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首页> 外文期刊>Communications, IEEE Transactions on >Spectrum Sensing for Cognitive Radios in Time-Variant Flat-Fading Channels: A Joint Estimation Approach
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Spectrum Sensing for Cognitive Radios in Time-Variant Flat-Fading Channels: A Joint Estimation Approach

机译：时变平坦衰落信道中认知无线电的频谱感知：联合估计方法

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摘要

Most of the existing spectrum sensing schemes utilize only the statistical property of fading channels, which unfortunately fails to cope with the time-varying fading channel that has disastrous effects on sensing performance. As a consequence, such sensing schemes may not be applicable to distributed cognitive radio networks. In this paper, we develop a promising spectrum sensing algorithm for time-variant flat-fading (TVFF) channels. We first formulate a dynamic state-space model (DSM) to characterize the evolution behaviors of two hidden states, i.e., the primary user (PU) state and the fading gain, by utilizing a two-state Markov process and another finite-state Markov chain, respectively. The summed energy, which serves as the observation of DSM, is employed for the ease of implementation. Relying on a Bayesian statistical inference framework, the sequential importance sampling based particle filtering is then exploited to numerically and recursively estimate the involved posterior probability, and thus, the PU state and the fading gain are jointly estimated in time. The estimations of two states are soft-outputs, which are successively refined with a designed iterative approach. Simulation results demonstrate that the new scheme can significantly improve the sensing performance in TVFF channels, which, in turn, provides particular promise to realistic applications.
机译：现有的大多数频谱感测方案仅利用衰落信道的统计特性，不幸的是，它无法应付对传感性能造成灾难性影响的时变衰落信道。结果，这种感测方案可能不适用于分布式认知无线电网络。在本文中，我们为时变平坦衰落（TVFF）信道开发了一种很有前途的频谱感测算法。我们首先建立动态状态空间模型（DSM），以利用两个状态的Markov过程和另一个有限状态的Markov来表征两个隐藏状态（即主要用户（PU）状态和衰落增益）的演化行为。链。为了便于实现，采用了总能量作为DSM的观测值。依靠贝叶斯统计推断框架，然后利用基于顺序重要性抽样的粒子滤波对涉及的后验概率进行数值和递归估计，从而及时地估计了PU状态和衰落增益。两种状态的估计是软输出，使用设计的迭代方法对其进行逐次完善。仿真结果表明，该方案可以显着提高TVFF信道的感测性能，从而为实际应用提供了特别的希望。

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