Efficient OFDM Channel Estimation via an Information Criterion

In this paper, we consider joint estimation of the channel length and of the impulse response for OFDM systems, exploiting information criteria to find the best trade-off, in terms of Kullback-Leibler divergence, between noise rejection and channel description accuracy. So far, information criteria have not been used for practical channel length estimation methods, due to their prohibitive complexity. We show how to make them affordable, performing channel estimation in a recursive way that allows to establish the optimal channel length with a moderate incremental cost. With reference to IEEE 802.11 OFDM-based standards for WLAN, we investigate several cases, applying the joint channel length and impulse response estimation to many scenarios, ranging from the simplest pilot-aided channel estimation based on training sequences, to the most challenging data-aided channel tracking, driven either by detected or by decoded symbols. In all cases, the achieved performance and robustness are very good, with a very small increase in complexity w.r.t. estimation methods that assume fixed channel length.