Pulse or digital communications – Receivers – Particular pulse demodulator or detector
Patent
1995-08-15
1999-02-02
Pham, Chi H.
Pulse or digital communications
Receivers
Particular pulse demodulator or detector
371 437, 375346, H03D 100
Patent
active
058675388
ABSTRACT:
The invention provides simple and reliable detection of .pi./4 shifted DQPSK modulated digital signals in a single-subscriber-unit, a multiple-subscriber unit (MSU) or a base transceiver station (BTS) of a fixed-wireless system, and is also directly applicable to other digital cellular or personal communication systems which utilizes a binary or M-ary PAM, FSK or PSK digital modulation scheme with differential or coherent encoding and time- and/or frequency-multiplexing. It offers great simplicity while providing soft-decision information for the later stage decoding of information bits encoded with an error correcting code. For each received sample z.sub.k+L and its estimated one z.sub.k+L, a Euclidean distance function is calculated. This Euclidean distance u(z.sub.k+L .vertline.v.sub.k+L, . . . , v.sub.k) is then added to the function derived from the previous iteration g(v.sub.k+L-1, . . . , v.sub.k), to yield a new Euclidean distance function f(v.sub.k+L, . . . , v.sub.k). Then a series of comparisons are carried out to find the minimum Euclidean distance with respect to each symbol within the channel memory span except v.sub.k. These minimum Euclidean distances are then added up to yield M values. The symbol corresponding to the minimum distance is the detected symbol. The same M Euclidean distance values are also used for soft decision derivation for use with an error detecting code. A simple measure of the accuracy of each symbol is calculated from the two shortest Euclidean distances. In particular, by taking the ratio of the difference to the sum of those two distances, the overall implementation of the demodulator becomes especially computationally efficient.
REFERENCES:
Erfanian, J.; "Reduced Complexity Symbol Detectors with Parallel Structures for ISI Channels"; IEEE Transactions on Communications, vol. 42, No. 2/3/4, Feb/Mar/Apr. 1994; pp. 1661-1671.
Hagenauer, J. et al.; "A Viterbe Algorithm with Soft-Decision Outputs and its Applications"; German Aerospace Research Establishment (DLR) Institute for Communications Technology, West Germany, IEEE, 1989, pp. 1680-1686.
Haykins, S.; "Adaptive Filter Theory", Chapter 1 Introduction, Prentice-Hall, 1986, pp. 4-7.
Koch, W. et al.; "Optimum and Sub-Optimum Detection of Coded Data Disturbed By time-Varying Intersymbol Interference", Germany, 1990 IEEE, pp. 1679-1684.
Proakis, J.; "Adaptive Equalization for TDMA Digital Mobile Radio", IEEE Transactions on Vehicular Technology, 40, No. 2, May 1991, pp. 333-341.
Proakis, J.; "Digital Communications", 2d. Edition, McGraw-Hill, Inc. 1989, pp. 602-605, 610-616, 624-627.
Robertson, P., et al.; "A Comparison of Optimal and Sub-Optimal MAP Decoding Algorithms Operating in the Log Domain"; Institute for Communications Technology, German Aerospace Research Establishment (DLR), Germany; IEEE International Conference on Communications, Seattle, Jun. 1995; pp. 1009-1013.
Hughes Electronics Corporation
Pham Chi H.
Sales Michael W.
Webster Bryan
Whelan John T.
LandOfFree
Computational simplified detection of digitally modulated radio does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Computational simplified detection of digitally modulated radio , we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Computational simplified detection of digitally modulated radio will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-1124552