Downlink precoding is considered for multi-path multi-user multi-input single-output (MU-MISO) 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.

翻译：多路多用户多输出单输出(MU-MISO)频道考虑下行编码前,基础台站在这些频道使用正方位频率分多路和低分辨率信号。提出了量化协调最小化(QCM)算法,其性能与其他预编码算法进行了比较,包括平面无线调低(SQUID)、多亚麻油贪婪迭代迭代四分制(MAGIQ)和安全比值最高。MAGIQ和QCM达到最高的信息率,QCM在乘数中测量的复杂度最低。信息率是试点辅助频道估算和进行联合数据和频道估测的盲人探测器计算的。5G低密度对等检查代码的位误差率证实了信息测算。在发报器上不完善频道知识的模拟显示,QCM和SQUID的性能与高分辨率二次量化器的零分解前的性能相似。