Time-domain Fading Channel Prediction Based on Spin-wave Reservoir Computing
Jiaxuan Chen, Haotian Chen, Ryosho Nakane, Gouhei Tanaka, Akira Hirose · 2023
This paper proposes a physical-device-based time-domain fading channel prediction scheme using spin-wave reservoir computing. We numerically construct a spin-wave reservoir chip that adopts new spin-wave transducers named Film-penetrating transducers (FPTs). We arrange three FPTs as exciters and forty-nine FPTs as detectors connected to the reservoir input and readout, respectively. We feed communication channel information collected in an actual fading environment to evaluate the prediction performance. We calculate the average root mean squared errors (RMSEs) and obtain the symbol error rates (SERs) for various forecasting time lengths. We find that our proposed scheme can achieve accurate channel prediction without any frequency-domain conversion. We obtain robust communication performance up to a forecasting time length of 8 ms. These results suggest a high capability of spin-wave reservoir computing in the application of channel prediction and its promising potential in other possible time-sequential computational tasks.