROPOROUS POLYMERIC ADSORBENT

1. INTRODUCTION 1,2,4-acid (1-Amino-2-naphthol-4-sulfonic acid) is among the most important naphthalene derivatives which are widely used as the intermediates of dyestuffs. In its production process, however, high strength wastewater streams are gene…     

基于拍卖的网络带宽分配方法的研究

基于拍卖的网络带宽分配方法的研究日益受到学术界的重视,主要集中在具有激励兼容性的Vickrey拍卖上.本文首先分析并比较了目前最具代表性的两种Vickrey拍卖方案(灵活市场模型和改进的第二价格拍卖),指出其在网络可扩展性、工程效率等方面的不足.然后提出了一种新的基于统一价格拍卖的资源分配算法,论证了其在网络这一特定环境中具有激励兼容性.该算法具有与网络状态无关的特性和更高的运行效率.最后,用NS-2仿真平台验证了该算法的有效性.     

协作D2D异构网络的联合资源分配和功率控制

针对下行协作D2D(Device-to-Device)异构网络中复用蜂窝用户的联合资源分配和功率控制问题,提出了一种量子珊瑚礁优化算法(Quantum Coral Reef Optimization Algorithm,QCROA).首先,构建异构网络模型并推导得到整个网络总吞吐量的数学表达式;其次,基于QCROA算法...     

A novel low-complexity power allocation algorithm based on the NOMA system in a low-speed environment

For future wireless communication systems, Power Domain Non-Orthogonal Multiple Access (PD-NOMA) using an advanced receiver has been considered as a promising radio access technology candidate. Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput (GMUT) performance. However, most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals (UTs) move in a slow fading channel environment. To resolve such problems, a power allocation method is proposed to considerably reduce the search space of a Full Search Power (FSP) allocation algorithm. The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance. Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process. The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5% compared with the FSP algorithm.     

基于单亲遗传算法的火力分配方法

提出了将单亲遗传算法应用于火力分配问题的方法,该方法既保持了传统遗传算法的诸多优点,又克服了传统遗传算法要求种群多样性、易陷入局部最优和实时性差等缺点。单亲遗传算法使用经过简化的遗传操作算子,算法的复杂度大大降低,可以应用于实时性要求较高的场合。仿真结果表明,单亲遗传算法能有效地解决火力分配问题,是一种简单、有效和快速的算法,具有很好的应用价值。     

双参数跨层自适应资源分配算法研究

针对多用户OFDM系统,该文提出了一种适合于混合业务的双参数跨层自适应资源分配方案,它只需调整时延补偿因子和吞吐量补偿因子两个参数,就可将现有的调度算法灵活高效地应用于系统中.仿真结果表明,该方案可以灵活地在系统功率效率和用户服务质量满意度之间取得折衷,并保证不同类型业务用户间的公平性.     

Optimal distributed power allocation for a new spectrum sharing paradigm in cognitive radio networks

The problem of power allocation in cognitive radio networks plays an important role to improve the efficiency of spectrum utilization. However, most of previous works focus on the power allocation for secondary users in spectrum sharing overlay or spectrum sharing underlay, which needs to frequently handoff between the idle spectrum bands or considers the interference constraints in all spectrum bands respectively. In order to reduce the handoff and fully utilize the spectrum resource, we propose a new spectrum sharing paradigm which not only can just need to adjust the transmit power in spectrum bands instead of frequently handoff between idle spectrum bands, but can fully utilize the spectrum resource as we only consider the interference power constraints in active spectrum bands rather than in all spectrum bands. Then based on this new spectrum sharing paradigm and the constraint conditions, we study the distributed power allocation for secondary users and formulate the optimization problem as a non-cooperative game problem, after that the variational inequality approach is used to solve this game problem and a Nash equilibria solution is got, finally simulation results are illustrated to demonstrate the performance of the proposed scheme.