本論文提出了一種用於低地球軌道(LEO)衛星通訊系統的載波頻率偏移(CFO)估計算法，從而使正交分頻多重進接(OFDMA)系統可以獲得接近於理想零都普勒偏移的性能。

第三代合作夥伴計劃(3GPP)正在探索發展第五代新空中介面(5G NR)以支持非地面網絡(NTN)，尤其是衛星通信網絡。近年來，近地軌道（LEO）衛星受到越來越多的關注。在LEO衛星通信系統中，信號解調受到時變頻偏的影響相當顯著，這是由於衛星以約 7.6 km/s的高速度移動，且隨著頻譜變得更加擁擠，正在設計更高頻率的鏈路，例如Kurz-above(Ka)波段，約28GHz。這些頻率會經歷較大的衰減，導致數百 kHz 的頻率偏移，因此系統必須能夠在低信噪比下運行。

然而，LEO系統的高動態環境與Ka波段頻率相結合，導致都普勒偏移非常大，進而破壞子載波之間的正交性造成載波間干擾(ICI)，從而限制了頻率估計器的基本分辨率，並顯著降低系統性能。挑戰就變成了估計範圍需要提升且達到高精準度。因此論文中採用的頻率估計策略由粗略的預補償和精細估計階段組成。

頻率偏移的預補償是基於衛星星曆數據與波束中心位置計算所需的頻率調整值，可以粗略地補償它們之間的相對運動引起的都普勒頻偏，並降低NTN操作對全球導航衛星系統 (GNSS)的依賴。而本論文所提出的改善自適應擴展卡爾曼濾波器(IAEKF)之差分都普勒補償技術針對影響濾波器的參數提供了相應的自適應算法，使其有更大的估計範圍，能夠供Ka-band的衛星通訊達到頻率同步。最後，我們也額外提出基於循環前綴(CP)的精細LSE頻率估計，能夠幫助訊號修復近乎於理想零都普勒的情況。

在本論文中，提出了幾個結果來比較方法的性能，並且評估終端在不同位置觀察到的都普勒以及不同訊號雜訊比(SNR)和都普勒頻移的位元錯誤率(BER)，通過仿真驗證了所提出算法的有效性與估計器性能良好，估計範圍大，精度高，並也適用於較低的頻段，而且增加用戶在波束中的分佈範圍,解決了地球用戶終端(UT)經過LEO衛星通道遇到的龐大都普勒頻移問題，從而提高OFDMA系統性能。

This thesis proposes an estimation algorithm for compensation of carrier frequency offset (CFO) for Low-earth orbit (LEO) satellite communication systems for the orthogonal frequency division multiple access (OFDMA) system.

The 3rd Generation Partnership Project (3GPP) is exploring 5G New Radio (5G NR) support for non-terrestrial networks (NTN), especially satellite communication networks. Low-Earth Orbit (LEO) satellites have been studied extensively in recent years. In the LEO satellite communication system, the demodulated signal is severely damaged by the time-varying Doppler effect, which is caused by the satellite moving at a high speed about 7.6 km/s. And as the spectrum becomes more crowded, higher frequency links are being designed, such as the Kurz-above (Ka) band, around 28GHz. These frequency bands experience severe attenuation, and cause the frequency offset to be hundreds of kilohertz.

However, LEO systems have very severe Doppler shift, which destroy the orthogonality between sub-carriers and cause inter-carrier interference (ICI). This limits the resolution of the frequency estimator and significantly reduces system performance. The challenge then becomes that the estimated range needs to increase and with high accuracy. The frequency estimation methods proposed in this thesis include pre-compensation, differential estimation and fine estimation.

The pre-compensation of the frequency offset is to calculate the frequency offset value based on the satellite ephemeris data and the center position, which can initially alleviate the severe Doppler shift, and reduce NTN's need for Global Navigation Satellite System (GNSS). The Improved Adaptive Extended Kalman Filter (IAEKF) proposed in this thesis does differential Doppler compensation, and it adds an adaptive algorithm to calculate the parameters which affect the filter, so it has a larger estimation range and can be used for Ka-band satellite communication to achieve frequency synchronization. Finally, the least squares estimator (LSE) based on cyclic prefix (CP) for fine frequency estimation, which can help the signal repair close to the ideal zero Doppler shift performance.

The results are presented at the end of this thesis to compare the performance of the method and evaluate the Doppler shift which caused by multi-user at different locations, and use the proposed method in a satellite environment to analyze its feasibility. Simulation results show that the proposed algorithm is effective and the estimator has good performance, such as large estimation range and high accuracy, and is also suitable for lower frequency band. And also increase the area of UTs distribution in beamforming footprint. It solves the huge Doppler shift problem caused by LEO satellite communication, thereby improves the performance of OFDMA system.

Chinese Abstract i
English Abstract iii
Contents v
1 INTRODUCTION 1
1.1 Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Research Motivation and Objective . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.5 Contribution and Achievement . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.6 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 BACKGROUNDS 6
2.1 Non-Terrestrial Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Classification and Characteristics of Satellite Communication . . . . . . . . . 9
2.3 Sun synchronous orbit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.4 Doppler Shift in Satellite Communication . . . . . . . . . . . . . . . . . . . . 12
2.4.1 The Effect of Different Orbital Heights and Velocities . . . . . . . . . 13
2.4.2 The Effect of Position Along Y-axis . . . . . . . . . . . . . . . . . . . 14
2.4.3 The Effect of Position Along X-axis . . . . . . . . . . . . . . . . . . . 16
2.4.4 The Effect of Footprint Size . . . . . . . . . . . . . . . . . . . . . . . 17
2.5 Extend Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3 Doppler Shift Compensation Method for LEO Satellite Communication 21
3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.1.1 Signal Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.1.2 Inter-Carrier Interference Coefficient . . . . . . . . . . . . . . . . . . 24
3.1.3 Satellite Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2 Problem Setup and Proposed Method . . . . . . . . . . . . . . . . . . . . . . 27
3.2.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2.2 Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3 Pre-compensation for LEO Systems . . . . . . . . . . . . . . . . . . . . . . . 31
3.4 Differential Compensation via Improve Adaptive Extended Kalman Filter for
LEO Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.5 Fine Compensation via Least Squared Estimator for LEO Systems . . . . . . 40
3.6 Differential and Fine Estimation Algorithm . . . . . . . . . . . . . . . . . . . 42
4 NUMERICAL AND SIMULATION RESULTS 44
4.1 Simulation Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.2 Analyzing Differential Doppler Estimators . . . . . . . . . . . . . . . . . . . 45
4.3 Compare Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.4 Analyzing Satellite Communication for Multi-User Scenarios . . . . . . . . . 58
5 CONCLUSIONS 65
Bibliography 66

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