High-resolution compressive channel estimation for broadband wireless communication systems

Abstract

Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Accurate channel estimation can be done by sampling received signal with analog-to-digital converter (ADC) at Nyquist rate and then estimating all channel taps with high resolution. However, these Nyquist sampling-based methods have two main disadvantages: (i) demand of the high-speed ADC, which already exceeds the capability of current ADC, and (ii) low spectral efficiency. To solve these challenges, compressive channel estimation methods have been proposed. Unfortunately, those channel estimators are vulnerable to low resolution in low-speed ADC sampling systems. In this paper, we propose a high-resolution compressive channel estimation method, which is based on sampling by using multiple low-speed ADCs. Unlike the traditional methods on compressive channel estimation, our proposed method can approximately achieve the performance of lower bound. At the same time, the proposed method can reduce communication cost and improve spectral efficiency. Numerical simulations confirm our proposed method by using low-speed ADC sampling.