Compressive Sensing CSI Acquisition and Feedback in FDD Massive MIMO Systems

This chapter presents an adaptive channel estimation (CE) and feedback scheme for FDD based massive MIMO systems. This scheme can adaptively adjust the training overhead and pilot design, aiming at accurately estimating and feeding back the downlink CSI with significantly reduced overhead. In particular, a compressive sensing based adaptive CSI acquisition scheme is introduced by exploiting the spatially common sparsity of massive MIMO channels, where the time slot overhead is adaptively controlled relying on the sparsity level of the channels. Furthermore, a distributed sparsity adaptive matching pursuit (DSAMP) algorithm is developed to jointly estimate the channels of multiple subcarriers. Then, a closed-loop channel tracking scheme based on the temporal channel correlation is provided to adaptively design the non-orthogonal pilot and enhance the CE. Besides, this chapter also provides the performance analysis of the considered scheme as theoretical support and guidance. Finally, simulation results indicate that the considered scheme outperforms its counterparts and can approach the performance bound, highlighting its effectiveness.