Wireless communication systems such as global system for mobile (GSM) communications are playing a growing role for data transmission. In order to ensure reliable transmission, the channel impulse response has to be estimated accurately. This is a difficult task particularly for fast fading channels caused by high-speed mobile units. We deal with the application of nonblind and blind channel estimation approaches to identify the full rate data Traffic CHannel (TCHF9.6) of GSM. We present a new iterative channel estimation scheme leading to a significant performance improvement especially for high-speed propagation with Doppler frequencies up to 500 Hz. Furthermore, it is shown that blind channel estimation schemes could be as efficient as nonblind methods when regarding bit error rates (BERs) after channel decoding in terms of the E~/sub b//N/sub 0/ ratio. Moreover, a solution for the scalar ambiguity inherent in all blind estimation approaches is suggested.

Channel estimation plays a leading role in wireless communication systems such as GSM (Global System for Mobile communications). Putting the main emphasis on investigating the application of non-blind and blind channel estimation approaches to the identification of a full rate data Traffic CHannel (TCH/F9.6), we present a new idea of an iterative channel estimation based upon the capabilities of channel coding. We show that this method leads to a significantly improved performance especially for high speed propagations with Doppler frequencies up to 500 Hz. Giving the bit error rates (BERs) before and after channel decoding in terms of the E~/sub b//N/sub 0/ ratio, we show, furthermore, that blind channel estimation schemes could be as efficient as non-blind methods.

We compare the effect of blind and nonblind channel estimates on the performance of Global System for Mobile communications (GSM) receivers. More precisely, we investigate whether two blind approaches, based on higher order statistics (HOS), can compete with two conventional methods, exploiting training sequences. For blind and nonblind estimates of six fast and slowly fading mobile radio channels, we give simulated bit error rates (BERs), after Viterbi detection, in terms of the signal-to-noise ratio (SNR). We also study the influence of cochannel interferers at different values of the signal-to-interference ratio (SIR). Averaged over the six channel examples, we demonstrate that the blind channel estimation algorithm eigenvector approach to blind identification (EVI) leads to an SNR loss of 1.2-1.3 dB only, while it saves the 22% overhead in GSM data rate caused by the transmission of training sequences. Since just 142 samples are used for blind channel estimation, we consider this performance outstanding for an approach based on HOS.