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Blind source separation of instantaneous MIMO systems based on the least-squares Constant Modulus Algorithm

机译:基于最小二乘常数模算法的瞬时MIMO系统盲源分离

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摘要

Blind symbol detection for mobile communications systems has been widely studied and can be implemented by using either adaptive or iterative techniques. However, adaptive blind algorithms require data of sufficient length to converge. Therefore, in a rapidly changing environment, they are likely unable to track the changing channels. In such a situation, one possible solution is to use iterative blind algorithms. Iterative blind source separation algorithms based on the least-squares constant modulus algorithm (LSCMA) for instantaneous multiple-input multiple-output (MIMO) systems are proposed. Since the LSCMA cannot guarantee correct separation and hence cannot be used directly for MIMO channels, two extensions are considered: cancellation techniques (successive and parallel), and using an orthogonality constraint to ensure independence among different outputs. In common with many block iterative algorithms, it is found that for small block sizes there can be a BER flare-up effect at high SNR, although this can be removed for a sufficiently large block size. Of the proposed algorithms, simulation results show that the orthogonality-based algorithm has the best performance, and is comparable to iterative least-squares with projection (ILSP) algorithm, but offers cheaper computational complexity.
机译:用于移动通信系统的盲符号检测已经被广泛研究,并且可以通过使用自适应技术或迭代技术来实现。但是,自适应盲算法需要足够长的数据才能收敛。因此,在快速变化的环境中,他们很可能无法跟踪变化的渠道。在这种情况下,一种可能的解决方案是使用迭代盲算法。针对瞬时多输入多输出(MIMO)系统,提出了一种基于最小二乘恒定模量算法(LSCMA)的迭代盲源分离算法。由于LSCMA无法保证正确的分隔,因此不能直接用于MIMO信道,因此考虑了两种扩展方式:抵消技术(连续和并行),以及使用正交性约束来确保不同输出之间的独立性。与许多块迭代算法一样,发现对于小块大小,在高SNR时会出现BER突发效应,尽管对于足够大的块大小,可以将其消除。仿真结果表明,基于正交性的算法具有最好的性能,与ILSP迭代最小二乘算法具有可比性,但计算复杂度较低。

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