The allocation of scarce spectral resources to support as many user applications as possible while maintaining reasonable quality of service is a fundamental problem in wireless communication. We argue that the problem is best formulated in terms of decision theory. We propose a scheme that takes decision-theoretic concerns (like preferences) into account and discuss the difficulties and subtleties involved in apply standard techniques from the theory of Markov Decision Processes (MDPs) in constructing an algorithm that is decision-theoretically optimal. As an example of the proposed framework, we construct such an algorithm under some simplifying assumptions. Additionally, we present analysis and simulation results that show that our algorithm meets its design goals. Finally, we investigate how far from optimal one well-known heuristic is. The main contribution of our results is in providing insight and guidance for the design of near-optimal admission-control policies.
分配稀缺的频谱资源以支持尽可能多的用户应用程序,同时保持合理的服务质量是无线通信中的一个基本问题。我们认为,最好用决策理论来解决这个问题。我们提出了一种考虑决策理论问题(如偏好)的方案,并讨论了从马尔可夫决策过程(MDP)理论构建标准理论上最佳算法时应用标准技术所涉及的困难和微妙之处。作为所提出框架的示例,我们在一些简化的假设下构造了这样的算法。此外,我们提供的分析和仿真结果表明我们的算法符合其设计目标。最后,我们研究一种最佳的启发式算法离理想还有多远。我们的研究结果的主要贡献在于为设计接近最优的准入控制策略提供了见识和指导。 P>
机译:在云计算环境中使用分布式启发式算法的无线传感器网络多媒体资源分配策略
机译:无线多媒体传感器网络中面向QoS的高效资源分配方案
机译:节能无线网络的多媒体中继资源分配:具有低层多样性合作的高层内容优先级
机译:具有多媒体服务CDMA无线网络下行链路的基于实用的资源分配方法
机译:资源受限的无线网络的决策理论方法
机译:低移动性的多跳多媒体无线传感器网络中的动态任务分配
机译:无线资源配置的决策理论方法 多媒体网络