As the bandwidth increases, the high-speed sampling rate becomes the bottleneck for the development of wideband spectrum sensing. Wideband spectrum sensing with sub-Nyquist sampling attracts more attention and modulated wideband converter (MWC) is an attractive sub-Nyquist sampling system. For the purpose of breaking the system structure limit, an advanced sub-Nyquist sampling framework is proposed to simplify the MWC system structure, adopting the single sampling channel structure with a frequency shifting module to acquire the sub-Nyquist sampling values. In order to recover the signal support information, the sensing matrix must be built according to the only one mixing function. Most existing support recovery methods rely on some prior knowledge about the spectrum sparsity, which is difficult to acquire in practical electromagnetic environment. To address this problem, we propose an adaptive residual energy detection algorithm (ARED), which bypasses the need for the above-mentioned prior knowledge. Simulation results show that, without requiring the aforementioned prior knowledge, the ARED algorithm based on the advanced sub-Nyquist sampling framework has the similar performance as MWC and even higher than MWC in some cases using only one sampling channel.

随着带宽的增加，高速采样率成为宽带频谱感知发展的瓶颈。具有亚奈奎斯特采样的宽带频谱感测引起了更多关注，调制宽带转换器（MWC）是一种有吸引力的亚奈奎斯特采样系统。为突破系统结构限制，提出一种先进的亚奈奎斯特采样框架，简化MWC系统结构，采用带移频模块的单采样通道结构获取亚奈奎斯特采样值。为了恢复信号支持信息，必须根据唯一的混合函数构建传感矩阵。大多数现有的支持恢复方法都依赖于一些关于频谱稀疏性的先验知识，这在实际电磁环境中很难获得。为了解决这个问题，我们提出了一种自适应剩余能量检测算法（ARED），它绕过了对上述先验知识的需求。仿真结果表明，在不需要上述先验知识的情况下，基于先进的亚奈奎斯特采样框架的 ARED 算法在仅使用一个采样通道的情况下具有与 MWC 相似的性能，甚至在某些情况下甚至高于 MWC。