Tracking FDD Massive MIMO Downlink Channels by Exploiting Delay and Angular Reciprocity

Abstract

The massive multiple-input multiple-output (MIMO) technology considerably enhances the spectral efficiency of a wireless communication system. However, it suffers from substantial performance degradation caused by the movement of users and the difficulty in acquiring downlink channel state information when combined with frequency division duplexing (FDD). This paper addresses these two fundamental problems by proposing a downlink channel tracking scheme that traces the multiuser downlink time-varying channel of an FDD massive MIMO system. By leveraging the delay and angular reciprocity between the uplink and downlink, a low-complexity module initially traces the frequency-independent parameters in each user's channel in the uplink. With the tracing results in previous instances, the module can efficiently trace the parameters of the existing paths, find paths that disappeared, and detect new paths from sparse uplink sounding reference signals. Then, in the downlink, a low-overhead module estimates the downlink gains for each user from a limited amount of cell-common sparse pilots. The K-means clustering algorithm is utilized to design these pilots and restrict them within a predefined amount. Accurate downlink channel tracking results can be obtained by using the frequently updated frequency-independent parameters and downlink gains, thereby compensating the performance degradation caused by movement. The numerical results validate the effectiveness and robustness of the proposed tracking scheme and suggest that we should frequently apply this scheme to ensure a high multiuser sum spectral efficiency performance.