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Analysis of the Impact of Doppler Shift on Data Transmission Quality in LEO Satellite IoT
The rapid development of low Earth orbit (LEO) satellite Internet of Things (IoT) has made it an important support for global IoT coverage. The quality and stability of data transmission directly determine the practical application value of the system. Caused by the high-speed motion of LEO satellites, Doppler shift exerts significant negative impacts on various data transmission scenarios such as file transfer and real-time data monitoring. Its mechanism involves carrier synchronization, signal interference, timing deviation and other aspects, ultimately resulting in increased bit error rate (BER) and decreased transmission rate. This paper deeply analyzes the influence mechanism of Doppler shift in different data transmission scenarios and quantifies its specific effects on BER and transmission rate.
I. Influence Mechanism in File Transfer Scenarios
File transfer has high requirements for data integrity. Doppler shift degrades communication quality by destroying signal synchronization, introducing interference, and worsening link budget. The core mechanisms mainly include four aspects.
(1) Carrier Synchronization Failure
Doppler shift causes the center frequency of the received signal to deviate from the expected value, invalidating traditional carrier synchronization algorithms. When the frequency offset exceeds the acquisition range of the carrier tracking loop, carrier loss of lock occurs, severely impairing demodulation performance. In S-band LEO satellite communication at an altitude of 600 km, a 24 ppm Doppler offset without effective compensation will prevent the demodulator from correctly recovering raw data, directly leading to data loss in file transfer.
(2) Inter-Carrier Interference (ICI)
For systems employing OFDM modulation, Doppler shift introduces not only carrier frequency offset (CFO) but also inter-subcarrier frequency offset (ISFO). Taking a 5G-NTN system at 600 km orbital altitude and 20 GHz communication frequency as an example, the maximum Doppler offset at the carrier center reaches 480 kHz. For a PUSCH channel occupying 256 resource blocks with a subcarrier spacing of 120 kHz, the cumulative frequency offset difference between the highest and lowest subcarriers due to ISFO can reach 8.8 kHz. Such linearly varying offset along subcarrier indices destroys orthogonality, induces severe ICI, sharply increases BER, and greatly reduces file transfer integrity.
(3) Symbol Timing Deviation
The Doppler effect compresses or stretches the signal in the time domain, changing the symbol rate to times the nominal rate, equivalent to introducing sampling frequency offset (SFO). If the receiver uses the same sampling frequency as the transmitter, OFDM symbols will gradually drift from the time reference. Once the deviation exceeds the cyclic prefix (CP), inter-symbol interference (ISI) occurs, further degrading reception performance and increasing error probability in file transfer.
(4) Degraded Link Budget
The demodulation performance degradation caused by Doppler shift directly reduces link margin. Under low signal-to-noise ratio conditions, even a small frequency offset significantly raises the demodulation threshold, requiring higher transmit power to maintain communication quality. Measured data show that when Doppler shift reaches 10 kHz, the demodulation performance of BPSK decreases by about 3–5 dB; when the shift exceeds 20 kHz, QPSK modulation can hardly operate normally. The increase in transmit power contradicts the low-power design requirement of IoT terminals.
II. Influence Mechanism in Real-Time Data Monitoring Scenarios
Real-time data monitoring demands extremely low latency and continuous transmission stability, such as industrial sensor networks and environmental monitoring, which require millisecond-level end-to-end latency and stable data streams. The fast time-varying nature of Doppler shift makes its impact more complex and severe, mainly reflected in four dimensions.
(1) Increased Delay Jitter
End-to-end latency for real-time monitoring must be controlled at the millisecond level. Rapid changes in Doppler shift substantially increase system processing burden, including computation latency of frequency offset estimation and compensation, as well as retransmission latency caused by frequency offset. When the Doppler shift rate reaches 0.27 ppm/s, the system must frequently update compensation parameters, easily making delay jitter exceed the acceptable range and undermining monitoring effectiveness.
(2) Damaged Continuous Transmission Stability
Real-time monitoring relies on continuous data streams. The Doppler shift of LEO satellite broadcast signals can reach up to 200 kHz with obvious time-varying characteristics. Without effective compensation, received signal quality deteriorates sharply, causing burst or continuous errors and data breaks, severely reducing reliability and even disabling the monitoring system from judging the actual state.
(3) Increased Difficulty of Adaptive Modulation and Coding
Adaptive Modulation and Coding (AMC) is key to optimizing spectral efficiency in modern satellite communications by dynamically adjusting modulation order and coding rate based on real-time channel quality estimation. However, fast-varying Doppler shift makes accurate channel estimation difficult. The AMC algorithm fails to track channel variations timely: an overly low order causes spectral efficiency loss, while an overly high order leads to a BER surge, making it hard to balance efficiency and reliability.
(4) Elevated Power Control Complexity
Most real-time monitoring devices are battery-powered with strict power constraints. The link quality degradation caused by Doppler shift requires higher transmit power, which drastically shortens battery life. This conflict between communication quality and power consumption is prominent in LEO satellite systems, demanding sophisticated intelligent power control algorithms and increasing system design difficulty.
III. Quantitative Impact on Bit Error Rate and Transmission Rate
The influence of Doppler shift on data transmission quality is ultimately quantified as increased BER and reduced throughput, closely related to orbital distance, modulation scheme, spreading factor and other parameters, with obvious differences across scenarios.
(1) Quantitative Changes in Bit Error Rate Performance
The impact of Doppler shift on BER exhibits clear dependence on distance and modulation. Based on performance analysis of LoRa-to-LEO systems:
- In short-range scenarios (0–200 km), BER for all spreading factors (SF7–SF12) remains low at to , with limited Doppler influence;
- As distance increases, BER rises sharply: at 1000 km, SF7 reaches and SF12 ;
- At 2000 km, SF7 degrades to , while SF12 stays below , showing a 2–3× performance gap, reflecting stronger processing gain and anti-interference ability of high spreading factors.
For OFDM systems, the mechanism is more complex. In S-band LEO communication, 24 ppm Doppler shift degrades QPSK BER from to or lower. In Ka-band, higher carrier frequency leads to larger absolute shift and more severe BER degradation.
(2) Quantitative Changes in Transmission Rate
Doppler shift reduces transmission rate mainly through three paths: decreased spectral efficiency, triggered retransmissions, and AMC performance loss, with noticeable rate reduction across frequency bands and systems.
- Spectral efficiency degradation: ICI and ISI directly lower spectral efficiency. In a 5G-NTN system at 600 km and 20 GHz, effective spectral efficiency drops by about 15–20% due to ISFO among 256 subcarriers.
- Retransmission inefficiency: Increased BER triggers ARQ, raising latency and bandwidth consumption. In high-dynamic Doppler environments, retransmitted blocks may experience different offsets, reducing ARQ efficiency by 30–50%.
- AMC performance loss: At a Doppler rate of 0.27 ppm/s, average spectral efficiency decreases by about 25% compared with the ideal case, directly limiting actual throughput.
Specifically, in LoRa systems at 500 km, throughput falls from 7–8 kbps (SF7) to below 2 kbps (SF12), related to both spreading factor and Doppler-induced demodulation degradation. In high-rate Ka-band systems, Doppler shift can reduce actual throughput by 30–40% relative to the theoretical rate.
