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Frequency allocation, transmit power control, and load balancing with site specific knowledge for optimizing wireless network performance.

机译:频率分配,发射功率控制和负载平衡以及特定于站点的知识,可优化无线网络性能。

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摘要

This dissertation is the first analytical and algorithmic work to exhibit the substantial gains that result from applying site specific knowledge to frequency allocation, transmit power control, and load balancing in wireless networks. Site specific knowledge refers to the use of knowledge of the surrounding propagation environment, building layouts, the locations of access points (APs) and clients, and the locations and electrical properties of physical objects. We assume a central network controller communicates with all APs, and has site specific knowledge which enables the controller to differentiate the sources of RF interference at every AP or user. By predicting the power from each interference source, the controller can allocate frequency channels, adjust transmit power levels, and balance loads among APs and clients in order to optimize throughput of the network. When site specific knowledge is not available, measurement-based algorithms may be used; we present three measurement-based frequency allocation algorithms that outperform the best published work by 18% for median user throughput. Then we present two site-specific knowledge-based frequency allocations that outperform the proposed measurement-based algorithms particularly for uplifting throughputs of the users who suffer low throughputs, e.g., we have gains of 3.75%, 11.8%, 10.2%, 18.2%, 33.3%, and 459% for 50, 25, 20, 15, 10, and 5 percentiles of user throughputs, respectively, over the proposed measurement-based algorithms. Furthermore, we employ transmit power control to further improve clients' throughputs achieved by optimal site-specific knowledge-based frequency allocations; transmit power control can improve the 25, 10, 5, and 3 percentiles of users' throughputs by up to 4.2%, 9.9%, 38%, and 110%, and save power by 20%. Finally, a load balancing algorithm is proposed as an add-on that works seamlessly with frequency allocation and transmit power control algorithms. The load-balancing algorithm can improve median user throughput by about 26%. The work in this dissertation shows that site specific knowledge is an important means for optimizing performance of wireless networks.
机译:这篇论文是第一个分析和算法工作,它展示了将站点特定知识应用于频率分配,发射功率控制和无线网络中的负载平衡所带来的实质性收益。特定于站点的知识是指对周围传播环境,建筑物布局,访问点(AP)和客户端的位置以及物理对象的位置和电气特性的了解。我们假设中央网络控制器与所有AP通信,并且具有特定于站点的知识,这使控制器能够区分每个AP或用户的RF干扰源。通过预测来自每个干扰源的功率,控制器可以分配频道,调整发射功率水平以及在AP和客户端之间平衡负载,以优化网络的吞吐量。如果无法获得特定地点的知识,则可以使用基于度量的算法;我们提出了三种基于测量的频率分配算法,这些算法在中位数用户吞吐量方面比最佳公开作品要高出18%。然后,我们提出两种基于特定站点的基于知识的频率分配,其性能优于建议的基于测量的算法,特别是在提升吞吐量较低的用户的吞吐量方面,例如,我们获得了3.75%,11.8%,10.2%,18.2%,与建议的基于测量的算法相比,分别有50%,25%,20%,15%,10%和5%的用户吞吐量分别占33.3%和459%。此外,我们采用发射功率控制,通过基于特定站点的最佳知识型频率分配来进一步提高客户的吞吐量;发射功率控制可以将用户吞吐量的25%,10%,5%和3%提高多达4.2%,9.9%,38%和110%,并节省20%的功率。最后,提出了一种负载均衡算法作为附加组件,可与频率分配和发射功率控制算法无缝地协同工作。负载平衡算法可以将中位数用户吞吐量提高约26%。本文的工作表明,针对特定地点的知识是优化无线网络性能的重要手段。

著录项

  • 作者

    Chen, Jeremy Kang-pen.;

  • 作者单位

    The University of Texas at Austin.;

  • 授予单位 The University of Texas at Austin.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:39:26

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