Joint Estimation for Channel and I/Q Imbalance in Massive MIMO Via Two-timescale Optimization
IEEE Global Communications Conference(2019)
摘要
In this paper, joint estimation for channel and In-phase/Quadrature imbalance (IQI) is investigated in the downlink Frequency Division Duplexing (FDD) massive multiple-input-multiple-output (MIMO) systems. First, exploiting the sparsity of massive MIMO channels and the timescale separation of channels and IQI, we derive a two-timescale sparse maximum a posterior (MAP) formulation for the joint estimation, where the IQI parameter is the long-term variable and the sparse channel is the short-term variable. Then we propose a two-timescale online joint sparse estimation (TOJSE) algorithm to solve the problem, which can converge to the stationary solutions of the original two-timescale non-convex stochastic optimization problem over time. Finally, simulations show that our proposed TOJSE algorithm can achieve significant gain over various baselines.
更多查看译文
关键词
massive MIMO,Channel estimation,I/Q imbalance,two-timescale stochastic optimization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络