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Spectrum sharing in cognitive radio networks with imperfect sensing: A discrete-time Markov model

机译:具有不完善传感的认知无线电网络中的频谱共享:离散时间马尔可夫模型

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摘要

An efficient and utmost utilization of currently scarce and underutilized radio spectrum resources has stimulated the introduction of what has been coined Cognitive Radio (CR) access methodologies and implementations. While the long-established approach has been based on licensed (or primary) spectrum access, this new communication paradigm enables an opportunistic secondary access to shared spectrum resources provided mutual interference is kept below acceptable levels. In this paper we address the problem of primary-secondary spectrum sharing in cognitive radio access networks using a framework based on a Discrete Time Markov Chain (DTMC) model. Its applicability and advantages with respect to other approaches is explained and further justified. Spectrum awareness of primary activity by the secondary users is based on spectrum sensing techniques, which are modeled in order to capture sensing errors in the form of false-alarm and missed-detec-tion. Model validation is successfully achieved by means of a system-level simulator which is able to capture the system behavior with high degree of accuracy. Parameter dependencies and potential tradeoffs are identified enabling an enhanced operation for both primary and secondary users. The suitability of the specified model is justified while allowing a wide range of extended implementations and enhanced capabilities to be considered.
机译:对当前稀缺和未充分利用的无线电频谱资源的有效,最大利用,刺激了人们引入所谓的认知无线电(CR)接入方法和实现。尽管长久以来的方法是基于许可的(或主要的)频谱访问,但只要相互干扰保持在可接受的水平以下,这种新的通信范例便可以对共享频谱资源进行机会性的二次访问。在本文中,我们使用基于离散时间马尔可夫链(DTMC)模型的框架解决认知无线电接入网络中主次频谱共享的问题。相对于其他方法,它的适用性和优势得到了解释和进一步证明。次要用户对主要活动的频谱感知是基于频谱感知技术的,该技术被建模以捕获错误警报和错过检测形式的感知错误。借助于系统级仿真器可以成功完成模型验证,该系统级仿真器可以高度准确地捕获系统行为。确定了参数依存关系和潜在的权衡取舍,从而使主要用户和次要用户都可以增强操作。指定模型的适用性是合理的,同时允许考虑广泛的扩展实现和增强的功能。

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