在过去大多数的研究中,带噪1-bit分布式压缩感知局限于使用高斯随机测量矩阵进行信号的重构。但是,这类矩阵内存消耗大,计算速度慢,阻碍了实际应用的发展。因此,作为改进,本文考虑将结构化的部分高斯循环矩阵应用于带噪1-bit分布式压缩...在过去大多数的研究中,带噪1-bit分布式压缩感知局限于使用高斯随机测量矩阵进行信号的重构。但是,这类矩阵内存消耗大,计算速度慢,阻碍了实际应用的发展。因此,作为改进,本文考虑将结构化的部分高斯循环矩阵应用于带噪1-bit分布式压缩感知当中。部分高斯循环矩阵可以通过快速傅里叶变换显著降低计算复杂度,提高恢复效率。为此,我们提出了新的鲁棒1-bit分布式压缩感知恢复算法。该算法通过计算符号不一致的数量,可以自适应地检测到符号翻转的位置,并进行修正。数值实验表明,在存在测量噪声和传输噪声的情况下,部分高斯循环矩阵和高斯随机矩阵的恢复性能相当。在此基础上,部分高斯循环矩阵的恢复时间更短,重构效率更高。In most previous studies, noisy 1-bit distributed compressed sensing has been limited to the use of Gaussian random measurement matrices for signal reconstruction. However, such matrices consume significant memory and have slow computational speeds, which hinder the development of their practical application. Therefore, as an improvement, this paper considers the application of structured partial Gaussian circulant matrices to noisy 1-bit distributed compressed sensing. Partial Gaussian circulant matrices can significantly reduce computational complexity and improve recovery efficiency through fast Fourier transform. To this end, we propose a new robust 1-bit distributed compressed sensing recovery algorithm. This algorithm can adaptively detect and correct sign flip positions by calculating the number of sign inconsistencies. Numerical experiments demonstrate that, in the presence of measurement noise and transmission noise, the recovery performance of partial Gaussian circulant matrices is comparable to that of Gaussian random matrices. Furthermore, the recovery time of partial Gaussian circulant matrices is shorter, and the reconstruction efficiency is higher.展开更多
Compared to high-resolution digital-toanalog converters(DACs), deploying 1-bit DACs requires much less hardware complexity for a massive multi-user multiple-input multiple-output(MUMIMO) system. However, the feasible ...Compared to high-resolution digital-toanalog converters(DACs), deploying 1-bit DACs requires much less hardware complexity for a massive multi-user multiple-input multiple-output(MUMIMO) system. However, the feasible domain of a1-bit transmitting signal is non-continuous, and thus it is more challenging to exploit multi-user interference(MUI) by precoding. In this paper, to improve symbol decision accuracy, we investigate MUI exploitation 1-bit precoding methods for massive MU-MIMO systems under QAM modulations. Because MUIs may be constructive or destructive, we define a modified mean square error(MSE) metric for QAM constellations to jointly evaluate the effect of both MUIs and noise. Then, we model the 1-bit precoding optimization problems to minimize the sum modified MSE or the maximum modified MSE, where both the transmitting vector and receiving processing factor are optimization variables. Based on whether the receiving processing factor remains constant during the whole transmission block, two scenarios are taken into consideration. Referring to existing interference exploitation 1-bit precoding methods, we design efficient algorithms to solve the two modified MSE based problems.Compared to existing 1-bit precoding methods, our proposed methods provide better bit error rate performance, especially in more practical scenario Ⅱ(constant receiving processing factor in one block).展开更多
1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论...1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论分析可知相对于高精度脉压系数,1-bit脉压系数会带来额外的脉压信噪比损失,但实现方式更为简单。此外,分析了在高信噪比下,发射信号为线性调频(linear frequency modulation,LFM)信号时周期性假目标出现的原因,并且指出相位编码可有效避免假目标出现。仿真实验验证了以上理论推导的正确性。最后,结合某高频(high frequency,HF)地波雷达的实测数据验证了1-bit采样的可行性。展开更多
文摘在过去大多数的研究中,带噪1-bit分布式压缩感知局限于使用高斯随机测量矩阵进行信号的重构。但是,这类矩阵内存消耗大,计算速度慢,阻碍了实际应用的发展。因此,作为改进,本文考虑将结构化的部分高斯循环矩阵应用于带噪1-bit分布式压缩感知当中。部分高斯循环矩阵可以通过快速傅里叶变换显著降低计算复杂度,提高恢复效率。为此,我们提出了新的鲁棒1-bit分布式压缩感知恢复算法。该算法通过计算符号不一致的数量,可以自适应地检测到符号翻转的位置,并进行修正。数值实验表明,在存在测量噪声和传输噪声的情况下,部分高斯循环矩阵和高斯随机矩阵的恢复性能相当。在此基础上,部分高斯循环矩阵的恢复时间更短,重构效率更高。In most previous studies, noisy 1-bit distributed compressed sensing has been limited to the use of Gaussian random measurement matrices for signal reconstruction. However, such matrices consume significant memory and have slow computational speeds, which hinder the development of their practical application. Therefore, as an improvement, this paper considers the application of structured partial Gaussian circulant matrices to noisy 1-bit distributed compressed sensing. Partial Gaussian circulant matrices can significantly reduce computational complexity and improve recovery efficiency through fast Fourier transform. To this end, we propose a new robust 1-bit distributed compressed sensing recovery algorithm. This algorithm can adaptively detect and correct sign flip positions by calculating the number of sign inconsistencies. Numerical experiments demonstrate that, in the presence of measurement noise and transmission noise, the recovery performance of partial Gaussian circulant matrices is comparable to that of Gaussian random matrices. Furthermore, the recovery time of partial Gaussian circulant matrices is shorter, and the reconstruction efficiency is higher.
文摘Compared to high-resolution digital-toanalog converters(DACs), deploying 1-bit DACs requires much less hardware complexity for a massive multi-user multiple-input multiple-output(MUMIMO) system. However, the feasible domain of a1-bit transmitting signal is non-continuous, and thus it is more challenging to exploit multi-user interference(MUI) by precoding. In this paper, to improve symbol decision accuracy, we investigate MUI exploitation 1-bit precoding methods for massive MU-MIMO systems under QAM modulations. Because MUIs may be constructive or destructive, we define a modified mean square error(MSE) metric for QAM constellations to jointly evaluate the effect of both MUIs and noise. Then, we model the 1-bit precoding optimization problems to minimize the sum modified MSE or the maximum modified MSE, where both the transmitting vector and receiving processing factor are optimization variables. Based on whether the receiving processing factor remains constant during the whole transmission block, two scenarios are taken into consideration. Referring to existing interference exploitation 1-bit precoding methods, we design efficient algorithms to solve the two modified MSE based problems.Compared to existing 1-bit precoding methods, our proposed methods provide better bit error rate performance, especially in more practical scenario Ⅱ(constant receiving processing factor in one block).
文摘1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论分析可知相对于高精度脉压系数,1-bit脉压系数会带来额外的脉压信噪比损失,但实现方式更为简单。此外,分析了在高信噪比下,发射信号为线性调频(linear frequency modulation,LFM)信号时周期性假目标出现的原因,并且指出相位编码可有效避免假目标出现。仿真实验验证了以上理论推导的正确性。最后,结合某高频(high frequency,HF)地波雷达的实测数据验证了1-bit采样的可行性。
