Dynamic Oversampling in 1-Bit Quantized Asynchronous Large-Scale Multiple-Antenna Systems for Sustainable Iot Networks

In this paper, we propose a dynamic oversampling technique for asynchronous large-scale multiple-antenna systems with 1-bit analog-to-digital converters at the base station that is suitable for sustainable internet of things and cellular networks. To the best of our knowledge, this is the first paper to introduce a dynamic oversampling technique for such systems. The main idea is to sample the received signal at a higher rate and only few weighted samples are chosen for further signal processing. We apply the generalized eigenvalue decomposition algorithm for linearly combining the samples and performing dimension reduction. We investigate the proposed technique in terms of the Bussgang theorem based sum rate capacity. Numerical results show that with the proposed dynamic oversampling technique the system can use small number of processing samples to achieve the same sum rates as the standard uniform oversampling technique while maintaining the same power consumption.