Joint Estimation for Channel and I/Q Imbalance in Massive MIMO via Two-Timescale Optimization

In this paper, joint estimation for channel and Inphase/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.