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Empirical Time-Dimension Model of Spectrum Use Based on a Discrete-Time Markov Chain With Deterministic and Stochastic Duty Cycle Models

机译:基于离散时间马尔可夫链的确定性和随机占空比模型的频谱使用经验时间维度模型

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摘要

The spectrum occupancy models widely used to date in dynamic spectrum access/cognitive radio (DSA/CR) research frequently rely on assumptions and oversimplifications that have not been validated with empirical measurement data. In this context, this paper presents an empirical time-dimension model of spectrum use that is appropriate for DSA/CR studies. Concretely, a two-state discrete-time Markov chain with novel deterministic and stochastic duty cycle models is proposed as an adequate mean to accurately describe spectrum occupancy in the time domain. The validity and accuracy of the proposed modeling approach is evaluated and corroborated with extensive empirical data from a multiband spectrum measurement campaign. The obtained results demonstrate that the proposed approach is able to accurately capture and reproduce the relevant statistical properties of spectrum use observed in real-world channels of various radio technologies. The importance of accurately modeling spectrum use in the design and evaluation of novel DSA/CR techniques is highlighted with a practical case study.
机译:迄今为止,在动态频谱访问/认知无线电(DSA / CR)研究中广泛使用的频谱占用模型通常依赖于未经经验测量数据验证的假设和过分简化。在这种情况下,本文提出了适用于DSA / CR研究的频谱使用经验时维模型。具体地,提出了具有新颖的确定性和随机占空比模型的两状态离散时间马尔可夫链,作为在时域中准确描述频谱占用的充分手段。所提出的建模方法的有效性和准确性得到了评估,并得到了来自多频带频谱测量活动的大量经验数据的证实。获得的结果表明,所提出的方法能够准确地捕获和再现在各种无线电技术的真实世界信道中观察到的频谱使用的相关统计特性。实际案例研究突出了在新型DSA / CR技术的设计和评估中准确建模频谱使用的重要性。

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