Delay-Doppler Frequency Domain-Aided Superimposing Pilot OTFS Channel Estimation Based on Deep Learning
Delay-Doppler Frequency Domain-Aided Superimposing Pilot OTFS Channel Estimation Based on Deep Learning
- New search for: Yang, Chaoyi
- New search for: Wang, Junlong
- New search for: Pan, Zhenni
- New search for: Shimamoto, Shigeru
- New search for: Yang, Chaoyi
- New search for: Wang, Junlong
- New search for: Pan, Zhenni
- New search for: Shimamoto, Shigeru
In this work, a channel estimation method for OTFS using superimposing pilot is proposed. The pilot is superimposing on the first transmitter data symbol, yielding an enhanced frequency domain of Delay-Doppler domain pattern at the receiver end. A deep convolution neural network is proposed to de-noise the interfered channel matrix. Simulation results show that the bit error rate performance of the proposed method is better than that of the existing methods at low pilot energy.
Document information
Delay-Doppler Frequency Domain-Aided Superimposing Pilot OTFS Channel Estimation Based on Deep Learning
2022-09-01
3493095 byte
Conference paper
Electronic Resource
English