Fast Algorithms in Slow and High Doppler Mobile Environments

Abstract

High Doppler effects resulting from fast time varying dispersive channels give rise to the so-called intercarrier interference, whose accurate modeling for data recovery is paramount. We present a novel turbo estimation scheme based on a known linearized model of the time varying channel via its derivatives. The derivatives estimation is adaptive, in the sense that at each turbo estimation it incorporates information on previously estimated parameters. This is combined with a decision-directed scheme implemented at bit level with soft decision. We show that any pilot based scheme that is able to induce a Toeplitz structure in the channel correlation matrix, can make use of an existing class of so-called superfast algorithms for minimum mean-square error (MMSE) channel estimation. Given a structure for the vector of pilots and an upper bound for the channel delay spread, say N, we show that it is only necessary to store 2N coefficients per pilot structure in order to recover the entire channel parameters. We bring attention to the fact that either for static or slowly varying channels, any Toeplitz-like model can yield a superfast equalization method as well, and show how fast order recursive algorithms can be combined to a superfast receiver structure, in order to yield both efficient equalizer computation and equalization.