Channel Feedback Based on AoD-Adaptive Subspace Codebook in FDD Massive MIMO Systems

Wenqian Shen, Linglong Dai, Byonghyo Shim, Zhaocheng Wang, Robert W. Heath

Channel feedback is essential in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. Unfortunately, previous work on multiuser MIMO has shown that the codebook size for channel feedback should scale exponentially with the number of base station (BS) antennas, which is greatly increased in massive MIMO systems. To reduce the codebook size and feedback overhead, we propose an angle-of-departure (AoD)-adaptive subspace codebook for channel feedback in FDD massive MIMO systems. Our key insight is to leverage the observation that path AoDs vary more slowly than the path gains. Within the angle coherence time, by utilizing the constant AoD information, the proposed AoD-adaptive subspace codebook is able to quantize the channel vector in a more accurate way. We also provide performance analysis of the proposed codebook in the large-dimensional regime, where we prove that to limit the capacity degradation within an acceptable level, the required number of feedback bits only scales linearly with the number of resolvable (path) AoDs, which is much smaller than the number of BS antennas. Moreover, we compare quantized channel feedback using the proposed AoD-adaptive subspace codebook with analog channel feedback. Extensive simulations that verify the analytical results are provided.

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