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Underdetermined blind separation of adjacent satellite interference in modern satellite communication systems

机译:现代卫星通信系统中相邻卫星干扰的不确定盲分离

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In this paper, a novel underdetermined blind source separation algorithm guided by particle swarm optimizer (PSO) is proposed for adjacent satellite interference in modern satellite communication systems. Different from traditional methods, we formulate the separation problem as clustering problem. Due to our algorithm is affected by the sparsity of source signals and the density of mixed vectors, our algorithm is motivated by the assumption is held that the distance between two arbitrary mixed signal vectors is less than the doubled sum of variances of distribution of the corresponding mixtures. In our method, we accomplish the underdetermined blind source separation by computing the Short Time Fourier Transform (STFT) to segment received mixtures and we use some estimates to separate the mixed source signals by PSO where the number of the mixed signals is unknown. In PSO, we define new parameters gather in formula (8) and c_(j) in formula (11). We verify the proposed method on several simulations. The experimental results demonstrate the effectiveness of the proposed method.
机译:针对现代卫星通信系统中的相邻卫星干扰,提出了一种新的不确定粒子群算法,该算法由粒子群优化器(PSO)指导。与传统方法不同,我们将分离问题公式化为聚类问题。由于我们的算法受到源信号稀疏性和混合矢量密度的影响,因此我们的算法受到以下假设的启发:两个任意混合信号矢量之间的距离小于相应信号的分布方差的两倍混合物。在我们的方法中,我们通过计算短时傅立叶变换(STFT)分割接收到的混合物来完成不确定的盲源分离,并使用一些估计值通过PSO分离混合源信号,其中混合信号的数量未知。在PSO中,我们在公式(8)中定义新参数,在公式(11)中定义 c_(j)。我们在几个模拟中验证了所提出的方法。实验结果证明了该方法的有效性。

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