  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. Traditionally, accurate channel estimation is done by
sampling received signal by analog-to-digital converter (ADC) at Nyquist rate
(high-speed ADC sampling) and then estimate all channel taps with
high-resolution. However, traditional linear estimation methods have two mainly
disadvantages: 1) demand of the high-speed ADC sampling rate which already
exceeds the capability of current ADC and also the high-speed ADC is very
expensive for regular wireless communications; 2) neglect the inherent channel
sparsity and the low spectral efficiency wireless communication is unavoidable.
To solve these challenges, in this paper, we propose a high-resolution
compressive channel estimation method by using low-speed ADC sampling. Our
proposed method can achieve close performance comparing with traditional sparse
channel estimation methods. At the same time, the proposed method has following
advantages: 1) reduce communication cost by utilizing cheap low-speed ADC; 2)
improve spectral efficiency by extracting potential training signal resource.
Numerical simulations confirm our proposed method using low-speed ADC sampling.
