Band-Limited Signal Compression Enabled Computationally Efficient Software-Defined Radio for Two-Way Satellite Time and Frequency Transfer

CHENG Long; DONG Shaowu; WU Wenjun; GONG Jianjun; WANG Weixiong; GAO Zhe

doi:10.11999/JEIT250705

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CHENG Long, DONG Shaowu, WU Wenjun, GONG Jianjun, WANG Weixiong, GAO Zhe. Band-Limited Signal Compression Enabled Computationally Efficient Software-Defined Radio for Two-Way Satellite Time and Frequency Transfer[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250705

Citation:

CHENG Long, DONG Shaowu, WU Wenjun, GONG Jianjun, WANG Weixiong, GAO Zhe. Band-Limited Signal Compression Enabled Computationally Efficient Software-Defined Radio for Two-Way Satellite Time and Frequency Transfer[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250705

Citation:

CHENG Long, DONG Shaowu, WU Wenjun, GONG Jianjun, WANG Weixiong, GAO Zhe. Band-Limited Signal Compression Enabled Computationally Efficient Software-Defined Radio for Two-Way Satellite Time and Frequency Transfer[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250705

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Band-Limited Signal Compression Enabled Computationally Efficient Software-Defined Radio for Two-Way Satellite Time and Frequency Transfer

doi: 10.11999/JEIT250705 cstr: 32379.14.JEIT250705

CHENG Long^{1, 2},
DONG Shaowu^{1, 3, 4
,
,},
WU Wenjun^{1, 3, 4},
GONG Jianjun^{1, 3},
WANG Weixiong^{1, 3},
GAO Zhe^{1, 3}

1.
National Time Service Center, Chinese Academy of Sciences, Xi’an 710600, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Key Laboratory of Time Reference and Applications, Chinese Academy of Sciences, Xi’an 710600, China
4.
School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China

Accepted Date: 2025-12-06
Rev Recd Date: 2025-12-06

Available Online: 2025-12-15

Abstract

Abstract

Objective This study addresses the critical challenges in Two-Way Satellite Time and Frequency Transfer (TWSTFT) systems, particularly focusing on the computational inefficiency and excessive resource consumption of Software-Defined Radio (SDR) receivers. Despite TWSTFT's reputation for exceptional long-term stability and precision in time transfer, traditional hardware-based implementations suffer from significant diurnal effects. Current mitigation strategies, such as data fusion with GPS Precise Point Positioning (PPP), are limited by their reliance on auxiliary link performance and lack of standardized algorithms across international networks. While SDR receivers have proven effective in reducing diurnal effects and improving accuracy, their high sampling rates and complex multi-correlator algorithms impose prohibitive computational demands, hindering real-time multi-station operations. To overcome these limitations, this research introduces an innovative band-limited signal compression method specifically designed for TWSTFT signals. The primary objective is to develop a solution that maintains high measurement resolution while dramatically enhancing computational efficiency, thereby enabling scalable and high-performance time transfer across global timing laboratories. This work holds significant potential to advance TWSTFT technology by addressing current bottlenecks and facilitating more robust international time and frequency transfer. Methods The proposed band-limited signal compression method adapts traditional signal compression techniques to TWSTFT by addressing the distortion of pseudo-random noise (PRN) code square-wave characteristics under bandwidth constraints. The method employs the following key technical approach: First, bandwidth-matched filtering is applied to the local PRN code replica to precisely align its spectral characteristics with the effective bandwidth of the received signal, thereby effectively suppressing out-of-band noise interference. For received signals with different bandwidths, the system employs n groups (e.g., n=1, 2, or 20) of phase-diversified, equally-spaced PRN code subsequences. The number of subsequence groups n is strictly determined by the constraint n×R_chip≥ 2×Band_signal, where R_chip denotes the sampling rate of the subsequences and Band_signal represents the signal bandwidth. During signal processing, the received signal - after being bandpass-filtered to suppress out-of-band noise - undergoes parallel correlation operations with these phase-diversified PRN code subsequences. The complete correlation function is reconstructed through a linear combination of the n independent correlation results, where each result is scaled by the normalization factor N_chip/n, with N_chip defined as the number of samples per PRN chip. This integrated approach, combined with dynamic optimization through adaptive sampling rate adjustment and efficient resource allocation algorithms, achieves optimal performance while maintaining computational efficiency. Results and Discussions The experimental validation was conducted on an advanced TWSTFT platform at the National Time Service Center (NTSC), utilizing data from TWSTFT links (NTSC-NIM, NTSC-SU, NTSC-PTB) and SATRE local-loop tests. Measurement data from MJD 60742 to MJD 60749 were collected following ITU-R TF.1153.4 standards. Results demonstrate significant improvements in both precision and computational efficiency. In local-loop tests, the method achieved the most stable Time of Arrival (TOA) measurements while maintaining high signal-to-noise ratio (Table 2), with time deviation (TDEV) outperforming traditional multi-correlator and conventional compression methods across all averaging periods (Fig. 9). For TWSTFT links, the proposed method demonstrated superior short-term stability in comparisons across different baseline lengths (Fig. 10 and Fig. 11). Configurations with PRN subsequence numbers n=1 and n=2 showed remarkable efficiency improvements, increasing processing speed by 795% and 707% respectively while reducing GPU memory usage by 89.77% and 84.65% (Table 4). The method supports up to 102 concurrent channels (n=1), significantly exceeding the 11-channel capacity of conventional techniques (Table 5). Analysis confirms the optimal balance between performance and efficiency, as increasing the number of PRN subsequences (n) provides no additional precision benefits but increases resource consumption. These advancements are attributed to the parallel processing of short correlations and bandwidth-aware sampling while maintaining measurement accuracy. Conclusions This study presents an innovative band-limited signal compression method designed to overcome the computational limitations of traditional TWSTFT systems. The proposed approach integrates parallel short-correlation processing with adaptive bandwidth-aware sampling, achieving significant improvements in both precision and efficiency. Experimental validation confirms the method's superior performance, demonstrating enhanced short-term stability across various signal bandwidths and baseline lengths compared to conventional multi-correlator techniques. Notably, the solution achieves remarkable computational efficiency, with processing speeds increased by 795% (n=1) and 707% (n=2) while reducing GPU memory requirements by 89.77% and 84.65% respectively. The system’s scalability is substantially improved, supporting up to 102 concurrent channels - a nine-fold increase over traditional implementations. These advancements validate the method's optimized balance between performance and resource utilization. Future research directions include adaptation to more complex operational scenarios to further enhance the technology's applicability in global time and frequency transfer networks.
- two-way satellite time and frequency transfer (TWSTFT),
- software-defined radio (SDR),
- signal compression,
- multi-correlator,
- pseudo-random noise (PRN) code

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References(21)

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