Coarse Quantization-Aware Block Diagonalization Algorithms for Multiple-Antenna Systems with Low-Resolution Signals

It is known that the estimated energy consumption of digital-to analog converters (DACs) is around 30% of the energy consumed by analog-to-digital converters (ADCs) keeping fixed the sampling rate and bit resolution. Assuming that similarly to ADC, DAC dissipation doubles with every extra bit of resolution, a decrease in two resolution bits, for instance from 4 to 2 bits, represents a 75% lower dissipation. The current limitations in sum-rates of 1-bit quantization have motivated researchers to consider extra bits in resolution to obtain higher levels of sum-rates. Following this, we devise coarse quantizationaware precoding using few bits for the broadcast channel of multiple-antenna systems based on the Bussgang theorem. In particular, we consider block diagonalization algorithms, which have not been considered in the literature so far. The sumrates achieved by the proposed Coarse Quantization-Aware Block Diagonalization (CQA-BD) and its regularized version (CQA-RBD) are superior to those previously reported in the literature. Simulations illustrate the performance of the proposed CQA-BD and CGA-RBD algorithms against existing approaches.