Blind Estimation of Linear and Nonlinear Sparse Channels

• Autorzy: Georgoulakis K.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a Clustering Based Blind Channel Estimator for a special case of sparse channels - the zero pad channels. The proposed algorithm uses an unsupervised clustering technique for the estimation of data clusters. Clusters labelling is performed by a Hidden Markov Model of the observation sequence appropriately modified to exploit channel sparsity. The algorithm achieves a substantial complexity reduction compared to the fully evaluated technique. The proposed algorithm is used in conjunction with a Parallel Trellis Viterbi Algorithm for data detection and simulation results show that the overall scheme exhibits the reduced complexity benefits without performance reduction.

Słowa kluczowe

EN

blind estimation and equalization; clustering techniques; sparse zero pad channels

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2013
• Tom: nr 1
• Strony: 65--71
• Opis fizyczny: Bibliogr. 21 poz., rys., tab.

Twórcy

autor

Georgoulakis K.

• Department of Science and Technology of Telecommunications University of Peloponnese, Tripolis, 22100 Greece,

Bibliografia

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