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

Received Date: 2025-07-28
Accepted Date: 2025-12-06
Rev Recd Date: 2025-12-06

Available Online: 2025-12-15

Abstract

Abstract

Objective This study addresses key challenges in Two-Way Satellite Time and Frequency Transfer (TWSTFT) systems, with emphasis on the computational inefficiency and high resource consumption of Software-Defined Radio (SDR) receivers. Although TWSTFT provides excellent long-term stability and time-transfer precision, conventional hardware implementations exhibit significant diurnal effects. Existing mitigation approaches, such as fusion with GPS Precise Point Positioning, depend on auxiliary link quality and lack unified algorithms across international networks. SDR receivers reduce diurnal effects and improve accuracy; however, high sampling rates and multi-correlator processing impose excessive computational burdens that limit real-time multi-station operation. The objective is to develop a band-limited signal compression approach that preserves measurement resolution while substantially improving computational efficiency, thereby enabling scalable and high-performance time transfer across international timing laboratories. Methods A band-limited signal compression method tailored to TWSTFT is proposed by accounting for the distortion of Pseudo-Random Noise (PRN) code square-wave characteristics under bandwidth constraints. Bandwidth-matched filtering is first applied to the local PRN code replica to align its spectrum with the effective bandwidth of the received signal and suppress out-of-band noise. For received signals with different bandwidths, n groups (e.g., n = 1, 2, or 20) of phase-diversified, equally spaced PRN code subsequences are generated. The number of subsequence groups n satisfies n × R_chip≥ 2 × Band_signal, where R_chip denotes the sampling rate of the subsequences and Band_signal represents the signal bandwidth. After bandpass filtering, the received signal undergoes parallel correlation with the phase-diversified PRN subsequences. The full correlation function is reconstructed by a linear combination of the n independent correlation outputs, each scaled by N_chip/n, where N_chip is the number of samples per PRN chip. Adaptive sampling-rate adjustment and resource-allocation strategies are applied to achieve efficient processing with preserved accuracy. Results and Discussions Experimental validation is performed on a TWSTFT platform at the National Time Service Center using TWSTFT links (NTSC–NIM, NTSC–SU, NTSC–PTB) and SATRE local-loop tests. Data from MJD 60 742 to MJD 60 749 are collected in accordance with ITU-R TF.1153.4. In local-loop tests, the proposed method provides the most stable Time of Arrival measurements while maintaining a high signal-to-noise ratio (Table 2). Time deviation outperforms traditional multi-correlator and conventional compression methods over all averaging times (Fig. 9). For operational links, superior short-term stability is observed across different baseline lengths (Fig. 10 and Fig. 11). With n = 1 and n = 2, processing speed increases by 795% and 707%, respectively, while GPU memory usage decreases by 89.77% and 84.65% (Table 4). The method supports up to 102 concurrent channels (n = 1), exceeding the 11-channel capacity of conventional approaches (Table 5). Increasing n beyond these values yields no further precision improvement but increases resource consumption, confirming an optimal trade-off between accuracy and efficiency. Conclusions A band-limited signal compression method is presented to address the computational constraints of TWSTFT SDR receivers. Parallel short-correlation processing combined with bandwidth-aware sampling achieves substantial gains in precision and efficiency. Experimental results confirm improved short-term stability across signal bandwidths and baseline lengths relative to conventional multi-correlator methods. The approach delivers large efficiency gains, with processing speed increases of 795% (n = 1) and 707% (n = 2) and GPU memory reductions of 89.77% and 84.65%, respectively. System scalability is markedly enhanced, supporting up to 102 concurrent channels. These results demonstrate an effective balance between performance and resource utilization for TWSTFT applications.
- 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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