Frequency Offset Estimation For 5G Based On Doppler And Kalman Filter In Satellite Communications System
The signal demodulation is significantly affected by the time-varying frequency offset in low earth orbit (LEO) satellite communication system. We present a method for Doppler shift and Doppler rate estimation based on 5G frame structure in satellite communication system. The integer and fractional part of the Doppler shift is estimated within a prime synchronizing signal (PSS) in two steps. Large estimation range and low complexity can be achieved in this method. Besides, a Doppler rate estimation algorithm is proposed. Precise Doppler rate is calculated by extracting the accumulated phase difference of two consecutive PSS. Furthermore, Kalman filter is utilized to improve the stability of the frequency offset estimators in low signal-to-noise ratio (SNR). Simulation results show that the estimators can perform well with large estimation range and high accuracy.
Orthogonal frequency division multiplexing (OFDM) has been widely adopted by mobile communication system, such as long term evolution (LTE) and worldwide interoperability for microwave access (WiMAX), for its high spectrum efficiency and its robustness against multipath fading. It also attracts extensive attention worldwide as a promising candidate technology for satellite mobile communication systems. Low earth orbit (LEO) satellite communication system can provide large coverage and is not susceptible to physical attacks and natural disasters. Besides, it has low propagation delay relative to the geostationary earth orbit (GEO) and medium earth orbit (MEO) communication system. So LEO satellite communication system is considered as a promising complement to the terrestrial 5G networks. However, due to the high-speed relative motion between the satellite and receiver, there is rapid time-varying Doppler effect, which seriously degrades the performance of OFDM system. The Doppler shift and Doppler rate estimation technology are important for LEO satellite communication system.?
- carrier frequency offset (CFO) measurement Technique.
- However, as the future 5G telecommunication system is unlikely to adopt the OFDM?s strict orthogonality between subcarriers or subchannels, its CFO may be measured in frequency domain.
- A low-density parity-check (LDPC) code and 256 quadrature amplitude modulation (QAM), which are NR technologies, are applied to meet the high-reliability and high data-rate requirements of 5G. In addition, we propose a data detection scheme based on a soft decision to improve reliability.
- It can perform perfect or practical synchronization and channel estimation. To reduce the total simulation time, it can be execute the SNR points in the SNR loop in parallel by using the Parallel Computing.
- The proposed scheme has high reliability and a high data rate. To provide various interoperable innovative platform services in 5G communications systems.
The Doppler shift estimation has been widely studied in OFDM based terrestrial communication system. It is usually divided into two steps to estimate the integer part and the fractional part of the Doppler shift. The two-step estimation method takes advantages of low complexity and a large range of Doppler shift estimation. The proposed algorithm improves the estimation accuracy of Doppler rate effectively. Moreover, Kalman filter is utilized on the Doppler shift and Doppler rate estimator to stabilize the estimations of Doppler shift and Doppler rate in low SNR. It is proved that the mean square error (MSE) performance of both estimators with Kalman filter are significantly improved.
MATLAB 2018 and above
Rapid time-varying frequency offset is an essential problem for the application of OFDM in LEO satellite communication system. Considering the 5G frame structure, this paper presents a scenario of carrier synchronization for OFDM based LEO satellite communication system. The Doppler shift is estimated in a two-step scheme within one PSS corresponding to the 5G frame structure, which takes advantages of wide estimation range and low complexity. Besides, we propose a Doppler rate estimation algorithm based on two consecutive PSS. Doppler rate estimation with high accuracy is achieved by accumulating the phase difference in a large time scale. Furthermore, the Kalman filter is utilized to improve the performance of both estimators. It is demonstrated that the Kalman filter allows the estimators to work in low SNR.?
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