Pulse or digital communications – Equalizers – Automatic
Patent
1997-11-25
1999-12-14
Chin, Wellington
Pulse or digital communications
Equalizers
Automatic
370292, 36972416, 3697242, H03H 0730
Patent
active
060027169
DESCRIPTION:
BRIEF SUMMARY
BACKGROUND OF THE INVENTION
The invention relates to a digital transmission system comprising a receiver, the receiver including a receiver input stage and a digital memory for storing a sequence of binary symbols of sample values 1 formed in the receiver input stage 1 of a signal distorted by a transmission channel, and an equalizer for forming a sequence of binary estimates from the sample values by means of an impulse response of a substitute system describing the transmission channel, this impulse response being determined by first correlations of coefficients of a known training sequence with the sample values of a part of the known training sequence extended by at least one binary symbol.
Furthermore, the invention relates to a receiver including a receiver input stage 1 and including a digital memory for storing a sequence of binary symbols of sample values 1 formed in the receiver input stage 1 of a signal distorted by a transmission channel, and an equalier for forming a sequence of binary estimates from the sample values by means of an impulse response of a substitute system describing the transmission channel, this impulse response being determined by first correlations of coefficients of a known training sequence with the sample values of a part of the known training sequence extended by at least one binary symbol.
DESCRIPTION OF THE RELATED ART
Such receivers are used, for example, in digital mobile radio according to the GSM standard. According to the GSM standard, digital signals are transmitted in a TDMA method by a GMSK modulation. The data transmission is then influenced by a time-variant transmission channel. More particularly, multipath propagation and reflections determine differences of delay and phase shifts for the transmitted digital data symbols in the received signal and lead to a superpositioning of adjacent data symbols. The fact that a received signal for a data symbol is influenced by d previous data symbols is known as intersymbol interference (ISI). Then d is an integer defining the memory depth of the transmission channel.
For the equalization of the received signal which is linearly distorted as a result of multipath propagation and transmitting-end and receiving-end band limitation filters (intrinsic impulse noise with linear demodulation of the GMSK signal), the receiver is to be adapted, for data reconstruction, to the respective time-variant transmission properties of the transmission channel. Therefore, an estimation is made of the respective impulse response of the currently distorting transmission system, this system comprising not only the transmission channel, but also the influences of the GMSK modulation, and a receiver input stage which produces sample values of the received digital signal. For this purpose, a substitute system describing the transmission system is formed, with the aid of which, impulse response data are estimated according to the Maximum Likelihood Sequence Estimation (MLSE) method via the execution of a Viterbi algorithm, more particularly, a soft-output Viterbi algorithm, or a single symbol estimation method.
With this method, the most probable transmit sequence is determined from all possible data sequences, while taking into account the received sequence and the estimated impulse response of the transmission system. More particularly, the Viterbi algorithm is suitable for estimating the data symbols according to the MLSE method. The Viterbi algorithm is known from "The Viterbi algorithm", G. D. Porney Jr., IEEE Proceedings, Vol. 61, pages 268-278, 1973. A more accurate estimation of the data symbols is provided by the soft-output Viterbi algorithm, which is known, for example, from "A Viterbi algorithm with soft-decision outputs and its applications", J. Hagenauer and P. Hoher, Proceedings of the GLOBECOM 1989, pages 47.1.1-47.1.7, Dallas 1989. Use is also made of maximum a posteriori symbol-by-symbol decoder algorithms according to "Optimal decoding of linear codes for minimizing symbol error rate", L. R. Bahl, J. Cocke, F. Jelinek,
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Fischer Robert
Gerstacker Wolfgang
Huber Johannes
Meyer Raimund
Schramm Peter
Chin Wellington
Halajian Dicran
Tran Conguan
U.S. Philips Corporation
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