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A novel blind maximum likelihood sequence detector (MLSD) for GSM and TDMA based systems is proposed. The baseband data at the receiver are partitioned into clusters that are identified using a new class of unsupervised clustering algorithms known as K-Harmonic Means (KHMp). The KHMp algorithms arc insensitive to the initialization of the cluster centers owing to a built-in boosting function, and thus provide reliable estimates of the cluster centers. The identified cluster representatives are then mapped to the corresponding combinations of input symbols using a discrete hidden Markov model formulation of the channel states and the mapping is used to compute the branch metrics in a cluster-based MLSD to perform signal detection. The proposed detector avoids any explicit channel modeling and training overhead and its performance is evaluated for the GSM systems.
Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on (Volume:1 )
Date of Conference: 4-7 Aug. 2002