Energy Efficiency Maximization Precoding for Quantized Massive MIMO Systems

The use of low-resolution digital-to-analog and analog-to-digital converters (DACs ADCs) significantly benefits energy efficiency (EE) at the cost high quantization noise for massive multiple-input multiple-output (MIMO) systems. This paper considers a precoding optimization problem maximizing EE in quantized downlink MIMO To this end, we jointly optimize an active antenna set, vectors, allocated power; yet acquiring such joint optimal solution is challenging. resolve challenge, decompose into direction power problems. For direction, characterize first-order optimality condition, which entails effects distortion selection. We cast derived condition as functional eigenvalue problem, wherein finding principal eigenvector attains best local point. propose generalized iteration based algorithm. given adopt gradient descent algorithm maximization. Alternating these two methods, our identifies power. In simulations, proposed methods provide considerable performance gains. Our results suggest that few-bit DACs are sufficient achieving