Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM

Entropy

卷:24

Gerhard Kramer¹  Fabian Steiner¹  Andrei Stefan Nedelcu² 

[1] Institute for Communications Engineering, Technical University of Munich (TUM), 80333 Munich, Germany;

[2] Optical and Quantum Laboratory, Huawei Munich Research Center, 80992 Munich, Germany;

关键词: massive MIMO;    precoding;    coarse quantization;    coordinate descent;    information rates;   

DOI  :  10.3390/e24040504

来源: DOAJ

【 摘 要 】

Downlink precoding is considered for multi-path multi-input single-output channels where the base station uses orthogonal frequency-division multiplexing and low-resolution signaling. A quantized coordinate minimization (QCM) algorithm is proposed and its performance is compared to other precoding algorithms including squared infinity-norm relaxation (SQUID), multi-antenna greedy iterative quantization (MAGIQ), and maximum safety margin precoding. MAGIQ and QCM achieve the highest information rates and QCM has the lowest complexity measured in the number of multiplications. The information rates are computed for pilot-aided channel estimation and a blind detector that performs joint data and channel estimation. Bit error rates for a 5G low-density parity-check code confirm the information-theoretic calculations. Simulations with imperfect channel knowledge at the transmitter show that the performance of QCM and SQUID degrades in a similar fashion as zero-forcing precoding with high resolution quantizers.

【 授权许可】

Unknown