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Deep Learning for Hybrid Beamforming with Finite Feedback in GSM Aided mmWave MIMO Systems
Zhilin Lu, Xudong Zhang, Rui Zeng +1
Hybrid beamforming is widely recognized as an important technique for millimeter wave (mmWave) multiple input multiple output (MIMO) systems. Generalized spatial modulation (GSM) i…
Towards Efficient Subarray Hybrid Beamforming: Attention Network-based Practical Feedback in FDD Massive MU-MIMO Systems
Zhilin Lu, Xudong Zhang, Rui Zeng +1
Channel state information (CSI) feedback is necessary for the frequency division duplexing (FDD) multiple input multiple output (MIMO) systems due to the channel non-reciprocity. W…
Quantization Adaptor for Bit-Level Deep Learning-Based Massive MIMO CSI Feedback
Xudong Zhang, Zhilin Lu, Rui Zeng +1
In massive multiple-input multiple-output (MIMO) systems, the user equipment (UE) needs to feed the channel state information (CSI) back to the base station (BS) for the following…
Better Lightweight Network for Free: Codeword Mimic Learning for Massive MIMO CSI feedback
Zhilin Lu, Xudong Zhang, Rui Zeng +1
The channel state information (CSI) needs to be fed back from the user equipment (UE) to the base station (BS) in frequency division duplexing (FDD) multiple-input multiple-output…