Spectrum sensing plays a key role in cognitive radio technology to acquire information on the occupancy status of the channel. Cyclostationary spectrum sensing is considered one of the most promising approaches. However, its performance is severely degraded by a mismatch between the actual and the nominal cyclic frequency [i.e. cyclic frequency offset (CFO)]. This is particularly true for vehicular networks, due to the high mobility and particularly to the presence of a non-zero radial acceleration between the transmitter and the receiver that makes the signal filtered out by the Doppler channel chirped, thus introducing the CFO. Consequently, the signal to be detected has to be properly modelled as a generalised almost-cyclostationary process. The proposed approach performs a maximum-likelihood estimation of the CFO jointly to the detection exploiting multiple cycles, through a maximisation of the generalised likelihood ratio test. The closed-form of false alarm probability is derived highlighting that this approach represents a constant false alarm rate detector. Numerical evaluations are provided to show the correctness of the theoretical analysis and that the performance is approximatively constant for a large range of CFO values. Moreover, comparisons with existing algorithms are provided.

中文翻译：

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认知车载网络中频偏下OFDM信号的多周期频谱感知

频谱感测在认知无线电技术中获得关键信息，以获取有关信道占用状态的信息。循环平稳频谱感测被认为是最有前途的方法之一。但是，其性能会因实际和标称循环频率[即循环频率偏移（CFO）]之间的不匹配而严重降低。由于高移动性，特别是由于发射机和接收机之间存在非零的径向加速度，使得通过多普勒信道滤除的信号线性调频，因此引入了CFO，因此对于车载网络尤其如此。因此，必须将要检测的信号适当地建模为广义的几乎循环平稳的过程。所提出的方法通过最大化广义似然比检验，对利用多个周期的检测联合执行CFO的最大似然估计。得出错误警报概率的闭合形式，突出表明此方法代表恒定的错误警报率检测器。提供了数值评估，以显示理论分析的正确性，并且对于大范围的CFO值，性能近似恒定。此外，提供了与现有算法的比较。提供了数值评估，以显示理论分析的正确性，并且对于大范围的CFO值，性能近似恒定。此外，提供了与现有算法的比较。提供了数值评估，以显示理论分析的正确性，并且对于大范围的CFO值，性能近似恒定。此外，提供了与现有算法的比较。