General frequency point scanning method and system for convergence network of satellite and mobile communication

Abstract

The invention relates to the technical field of communication, and discloses a universal frequency point scanning method and system for a satellite and mobile communication convergence network, and the method comprises the steps: receiving a time domain signal which comprises a candidate frequency point and determines a signal frequency range; determining a time domain sampling rate and a fast Fourier transform length according to a system bandwidth and a time slot structure, and dividing sub-bands and adjusting parameters when the time domain sampling rate and the fast Fourier transform length exceed hardware limitation; performing fast Fourier transform after downsampling to obtain a frequency domain power spectrum, and performing time dimension averaging and sub-band splicing processing; selecting a corresponding frequency domain power value based on a preset frequency point list, calculating a detection metric in combination with time-frequency domain mapping characteristics of different systems, and obtaining at least one of coarse frequency offset or coarse time offset based on the detection metric; and after the metric values are ranked, selecting candidate frequency points to be combined with at least one of coarse frequency offset or coarse time offset for subsequent cell search. The method is compatible with a multi-system system, breaks through hardware limitation, achieves wide frequency domain coverage, and synchronously obtains key offset parameters to improve frequency point identification precision and access efficiency.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and specifically to a general frequency scanning method and system for converged satellite and mobile communication networks. Background Technology

[0002] With the continued growth of global communication demand, building a seamless communication network covering all regions has become a core development direction for the industry. While traditional terrestrial mobile communication networks (such as 4G and 5G) offer advantages like high bandwidth and low latency, they suffer from coverage blind spots in areas such as oceans, deserts, and remote mountainous regions, making it difficult to meet the demand for ubiquitous connectivity. Satellite communication systems, with their wide-area coverage capabilities, have become a key support for filling the gaps in terrestrial networks and achieving integrated air-space-ground communication. The convergence of these two technologies has become an important trend in the evolution of communication technology.

[0003] In converged satellite and terrestrial mobile communication networks, multi-mode terminals need to achieve seamless roaming and service continuity across heterogeneous networks, making frequency scanning during the initial access or network handover phase a crucial step. Current mainstream frequency scanning schemes primarily rely on power scanning, calculating signal power through time-domain filtering or fast Fourier transform frequency domain methods, and selecting high-power frequencies for synchronous access to shorten access time.

[0004] However, existing solutions have significant limitations: First, they lack versatility, being designed for specific network standards and difficult to integrate with different types of satellite and terrestrial communication systems, such as narrowband / broadband and single-carrier / multi-carrier systems. Second, their identification accuracy is limited; simple power scanning is insufficient to accurately distinguish the power contribution of target signals from interference signals in scenarios with high resource utilization. Third, their implementation cost is high; integrating multiple dedicated scanning modules to adapt to multi-standard networks significantly increases the design complexity and hardware cost of multi-mode receivers. Furthermore, existing solutions only provide power measurements for frequency point selection and cannot simultaneously acquire key parameters such as frequency offset and time offset, leading to complex and time-consuming subsequent cell search processes and hindering improvements in network access efficiency. Therefore, a universal, efficient, and low-cost frequency scanning solution is urgently needed to adapt to the diverse needs of converged networks. Summary of the Invention

[0005] To address the shortcomings of existing frequency scanning schemes, such as incompatibility with different systems (narrowband / wideband, single-carrier / multi-carrier) in converged satellite and terrestrial mobile communication networks, insufficient versatility, limited identification accuracy, high implementation costs, and inability to simultaneously acquire frequency and time offset parameters, leading to low network access efficiency, this invention provides a universal frequency scanning method and system for converged satellite and mobile communication networks. This method is compatible with narrowband and wideband systems, as well as single-carrier and multi-carrier systems, and can adapt to different candidate frequency ranges and frame structures, effectively reducing the design and implementation complexity of multi-mode receivers. It calculates different metric values ​​for different communication network standards, which is more effective than using power values ​​as a metric for frequency selection, further improving network access speed. Simultaneously with frequency selection, it can estimate coarse frequency offset and coarse time offset, or one of them, reducing the complexity of subsequent cell search.

