基于VCG机制和POMDP强化学习的动态频谱分配算法

以认知无线网络动态频谱分配问题为研究对象,提出一种通用的动态频谱分配博弈框架,将频谱的动态变化、认知用户的可能影响频谱分配的自私的网络行为、频谱分配中的信息约束限制和分布式特性在动态频谱环境中加以考虑,通过VCG机制的部署和实施,有效的解决动态频谱分配问题,防止自私用户可能存在欺骗行为;为进一步提高认知无线网络中频谱分配方法的性能,提出了一种动态频谱分配的POMDP强化学习算法,通过认知用户依据它们自身历史信息的观察统计和学习,预测当前竞拍策略,通过累积折扣奖赏影响动态频谱分配。仿真结果表明,基于POMDP强化学习算法可以显著的改善认知用户的行为,提高动态频谱分配性能。     

Inhibition and recovery of cucumber roots given multiple treatments of ferulic acid in nutrient culture

Ferulic acid, a frequently cited allelopathic agent, inhibited photosynthesis, leaf expansion, and root elongation of cucumber seedlings grown in aerated nutrient cultures in a growth chamber. Other effects were a reduction in the proportion of radioactivity fixed by photosynthesis translocated to roots, a stimulation in secondary root initiation, and an increase in root-shoot ratios. Inhibition of leaf expansion and root elongation induced by multiple ferulic acid treatments was rapidly lost once ferulic acid was removed from the root environment. The changes in general root morphology, i.e., average root length and root number, associated with ferulic acid treatments, were partially reversed or not affected when ferulic acid was removed from the root environment.Paper No. 11411 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, North Carolina 27695-7601. The use of trade names in this publication does not imply endorsement by the North Carolina Agricultural Research Service of the products named, nor criticism of similar ones not mentioned.     

无线Mesh网络中路由与信道联合分配研究

无线Mesh网络中路由器使用多射频接口并配备多信道传输能有效增加网络吞吐量及降低干扰。研究路由与信道分配问题的目的就是增加网络容量、减少延迟等。文中针对无线Mesh网络中多接口多信道的路由与信道分配问题做了统一考虑,根据路由约束、信道约束、干扰约束以及宽带约束建立了混合整数线性规划（MILP）模型,并提出了基于迭代搜索的启发式算法很好地解决了此问题。仿真结果表明该算法可以提高网络吞吐量,降低延迟。     

Multi-channel power allocation based on market competitive equilibrium in cognitive radio networks

Cognitive radios such as intelligent phones and Bluetooth devices have been considered essential goods in next-generation communication systems.Such devices will have to share the same frequency band owing to the limited bandwidth resource.To improve spectrum efciency,we formulate multi-channel power allocation as a market competitive equilibrium(CE)problem,and prove that its solution exists and is unique under the condition of weak interference.We then propose two distributed power allocation algorithms achieving CE,namely the fast convergent power allocation algorithm(FCPAA)and the social-fairness-aware FCPAA(SFAF).Theoretical analysis and simulation results demonstrate that the proposed algorithms lead to better system performance in terms of the guaranteed interference temperature constraint using the price mechanism instead of a strategy based on the Nash equilibrium.Moreover,it is shown that the FCPAA maximizes total utility,and converges more quickly than the method addressed in prior research with the help of improved round-robin rules.However,the FCPAA cannot ensure the same social fairness among secondary users as the SFAF scheme in both the non-fading channel and Rayleigh fading channel;the SFAF balances the individual utility by adjusting each user’s budget at the expense of a small quantity of system total throughput.     

Adaptive joint bandwidth and power allocation in heterogeneous wireless access environment

Joint bandwidth and power allocation for a multi-radio access(MRA)system in a heterogeneous wireless access environment is studied.Since both the number of users being served by the system and the wireless channel state are time-varying,the optimal resource allocation is no longer a static optimum and will change with the varying network state.Moreover,distributed resource allocation algorithms that require iterative updating and signaling interactions cannot converge in negligible time.Thus,it is unrealistic to assume that the active user number and the wireless channel state remain unchanged during the iterations.In this paper,we propose an adaptive joint bandwidth and power allocation algorithm based on a novel iteration stepsize selection method,which can adapt to the varying network state and accelerate the convergence rate.A distributed solution is also designed for the adaptive joint resource allocation implementation.Numerical results show that the proposed algorithm can not only track the varying optimal resource allocation result much more quickly than a traditional algorithm with fixed iteration stepsize,but can also reduce the data transmission time for users and increase the system throughput.     

MABP: an optimal resource allocation approach in data center networks

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.     

Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection

In this paper,we consider a multi-channel cognitive radio network(CRN)where each secondary user(SU)can only choose to sense a subset of channels.We formulate a joint optimization problem of sensingchannel selection,sensing time and power allocation under the constraints of average transmit power budget and average interference power budget,which maximizes the CRN’s total throughput.We propose a greedy algorithm to solve the joint optimization problem,which has much less computational complexity.Moreover,it is shown that the search space of the greedy algorithm can be further pruned.Finally,numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm.     

矿产勘查生产要素配置中政府和市场作用分析

矿产资源是经济社会发展的重要物质基础,是国家安全的战略保障。党的二十大要求“构建全国统一大市场,深化要素市场化改革,建设高标准市场体系”,强调“充分发挥市场在资源配置中的决定性作用,更好发挥政府作用”。本文分析了近年来矿产勘查生产要素配置现状,梳理了矿产勘查中政府和市场关系演变和作用机制,从充分发挥市场决定性作用、构建“有效市场”和更好发挥政府作用、塑造“有为政府”两个方面提出对策建议,以期为充分发挥政府和市场两个主体在矿产勘查生产要素配置中的作用提供一些思路。     

塔里木河“二源一干”生态供水潜力研究

为解决塔里木河干流水资源短缺、流域损失水量过大、用水效率低下、农业灌溉用水挤占生态用水等问题,基于“节水优先”的治水方针,以塔里木河二源流(阿克苏河、叶尔羌河)及其干流(“二源一干”)的山区水库群和平原水库群为研究对象,兼顾塔里木河干流的农业灌溉用水、生态用水、工业用水、生活用水等多目标,构建并求解了现状水平年和远景规划年的山区与平原水库群联合调度优化模型,分析了塔里木河干流的生态供水潜力和山区水库群联合调度的贡献。结果表明：仅通过干流平原水库群联合调度,农业灌溉用水和生态用水的供水保证率难以满足设计要求;通过山区与平原水库群优化调度,在远景规划年各行业均满足设计保证率要求,体现了山区水库群显著的调控性能和“节水优先”治水方针的合理性和可靠性;远景规划年塔里木河干流的生态供水潜力为2.84亿m³,可为塔里木河下游生态保护与修复提供了坚实的水量基础。     

基于NOMA的5G超密网计算迁移与资源分配策略

针对5G超密网中移动设备计算能力不足、频谱资源有限的问题,提出了一种基于非正交多址接入（NOMA）的计算迁移与带宽分配策略。首先,对系统模型进行了分析,并在此基础上以最小化设备计算代价为目标对所研究的问题进行形式化定义;然后,将该问题分解成设备的计算迁移、系统的带宽分配和设备的分组匹配三个子问题,并利用模拟退火、内点法和贪心算法对这三个子问题进行求解;最后,通过联合优化算法对上述子问题进行交替性迭代求解,最终获得最优计算迁移和资源分配策略。仿真结果表明,所提出的联合优化策略不但优于传统的正交多址接入（OMA）方式,而且能获得比平均分配带宽的NOMA技术更低的设备计算代价。