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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach
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QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach

机译：基于认知无线电的智能电网中的QoS差分调度：一种自适应动态规划方法

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摘要

As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
机译：作为下一代电网，智能电网将与各种新颖的通信技术集成在一起，以支持爆炸性数据流量和服务质量（QoS）的各种要求。认知无线电（CR）具有改善频谱利用率的良好能力，它为智能电网通信网络提供了有效而可靠的解决方案。在本文中，我们研究了基于CR的智能电网通信网络中的QoS差分调度问题。调度程序负责管理频谱资源并安排智能电网用户（SGU）的数据传输。为了保证差异QoS，根据SGU的角色和它们在智能电网中的当前状况，为它们分配了不同的优先级。调度程序基于QoS感知优先级策略，调整信道分配，以最大程度地减少SGU的传输延迟。将整个传输调度问题表述为半马尔可夫决策过程，并通过自适应动态规划的方法进行求解。针对调度问题建立了启发式动态规划（HDP）体系结构。通过在线网络培训，HDP可以从主要用户和SGU的活动中学习，并调整调度决策，以达到最小化传输时延的目的。仿真结果表明，所提出的优先级策略确保了高优先级SGU的低传输延迟。此外，紧急数据传输延迟也降低到了很低的水平，从而确保了智能电网中的QoS差异。

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