Joint Port Selection Based Channel Acquisition for FDD Cell-Free Massive MIMO
CoRR(2023)
摘要
In frequency division duplexing (FDD) cell-free massive MIMO, the acquisition
of the channel state information (CSI) is very challenging because of the large
overhead required for the training and feedback of the downlink channels of
multiple cooperating base stations (BSs). In this paper, for systems with
partial uplink-downlink channel reciprocity, and a general spatial domain
channel model with variations in the average port power and correlation among
port coefficients, we propose a joint-port-selection-based CSI acquisition and
feedback scheme for the downlink transmission with zero-forcing precoding. The
scheme uses an eigenvalue-decomposition-based transformation to reduce the
feedback overhead by exploring the port correlation. We derive the sum-rate of
the system for any port selection. Based on the sum-rate result, we propose a
low-complexity greedy-search-based joint port selection (GS-JPS) algorithm.
Moreover, to adapt to fast time-varying scenarios, a supervised deep
learning-enhanced joint port selection (DL-JPS) algorithm is proposed.
Simulations verify the effectiveness of our proposed schemes and their
advantage over existing port-selection channel acquisition schemes.
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关键词
Cell-free massive MIMO,channel acquisition,joint port selection,channel correlation,deep learning
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