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Clustering-based blind maximum likelihood sequence detection for GSM and TDMA systems

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2 Author(s)
Boppana, D. ; Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA ; Rao, S.S.

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.

Published in:

Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on  (Volume:1 )

Date of Conference:

4-7 Aug. 2002

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