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Analysis and optimization of dynamic spectrum sharing for cognitive radio networks.

机译：认知无线电网络动态频谱共享的分析和优化。

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摘要

The goal of this dissertation is to present the analysis and optimization of dynamic spectrum sharing for cognitive radio networks (CRNs). Spectrum scarcity is a well known problem at present. In order to deal with this problem, dynamic spectrum sharing (DSS) was proposed. DSS is a technique where cognitive radio networks dynamically and opportunistically share the channels with primary users. The major contribution of this dissertation is in analyzing the problem of dynamic spectrum sharing under different scenarios and developing optimal solutions for these scenarios. In the first scenario, a contention based dynamic spectrum sharing model is considered and its throughput analysis is presented. One of the applications of this throughput analysis is in finding the optimal number of secondary users in such a scenario. The problem is studied for fixed and random allocation of channels to primary users while secondary users try to opportunistically use these channels. Primary users contend for the channels, and secondary users try to use the channels only when primary users are not using it. These secondary users themselves contend for the opportunistic usage. The numerical formulas developed for finding the optimal number of secondary users have been carefully analyzed with the solutions obtained using the throughput model directly and finding the optimal number of secondary users. These two match very closely with each other and hence provide simple numerical formulas to calculate the optimal number. The second scenario studied is based upon the idea of pre-knowledge of primary user activity. For instance, the active broadcasting periods of TV channels can be obtained from past measurements as the TV channels activities are approximately fixed. In this scenario, time spectrum block (TSB) allocation for DSS is studied. Optimal TSB allocation is considered to minimize the total interference of the system and hence maximize the overall throughput of the system of community networks. The results obtained using the proposed ABCD algorithm follow very closely with the optimal results. Thus the simple algorithm developed can be used for time spectrum block allocation in practical scenarios.
机译：本文的目的是提出认知无线电网络动态频谱共享的分析和优化。频谱稀缺是目前众所周知的问题。为了解决这个问题，提出了动态频谱共享（DSS）。 DSS是一种技术，认知无线电网络可以动态地和机会地与主要用户共享频道。本文的主要贡献在于分析了不同场景下的动态频谱共享问题，并为这些场景开发了最优的解决方案。在第一种情况下，考虑了基于竞争的动态频谱共享模型，并提出了其吞吐量分析。这种吞吐量分析的应用之一是在这种情况下找到最佳的辅助用户数量。研究了为主要用户固定和随机分配频道而次要用户尝试机会性地使用这些频道的问题。主要用户争夺频道，而次要用户仅在主要用户不使用频道时才尝试使用频道。这些次要用户自己争夺机会性使用。已使用直接使用吞吐量模型获得的解决方案并找到了最佳的辅助用户数量，仔细分析了为找到最佳的辅助用户数量而开发的数值公式。这两个彼此非常接近，因此提供了简单的数值公式来计算最佳数量。研究的第二种情况是基于预先了解主要用户活动的想法。例如，由于电视频道活动大致固定，因此可以从过去的测量中获得电视频道的有效广播时段。在这种情况下，研究了DSS的时间频谱块（TSB）分配。最佳的TSB分配被认为是最小化系统的总干扰，从而最大化社区网络系统的整体吞吐量。使用建议的ABCD算法获得的结果与最佳结果非常接近。因此，所开发的简单算法可以在实际情况下用于时间频谱块分配。

著录项

  • 作者

    Wadhwa, Manish.;

  • 作者单位

    Old Dominion University.;

  • 授予单位 Old Dominion University.;
  • 学科 Engineering Computer.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 92 p.
  • 总页数 92
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 古生物学;
  • 关键词

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