[0006] In a first aspect, the present invention provides a general frequency scanning method for a converged satellite and mobile communication network, comprising: Receive time-domain signals containing candidate frequency points to determine the signal frequency range; Based on the bandwidth and time slot structure of the communication system, the time domain sampling rate and the fast Fourier transform length are determined. If the fast Fourier transform length exceeds the preset maximum limit, the frequency domain bandwidth range is divided into sub-bands, the fast Fourier transform length is set to the preset maximum value, and the time domain sampling rate is adjusted accordingly. The received signal is downsampled to the time-domain sampling rate, and a fast Fourier transform is performed according to the fast Fourier transform length to obtain the frequency-domain power spectrum. Determine the minimum statistical granularity in the time dimension, and within the range of the minimum statistical granularity in the time dimension, perform point-by-point averaging on the frequency domain power values ​​to obtain a set of averaged frequency domain power values. If there are sub-bands, perform transformation and averaging processes on each sub-band separately, and then stitch the processing results of all sub-bands together in the frequency dimension. After stitching, the signal range and the maximum supported frequency offset are determined by covering all candidate frequency points. Obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, select the frequency domain power value corresponding to the frequency point based on the center frequency of the candidate frequency point, the bandwidth of the determined signal, and the maximum frequency offset range. The detection metric of each candidate frequency point is calculated based on the physical channel time-frequency domain mapping characteristics of different communication systems. The detection metric is then used to calculate at least one of coarse frequency offset or coarse time offset. The detection metric values ​​of all candidate frequency points are sorted from largest to smallest. A preset number of candidate frequency points are selected as output and combined with at least one of coarse frequency offset or coarse time offset for subsequent cell search.

[0007] The universal frequency scanning method for converged satellite and mobile communication networks provided in this invention achieves frequency scanning of converged satellite and terrestrial mobile communication networks through a unified process, is compatible with multiple system standards, and solves the problem of insufficient universality of existing solutions. Subband division and splicing overcome the hardware FFT length limitation, achieving wide frequency domain coverage; time-dimensional averaging reduces noise interference and improves recognition accuracy. Simultaneously, detection metrics are calculated based on the time-frequency domain mapping characteristics of the physical channels of different communication systems, and candidate frequency points and key parameters are output simultaneously in a single scan, providing efficient input for subsequent cell search, significantly shortening network access time, and meeting the seamless roaming requirements of converged networks in multiple scenarios.

[0008] In one optional implementation, determining the time-domain sampling rate and the Fast Fourier Transform (FFT) length based on the bandwidth and time slot structure of the communication system, and if the FFT length exceeds a preset maximum limit, dividing the frequency domain bandwidth into sub-bands, configuring the FFT length to a preset maximum value, and adjusting the time-domain sampling rate, includes: Determine the frequency domain resolution: If the communication system is a multi-carrier communication system, the frequency domain resolution is set to the minimum subcarrier spacing of the downlink signal of the system; if the communication system is a single-carrier satellite communication system, the frequency domain resolution is determined by combining the system signal bandwidth and the requirements of subsequent cell search for residual frequency offset, and the frequency domain resolution is less than the absolute value of the maximum Doppler frequency shift of the system. Determine the initial time-domain sampling rate: based on the frequency domain bandwidth range that the communication system needs to cover. The minimum sampling rate that conforms to the Nyquist sampling theorem is selected as the time-domain sampling rate. ; Calculate the Fast Fourier Transform length: based on the time-domain sampling rate With frequency domain resolution The ratio is used to calculate the length of the Fast Fourier Transform; Subband division and parameter adjustment: If the calculated Fast Fourier Transform length exceeds the maximum Fast Fourier Transform length supported by the system. Then adjust the time-domain sampling rate. and according to the formula The number of subbands dividing the frequency domain bandwidth range, where, For the number of sub-bands, Indicates rounding up. This refers to the frequency bandwidth range that needs to be covered.

[0009] This invention determines the frequency domain resolution through classification, ensuring scanning accuracy and adaptability under different systems; it selects the sampling rate and calculates the FFT length based on the Nyquist sampling theorem to optimize resource consumption; and it achieves wide frequency domain coverage under hardware constraints through subband division formulas, making the solution both flexible and efficient, balancing scanning accuracy, computational complexity, and hardware cost. It provides a quantifiable and easily implementable parameter configuration system for frequency point scanning of multi-standard fusion networks, facilitating engineering implementation.

[0010] In one optional implementation, the number of power value points in the frequency dimension after selecting the frequency point corresponding to the frequency domain power value is: , This represents the maximum frequency offset; the number of points in the time dimension is... .

[0011] This invention provides point count calculation formulas for both frequency and time dimensions, and uses quantified parameters (such as signal bandwidth and maximum frequency deviation) to provide a pre-evaluation basis for scanning performance (frequency deviation coverage and time statistical accuracy). The formulas correlate signal bandwidth, maximum frequency deviation, frequency domain resolution, and time statistical granularity, ensuring complete power value coverage when selecting frequency points, avoiding signal omissions or measurement distortion, and guaranteeing the reliability of scanning results from a parameter perspective.

