A novel two-stage channel estimation method for wireless communications

Abstract

In this paper, we proposed a novel two-stage channel estimation (2S-CE) method. In contrast to conventional channel estimation methods, this method makes the maximum use of the information contributed by the known data in every transmission burst. In the first stage, the least-squares (LS) algorithm was used to estimate the channel impulse response (CIR) based on the normal training sequence. Then the maximum channel memory was estimated and used to locate the uncorrupted data in the guard interval. In the second stage, the uncorrupted data together with the normal training sequence were sent to the LS algorithm again to obtain the fine-tuned CIR. To verify the efficiency of the proposed 2S-CE method, both a theoretical analysis and computer simulations have been done. Computer simulation results confirm the analysis results and demonstrate that the proposed 2S-CE method outperforms a conventional single-stage channel estimation method.