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Optimized Precoding for MU-MIMO With Fronthaul Quantization
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DOI：10.1109/TWC.2023.3247802.png)
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Abstract
En 中文
One of the first widespread uses of multi-user multiple-input multiple-output (MU-MIMO) is in 5G networks, where each base station has an advanced antenna system (AAS) that is connected to the baseband unit (BBU) with a capacity-constrained fronthaul. In the AAS configuration, multiple passive antenna elements and radio units are integrated into a single box. This paper considers precoded downlink transmission over a single-cell MU-MIMO system. We study optimized linear precoding for AAS with a limited-capacity fronthaul, which requires the precoding matrix to be quantized. We propose a new precoding design that is aware of the fronthaul quantization and minimizes the mean-squared error at the receiver side. We compute the precoding matrix using a sphere decoding (SD) approach. We also propose a heuristic low-complexity approach to quantized precoding. This heuristic is computationally efficient enough for massive MIMO systems. The numerical results show that our proposed precoding significantly outperforms quantization-unaware precoding and other previous approaches in terms of the sum rate. The performance loss for our heuristic method compared to quantization-aware precoding is insignificant considering the complexity reduction, which makes the heuristic method feasible for real-time applications. We consider both perfect and imperfect channel state information (CSI).
Keywords:
Precoding
Symbols
Quantization (signal)
Downlink
Antennas
Complexity theory
Uplink
Quantization-aware precoding
advanced antenna system (AAS)
limited fronthaul capacity
reduced complexity
MU-MIMO
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W
Organization
Cited Papers
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