Nedelcu Andrei Stefan, Steiner Fabian, Kramer Gerhard
Optical and Quantum Laboratory, Huawei Munich Research Center, 80992 Munich, Germany.
Institute for Communications Engineering, Technical University of Munich (TUM), 80333 Munich, Germany.
Entropy (Basel). 2022 Apr 4;24(4):504. doi: 10.3390/e24040504.
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.
针对多径多输入单输出信道考虑下行链路预编码，其中基站采用正交频分复用和低分辨率信令。提出了一种量化坐标最小化（QCM）算法，并将其性能与其他预编码算法进行比较，包括无穷范数平方松弛（SQUID）、多天线贪婪迭代量化（MAGIQ）和最大安全裕度预编码。MAGIQ和QCM实现了最高的信息速率，并且以乘法次数衡量，QCM具有最低的复杂度。针对导频辅助信道估计和执行联合数据与信道估计的盲检测器计算信息速率。5G低密度奇偶校验码的误码率证实了信息论计算结果。在发射机处信道知识不完美的情况下进行的仿真表明，QCM和SQUID的性能与具有高分辨率量化器的迫零预编码以类似方式下降。