[0012] In one optional implementation, the step of calculating the detection metric for each candidate frequency point based on the physical channel time-frequency domain mapping characteristics of different communication systems, and using the detection metric to calculate at least one of coarse frequency offset or coarse time offset, includes: Using the number of frequency domain points corresponding to the bandwidth of the determined signal as the window length, the selected candidate frequency points are... The corresponding frequency domain power values ​​are averaged using a sliding window, and the maximum average value is selected as the initial detection metric. The initial coarse frequency offset is estimated based on the difference between the frequency corresponding to the maximum average value and the center frequency of the candidate frequency point, where when… When =1, the coarse frequency offset estimation step is omitted; If the determined signal is a periodic burst signal, then regarding the time dimension... The initial detection metric is used to calculate the peak-to-average power ratio (PAPR) using a sliding method. The maximum PAPR value is taken as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum PAPR value and the assumed position of the determined signal. Alternatively, the number of initial detection metric values ​​exceeding a preset threshold is selected as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum initial detection metric and the assumed position of the determined signal. When =1, the coarse time-partial estimation step is omitted.

[0013] This invention accurately identifies the power characteristics of the target frequency point and simultaneously acquires frequency offset information by using frequency-dimensional sliding window averaging and coarse frequency offset estimation. For periodic burst signals, it designs two methods: peak-to-average ratio calculation and threshold counting, which are adapted to different system signal patterns. While outputting detection metrics, it estimates coarse time offset, reduces the independent time offset estimation process in subsequent cell search, and improves access efficiency.

[0014] In one optional implementation, the preset threshold is a noise threshold, which is obtained by averaging the smallest preset quantity value among the initial detection metrics and multiplying it by a preset scaling factor.

[0015] The noise threshold calculation method provided in this invention is based on the minimum initial detection metric value and dynamically adapts to noise levels in complex channel environments, solving the false detection / missed detection problem of fixed thresholds. The configurability of preset values ​​and scaling factors allows the solution to be flexibly adjusted according to system noise characteristics and detection requirements, ensuring frequency point detection accuracy while optimizing adaptability to different communication systems and improving the robustness of the detection metric.

[0016] In one alternative implementation, the determining signal includes at least one of a synchronization signal, a frequency acquisition signal, or a pilot signal in different communication systems; the maximum frequency offset includes the crystal oscillator frequency offset of the communication system and the Doppler frequency offset of the satellite communication.

[0017] This invention ensures compatibility with multiple scenarios, including 4G / 5G terrestrial communication, 5G NTN satellite communication, and narrowband single-carrier satellite communication, by providing defined signal type coverage and adaptation modes for different systems. The definition of maximum frequency offset fully covers the sources of frequency offset in terrestrial and satellite communication in the fused network, making frequency point scanning accurate in handling satellite high-dynamic Doppler scenarios and terrestrial crystal oscillator deviation scenarios, and providing comprehensive technical support for frequency point identification for seamless full-domain coverage of the fused network.

[0018] Secondly, embodiments of the present invention provide a universal frequency scanning system for a converged satellite and mobile communication network, comprising: The signal acquisition module is used to receive a time-domain signal containing candidate frequency points to determine the signal frequency range; The parameter configuration module is used to determine the time domain sampling rate and the fast Fourier transform length according to the bandwidth and time slot structure of the communication system. If the fast Fourier transform length exceeds the preset maximum limit, the frequency domain bandwidth range is divided into sub-bands, the fast Fourier transform length is set to the preset maximum value, and the time domain sampling rate is adjusted accordingly. The frequency domain conversion module is used to downsample the received signal to the time domain sampling rate and perform a fast Fourier transform according to the fast Fourier transform length to obtain the frequency domain power spectrum. The power processing module is used to determine the minimum statistical granularity in the time dimension, and to perform point-by-point averaging on the frequency domain power values ​​within the range of the minimum statistical granularity in the time dimension to obtain a set of averaged frequency domain power values. The sub-band processing module is used to perform transformation and averaging processes on each sub-band if there are sub-bands, and to stitch the processing results of all sub-bands together in the frequency dimension. After stitching, it covers all candidate frequency points to determine the signal range and the maximum supported frequency offset. The frequency point filtering module is used to obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, the frequency domain power value corresponding to the frequency point is selected according to the center frequency of the candidate frequency point, the bandwidth of the determined signal and the maximum frequency deviation range. The metric calculation and filtering module is used to calculate the detection metric of each candidate frequency point based on the physical channel time-frequency domain mapping characteristics of different communication systems, and to calculate at least one of coarse frequency offset or coarse time offset using the detection metric. The detection metric values ​​of all candidate frequency points are sorted from largest to smallest, and a preset number of candidate frequency points are selected as output. The output is combined with at least one of coarse frequency offset or coarse time offset for subsequent cell search.

[0019] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the general frequency scanning method for satellite and mobile communication converged networks described in the first aspect or any corresponding embodiment thereof.

[0020] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the general frequency scanning method for a converged satellite and mobile communication network described in the first aspect or any corresponding embodiment thereof.

