Title :
Efficient algorithms for sequence detection in non-Gaussian noise with intersymbol interference
Author :
Chen, Yue ; Blum, Rick S.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Lehigh Univ., Bethlehem, PA, USA
fDate :
8/1/2000 12:00:00 AM
Abstract :
Sequence detection is studied for communication channels with intersymbol interference and non-Gaussian noise using a novel adaptive receiver structure. The receiver adapts itself to the noise environment using an algorithm which employs a Gaussian mixture distribution model and the expectation maximization algorithm. Two alternate procedures are studied for sequence detection. These are a procedure based on the Viterbi algorithm and a symbol-by-symbol detection procedure. The Viterbi algorithm minimizes the probability the sequence is in error and the symbol-by-symbol detector minimizes symbol error rate, which are different
Keywords :
Adaptive signal detection; Digital communication; Error statistics; Gaussian processes; Intersymbol interference; Iterative methods; Noise; Receivers; Sequences; Telecommunication channels; Viterbi detection; Gaussian mixture distribution model; Viterbi algorithm; adaptive receiver structure; communication channels; expectation maximization algorithm; intersymbol interference; noise environment; nonGaussian noise; sequence detection; symbol error rate; symbol-by-symbol detection procedure; Additive noise; Convolutional codes; Digital communication; Gaussian noise; Intersymbol interference; Matched filters; Signal processing; Signal processing algorithms; Viterbi algorithm; Working environment noise;
Journal_Title :
Communications, IEEE Transactions on