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Tensor-Based Receiver for Joint Channel, Data, and Phase-Noise Estimation in MIMO-OFDM Systems
IEEE Journal of Selected Topics in Signal Processing ( IF 7.5 ) Pub Date : 2021-02-24 , DOI: 10.1109/jstsp.2021.3061917
Bruno Sokal , Paulo R. B. Gomes , Andre L. F. de Almeida , Martin Haardt

Phase-noise is a system impairment caused by the mismatch between the oscillators at the transmitter and the receiver. In OFDM systems, this induces inter-carrier-interference (ICI) by rotating the transmitted symbols. Thus it can cause severe system performance degradation. To reduce its effects, the phase-noise must be estimated or compensated. In this work, we propose a two-stage tensor-based receiver for a joint channel, phase-noise (PN), and data estimation in MIMO-OFDM systems. In the first stage, we show that the received signal at the pilot subcarriers can be modeled as a third-order PARAFAC tensor. Based on this model, we propose two algorithms for channel and phase-noise estimation at the pilot subcarriers. The first algorithm, based on the BALS (Bilinear Alternating Least Squares), is an iterative algorithm that estimates the channel gains and the phase-noise impairments. The second is a closed-form algorithm based on the LS-KRF (Least Squares - Khatri-Rao Factorization) that estimates the channel gains and the phase-noise terms through multiple rank-one factorizations. Both algorithms achieve similar performance, but in terms of computational complexity, we show that the LS-KRF becomes more attractive than the BALS as the number of receive antennas is increased. The second stage consists of data estimation, for which we propose a ZF (Zero-Forcing) receiver that capitalizes on the PARATuck tensor structure of the received signal at the data subcarriers using the Selective Kronecker Product (SKP) operator. Our numerical simulations show that the proposed receiver achieves an improved performance compared to the state-of-art receivers in terms of symbol error rate (SER) and normalized mean square error (NMSE) of the estimated channel and phase-noise matrices.

中文翻译:

基于张量的接收器,用于MIMO-OFDM系统中的联合信道,数据和相位噪声估计

相位噪声是由于发射器和接收器的振荡器之间不匹配而引起的系统损伤。在OFDM系统中,这通过旋转传输的符号来引起载波间干扰(ICI)。因此,它可能导致严重的系统性能下降。为了减少其影响,必须估算或补偿相位噪声。在这项工作中,我们为MIMO-OFDM系统中的联合信道,相位噪声(PN)和数据估计提出了一个基于两级张量的接收器。在第一阶段,我们表明可以将导频子载波上的接收信号建模为三阶PARAFAC张量。基于该模型,我们提出了两种用于导频子载波的信道和相位噪声估计的算法。第一个基于BALS(双线性交替最小二乘)的算法,是一种迭代算法,用于估计通道增益和相位噪声损伤。第二种是基于LS-KRF(最小二乘-Khatri-Rao因式分解)的闭式算法,该算法通过多个秩一因式分解来估计通道增益和相位噪声项。两种算法都具有相似的性能,但是在计算复杂度方面,我们表明随着接收天线数量的增加,LS-KRF比BALS更具吸引力。第二阶段包括数据估计,为此,我们提出了一个ZF(零强制)接收机,该接收机利用选择性Kronecker乘积(SKP)运算符,利用数据子载波处接收信号的PARATuck张量结构来利用。
更新日期:2021-04-02
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