In this work, we present block diagonalization and power allocation algorithms for large-scale multiple-antenna systems with coarsely quantized signals. In particular, we develop Coarse Quantization-Aware Block Diagonalization${\scriptstyle \mathrm {\left ({CQA-BD}\right)}}$and Coarse Quantization-Aware Regularized Block Diagonalization${\scriptstyle \mathrm {\left ({CQA-RBD}\right)}}$precoding algorithms that employ the Bussgang decomposition and can mitigate the effects of low-resolution signals and interference. Moreover, we also devise the Coarse Quantization-Aware Most Advantageous Allocation Strategy${\scriptstyle \mathrm {\left ({CQA-MAAS}\right)}}$power allocation algorithm to improve the sum rate of precoders that operate with low-resolution signals. An analysis of the sum-rate performance is carried out along with computational complexity and power consumption studies of the proposed and existing techniques. Simulation results illustrate the performance of the proposed${\scriptstyle \mathrm {CQA-BD}}$and${\scriptstyle \mathrm {CQA-RBD}}$precoding algorithms, and the proposed${\scriptstyle \mathrm {CQA-MAAS}}$power allocation strategy against existing approaches.