1. OTFS Channel Estimation based on OGCE-BEM
- Author
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LI Xinyi, XIE Zhibin, ZHANG Jinbo, and MAO Yunlong
- Subjects
OTFS ,OGCE-BEM ,forgetting factor ,channel estimation ,Applied optics. Photonics ,TA1501-1820 - Abstract
【Objective】With the development of the sixth generation mobile communication technology, the inter-carrier interference in the traditional Orthogonal Frequency Division Multiplexing (OFDM) system makes the channel estimation performance insufficient to provide highly reliable communication, and Orthogonal Time-Frequency Space (OTFS) system can effectively solve the problem of communication system reliability degradation caused by fast time variability and Doppler effect, which has received wide attention in recent years.【Methods】In order to effectively meet the channel estimation performance requirements of OTFS systems, this paper uses an Optimized Generalized Complex Exponential (OGCE) Basis Expansion Model (BEM) to calculate the channel impulse response as a time-invariant basis function with basis function coefficients, which can effectively fit fast time-varying channels in high-speed mobile communication scenarios. The OGCE-BEM improves the spectral leakage by more intensive sampling and reduces the error of the high-frequency basis model by adding correction coefficients to reduce the error of the HF-based model.【Results】The simulation results show that the proposed algorithm is suitable for high-speed mobile communication scenarios with more reasonable design of the basis function. The estimation method has lower mean square error than the fixed forgetting factor, and the channel estimation results are more accurate. Compared with Least Square (LS), BEM-LS and BEM-Linear Minimum Mean Square Error (LMMSE) channel estimation methods, the performance of mean square error is significantly improved.【Conclusion】It can be seen that the channel estimation algorithm based on OGCE-BEM can effectively reduce the number of unknown parameters to be estimated and improve the accuracy of channel estimation.
- Published
- 2024
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