Optimization based Millimeter Wave Channel Estimation with Low-resolution Analog-to-digital Converters

Millimeter wave large-scale Multiple Input Multiple Output (MIMO) system has more radio frequency links that bringing more power consumption, which could be efficiently tackled by using low-resolution Analog-to-Digital Converters (ADCs) in receiver. Considering the influence of the received signal amplitude distortion caused by low-resolution ADCs on the performance of channel estimation, a two-stage millimeter wave channel estimation algorithm is proposed after optimization. In the first stage, we construct the optimization problem which inequality constraints originating from the received signal determined by the quantized received signal and estimate the direction of arrival by using l1-norm to measure the sparsity. In the second stage, according to the estimated direction, Bussgang decomposition has been used to approximate the nonlinear quantization process, and the least square estimation of the complex channel gain is obtained. Simulation results show that the performance of the proposed algorithm is improved by about 5 dB compared with the current state-of-the-art algorithm, and the complexity is reduced to be linear. It can be seen that the proposed algorithm is greatly improved in terms of effectiveness and reliability, and has certain practical value.