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首页> 外文期刊>Telecommunication systems: Modeling, Analysis, Design and Management >Downlink resource allocation for on-demand multimedia services in high-speed railway communication systems
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Downlink resource allocation for on-demand multimedia services in high-speed railway communication systems

机译:高速铁路通信系统中按需多媒体服务的下行资源分配

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With the rapid development of high-speed railway (HSR) system, there is an increasing demand on providing high throughput and continuous multimedia (CM) services for HSR passengers. In this paper, we investigate the downlink resource allocation problem for on-demand CM services in HSR OFDMA systems with a cellular/infostation integrated network architecture. Considering both the integrity and continuity of service transmission, the resource allocation problem is formulated as a two-stage optimization programming. The aim of this study is to maximize the total reward of delivered services then to minimize the weighted total number of cumulative discontinuity packets over the trip of the train. To resolve the difficulty of multi-stage optimization, an equivalent one-stage programming is proposed. Since the resultant mixed integer programming is NP-hard in general, we reformulate it as a sparse -minimization problem and then relax it to a linear programming. Furthermore, a reweighted -minimization technique is applied to improve the system performance. Guided by the proposed optimization approaches, we next develop two efficient online resource allocation algorithms for practical systems,where a-priori knowledge of future service arrivals and channel gains is not available. Finally, simulation results are provided to validate the feasibility and effectiveness of the proposed algorithms.
机译:随着高速铁路(HSR)系统的快速发展,对HSR乘客提供高吞吐量和连续多媒体(CM)服务的需求越来越大。在本文中,我们研究了具有蜂窝/侵入综合网络架构的HSR OFDMA系统中按需CM服务的下行链路资源分配问题。考虑到服务传输的完整性和连续性,资源分配问题被制定为两级优化编程。本研究的目的是最大限度地提高交付服务的总奖励,然后最大限度地减少火车旅行中累积不连续数据包的加权总数。为了解决多级优化的难度,提出了一种等效的一阶段编程。由于结果混合整数编程是NP - 普遍的,因此我们将其重构为稀疏 - 百分之一题问题,然后将其放松到线性编程。此外,应用了重新过度的 - 衍生技术来改善系统性能。由所提出的优化方法为指导,我们接下来为实际系统开发两种有效的在线资源分配算法,其中不可用未来服务抵达和渠道增益的先验知识。最后,提供了仿真结果以验证所提出的算法的可行性和有效性。

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