Uplink-aided downlink channel estimation in FDD massive MIMO by variational Bayesian inference

In this paper, we discuss the downlink channel estimation in frequency division duplex (FDD) massive MIMO system. Based on the angular reciprocity between uplink and downlink, we combined the uplink support prior information into the downlink channel estimation. A downlink channel estimation method based on variational Bayesian inference(VBI) is proposed, which is by taking the support prior information into consideration. Meanwhile the VBI is discussed for complex number in our system model, and the structural sparsity is utilized in the Bayesian inference. The Bayesian Cramer-Rao bound for the channel estimation MSE is also given out. Compared with Bayesian compressed sensing and other algorithms, the proposed algorithm achieves much better performance in terms of channel estimation accuracy by simulations.