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Article Dans Une Revue IEEE Transactions on Vehicular Technology Année : 2018

On the Performance of Sliding Window TD-LMMSE Channel Estimation for 5G Waveforms in High Mobility Scenario

Résumé

The upcoming 5G era is considered as a critical answer to future railway communication needs. In this work, we analyze the performance of sliding window time domain LMMSE channel estimation technique where a generalized development is proposed and analyzed for 5G FBMC-(O)QAM waveform candidates. In order to enhance performance, the analytical model is extended to exploit multipaths and multiantennas correlation wherever they do exist e.g., tunnels. TD-LMMSE performance for 5G waveforms and achieved enhancements are verified by Monte Carlo simulations.
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Dates et versions

hal-01871302 , version 1 (10-09-2018)

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Citer

Michel Saideh, Marion Berbineau, Iyad Dayoub. On the Performance of Sliding Window TD-LMMSE Channel Estimation for 5G Waveforms in High Mobility Scenario. IEEE Transactions on Vehicular Technology, 2018, 67 (9), pp.8974-8977. ⟨10.1109/TVT.2018.2845551⟩. ⟨hal-01871302⟩
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