Abstract
This paper presents a novel channel estimation technique for space-time coded (STC) systems. It is based on applying the maximum likelihood (ML) principle not only over a known pilot sequence but also over the unknown symbols in a data frame. The resulting channel estimator gathers both the deterministic information corresponding to the pilot sequence and the statistical information, in terms of a posteriori probabilities, about the unknown symbols. The method is suitable for Turbo equalization schemes where those probabilities are computed with more and more precision at each iteration. Since the ML channel estimation problem does not have a closed-form solution, we employ the expectation-maximization (EM) algorithm in order to iteratively compute the ML estimate. The proposed channel estimator is first derived for a general time-dispersive MIMO channel and then is particularized to a realistic scenario consisting of a transmission system based on the global system mobile (GSM) standard performing in a subway tunnel. In this latter case, the channel is nondispersive but there exists controlled ISI introduced by the Gaussian minimum shift keying (GMSK) modulation format used in GSM. We demonstrate, using experimentally measured channels, that the training sequence length can be reduced from 26 bits as in the GSM standard to only 5 bits, thus achieving a 14% improvement in system throughput.
Highlights
The so-called Turbo codes [1, 2, 3] have revealed themselves as a very powerful coding technique able to approach the Shannon limit in AWGN channels
We present a novel channel estimation technique that gathers both the deterministic information corresponding to the pilot sequence and the statistical information, in terms of a posteriori probabilities, about the unknown symbols
We focus on the application of the maximum likelihood (ML)-EM channel estimator described in Section 4 to an space-time coded (STC) global system mobile (GSM)-like system for underground railway transportation systems
Summary
The so-called Turbo codes [1, 2, 3] have revealed themselves as a very powerful coding technique able to approach the Shannon limit in AWGN channels. The same decoding principle has been successfully applied, under the term Turbo equalization [5], to effectively compensate the ISI induced by the channel and/or the EURASIP Journal on Applied Signal Processing modulation scheme This technique exploits the fact that ISI can be viewed as a form of rate-1, nonrecursive coding. Due to the conservative nature of its market, it is expected that railway radio-communication systems will employ GSM-R for the long-term future For this reason, when subway operators wish to deploy advanced, high data rate, digital services for security or entertainment purposes, it is very likely that they will prefer to increase the capacity of the existing GSM-R system rather than switch to another radio standard.
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