Phase noise (PN) is a major disturbance in MIMO systems, where the contribution of different oscillators at the transmitter and the receiver side may degrade the overall performance and offset the gains offered by MIMO techniques. This is even more crucial in the case of massive MIMO, since the number of PN sources may increase considerably. In this work, we propose an iterative receiver based on the application of the expectation-maximization algorithm. We consider a massive MIMO framework with a general association of oscillators to antennas, and include other channel disturbances like imperfect channel state information and Rician block fading. At each receiver iteration, given the information on the transmitted symbols, steepest descent is used to estimate the PN samples, with an optimized adaptive step size and a threshold-based stopping rule. The results obtained for several test cases show how the bit error rate and mean square error can benefit from the proposed phase-detection algorithm, even to the point of reaching the same performance as in the case where no PN is present{\color{black}, offering better results than a state-of-the-art alternative}. Further analysis of the results allow to draw some useful trade-offs respecting final performance and consumption of resources.

翻译：相位噪声（PN）是多输入多输出（MIMO）系统中的主要干扰因素，发射端和接收端不同振荡器产生的相位噪声可能降低系统整体性能，抵消MIMO技术带来的增益。在大规模MIMO场景下，这一问题尤为关键，因为相位噪声源的数量可能急剧增加。本文提出一种基于期望最大化（EM）算法的迭代接收机方法。我们考虑具有振荡器与天线通用关联模式的大规模MIMO框架，并纳入信道状态信息不完善及莱斯块衰落等其他信道干扰。在每次接收机迭代过程中，基于已知发送符号信息，采用具有优化自适应步长和阈值停止准则的最速下降法估计相位噪声样本。多种测试场景下的结果表明，所提相位检测算法能有效改善误码率和均方误差性能，甚至可达到与无相位噪声情况下相同的性能水平，且优于现有先进替代方案。进一步分析揭示了系统最终性能与资源消耗之间的有用折衷关系。