School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China.
Sensors (Basel). 2018 Jul 10;18(7):2222. doi: 10.3390/s18072222.
Spectrum sensing is an important task in cognitive radio. However, currently available Analog-to-Digital Converters (ADC) can hardly satisfy the sampling rate requirement for wideband signals. Even with such an ADC, the cost is extremely high in terms of price and power consumption. In this paper, we propose a spectrum-sensing method based on single-channel sub-Nyquist sampling. Firstly, a serial Multi-Coset Sampling (MCS) structure is designed to avoid mismatches among sub-ADCs in the traditional parallel MCS. Clocks of the sample/hold and ADC are provided by two non-uniform sampling clocks. The cooperation between these two non-uniform sampling clocks shifts the high sampling rate burden from the ADC to the sample/hold. Secondly, a power spectrum estimation method using sub-Nyquist samples is introduced, and an efficient spectrum-sensing algorithm is proposed. By exploiting the frequency-smoothing property, the proposed efficient spectrum-sensing algorithm only needs to estimate power spectrum at partial frequency bins to conduct spectrum sensing, which will save a large amount of computational cost. Finally, the sampling pattern design of the proposed serial MCS is given, and it is proved to be a minimal circular sparse ruler with an additional constraint. Simulations show that mismatches in traditional parallel MCS have a serious impact on spectrum-sensing performance, while the proposed serial MCS combined with the efficient spectrum-sensing algorithm exhibits outstanding spectrum-sensing performance at much lower computational cost.
频谱感知是认知无线电中的一项重要任务。然而，目前可用的模数转换器（ADC）很难满足宽带信号的采样率要求。即使使用这样的 ADC，其价格和功耗方面的成本也非常高。在本文中，我们提出了一种基于单通道欠奈奎斯特采样的频谱感知方法。首先，设计了一种串行多余弦集采样（MCS）结构，以避免传统并行 MCS 中子 ADC 之间的失配。采样/保持和 ADC 的时钟由两个非均匀采样时钟提供。这两个非均匀采样时钟的协作将高采样率负担从 ADC 转移到采样/保持。其次，引入了一种使用欠奈奎斯特样本的功率谱估计方法，并提出了一种有效的频谱感知算法。通过利用频率平滑特性，所提出的高效频谱感知算法仅需要估计部分频率-bin 的功率谱来进行频谱感知，这将节省大量的计算成本。最后，给出了所提出的串行 MCS 的采样模式设计，并证明其具有附加约束的最小循环稀疏规则。仿真结果表明，传统并行 MCS 中的失配对频谱感知性能有严重影响，而所提出的串行 MCS 结合高效频谱感知算法在更低的计算成本下表现出出色的频谱感知性能。
