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Blind tensor-based identification of memoryless multiuser Volterra channels using SOS and modulation codes

机译:基于盲张量的SOS和调制码无记忆多用户Volterra通道识别

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In this paper, a channel identification technique using Second Order Statistics (SOS) is proposed for memoryless multiuser Volterra communication channels. The Parallel Factor (PARAFAC) decomposition of a third order tensor formed from spatio-temporal covariance matrices of the received signals is considered by using the Alternating Least Squares (ALS) algorithm. Modulation codes (constrained codes) are used to ensure some orthogonality constraints of the transmitted signals. That constitutes a new application of modulation codes, aiming to introduce temporal redundancy and ensure some statistical properties. Identifiability conditions for the problem under consideration are addressed and simulation results illustrate the performance of the proposed estimation method.
机译:在本文中,提出了一种用于无记忆多用户Volterra通信信道的使用二阶统计(SOS)的信道识别技术。通过使用交替最小二乘(ALS)算法,考虑了由接收信号的时空协方差矩阵形成的三阶张量的并行因子(PARAFAC)分解。调制码(约束码)用于确保发射信号的某些正交性约束。这构成了调制代码的新应用,旨在引入时间冗余并确保某些统计属性。解决了所考虑问题的可识别条件,仿真结果说明了所提出估计方法的性能。

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