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- W2805637342 abstract "In this paper, sparse channel estimation in OFDM communication systems is investigated. Particularly, the application of compressive sensing theory into sparse channel estimation is studied. Several existing sparse signal recovery algorithms are compared along with the conventional least-square method. Furthermore, overcomplete dictionaries are considered for sparse representations of the multipath channels. Simulation results show that the oversampled DFT matrices lead to sparser channel coefficients and superior estimation quality when compared to the baseband channel representations, and AS-SaMP provides a better estimation accuracy without requiring excessively higher complexity among the compared recovery algorithms." @default.
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- W2805637342 date "2018-01-01" @default.
- W2805637342 modified "2023-09-27" @default.
- W2805637342 title "Sparse Channel Estimation Based on Compressive Sensing with Overcomplete Dictionaries in OFDM Communication Systems" @default.
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- W2805637342 doi "https://doi.org/10.1007/978-981-10-8660-1_7" @default.
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