Research on antenna design based on low-resolution digital-to-analog converters

Abstract

In the ever-evolving field of communication, the optimization of antenna design and structure has garnered significant attention from professionals. Effective antenna design plays a crucial role in ensuring reliable and efficient communication systems. However, the challenge lies in overcoming the limitations imposed by current low-resolution digital-to-analog converters (DACs) on the attainment of highly efficient antenna structures. This study aims to address this issue by exploring the potential of low-resolution DACs for improving the structural design of antennas. To achieve this, we propose gradient-based and low-complexity heuristic solutions that leverage global optimization techniques. By optimizing the antenna structure using these innovative approaches, we aim to enhance the overall performance and efficiency of communication systems. The significance of this research lies in its potential to revolutionize antenna design by overcoming the constraints of low-resolution DACs. By incorporating Sigma-Delta modulation in the filter design, we anticipate significant improvements in performance when the number of transmitting antennas is comparable to the number of users. Furthermore, our investigation reveals that the application of Compressed Sensing techniques yields results that closely align with the optimal solution in scenarios where the number of transmitting antennas greatly exceeds the number of users.