[0021] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the general frequency scanning method for a converged satellite and mobile communication network described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a general frequency scanning method for a converged satellite and mobile communication network according to an embodiment of the present invention. Figure 2 This is a structural block diagram of a general frequency scanning system for a converged satellite and mobile communication network according to an embodiment of the present invention; Figure 3 This is an example diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0026] In converged satellite and terrestrial mobile communication networks, terminals need to scan and synchronize multiple candidate frequency points when initially accessing or switching networks. Existing frequency scanning schemes typically involve power scanning, but simple power scanning is difficult to adapt to complex communication system designs, such as the difficulty in accurately identifying the source of power signals when resource utilization is high. Furthermore, frequency scanning schemes are usually designed for specific communication network standards, lacking versatility, and integrating multiple dedicated scanning modules results in high implementation costs.

[0027] According to embodiments of the present invention, a general frequency scanning method for converged satellite and mobile communication networks is provided. This method is compatible with narrowband and broadband systems, single-carrier and multi-carrier systems, and can adapt to different candidate frequency ranges and frame structures, effectively reducing the design and implementation complexity of multi-mode receivers and lowering costs. It should be noted that the steps shown in the flowcharts can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that presented here.

[0028] Figure 1 This is a flowchart of a general frequency scanning method for a converged satellite and mobile communication network according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S1: Receive a time-domain signal containing the candidate frequency points to determine the signal frequency range.

[0029] Specifically, the signal types involved in the embodiments of this invention cover the adaptation forms of different systems, ensuring compatibility with multiple scenarios such as 4G / 5G terrestrial communication, 5G NTN satellite communication, and narrowband single-carrier satellite communication; the signals are determined to be ZC sequences, PN sequences, or chirp signals, etc., which have different names in different communication systems, such as synchronization signals, frequency acquisition signals, or pilot signals. The duration of receiving time-domain signals... Generally, the transmission period of the signal is determined. For example, the initial search period for the synchronization signal block in 5G terrestrial mobile communication or 5G NTN satellite communication is 20ms. For 4G mobile communication systems, since the always-present broadband pilot signal is mapped, the duration of the received signal can be selected in combination with the need to reduce noise variance.

[0030] This invention covers various definitive signal types, including ZC sequences, PN sequences, and chirp signals, and is adaptable to multiple scenarios such as 4G / 5G terrestrial communication, 5G NTN, and narrowband single-carrier satellite communication. It is also compatible with signal forms with different names, such as synchronization signals, frequency acquisition signals, and pilot signals. At the same time, it flexibly adapts the reception duration (e.g., a 20ms transmission period for 5G synchronization signal blocks, and a suitable length for 4G based on noise variance requirements). This ensures the universality of multi-standard converged networks and improves noise suppression capabilities through duration optimization, providing accurate and flexible signal layer support for frequency point scanning with seamless full coverage.

[0031] Step S2: Based on the bandwidth and time slot structure of the communication system, determine the time-domain sampling rate and the Fast Fourier Transform (FFT) length. If the FFT length exceeds a preset maximum limit, divide the frequency domain bandwidth into sub-bands, set the FFT length to the preset maximum value, and adjust the time-domain sampling rate accordingly. Specifically, this includes the following steps: 1. Determine the frequency domain resolution: If the communication system is a multi-carrier communication system, the frequency domain resolution is set to the minimum subcarrier spacing of the downlink signal of the system; if the communication system is a single-carrier satellite communication system, the frequency domain resolution is determined by combining the system signal bandwidth and the requirements of subsequent cell search for residual frequency offset, and the frequency domain resolution is less than the absolute value of the maximum Doppler frequency shift of the system. This invention addresses the differences between multi-carrier communication systems and single-carrier satellite communication systems by employing a classification-based adaptation configuration logic. This ensures precise matching between frequency point scanning and signal subcarrier structure in multi-carrier systems, while simultaneously determining the resolution by considering the signal bandwidth, residual frequency offset requirements, and Doppler frequency shift characteristics of single-carrier satellite systems. This guarantees frequency offset coverage and scanning accuracy in high-dynamic satellite scenarios. This differentiated configuration avoids the compatibility issues caused by a uniform resolution, and by limiting the resolution of single-carrier systems to less than the absolute value of the maximum Doppler frequency shift, it provides a reliable foundation for subsequent coarse frequency offset estimation. Furthermore, it balances the scanning efficiency and detection accuracy of different systems, facilitating the efficient implementation of the solution in multi-standard scenarios within converged networks.

[0032] 2. Determine the initial time-domain sampling rate: based on the frequency domain bandwidth range that the communication system needs to cover. The minimum sampling rate that conforms to the Nyquist sampling theorem is selected as the time-domain sampling rate. This approach satisfies the requirement for complete frequency domain bandwidth coverage, avoids signal aliasing distortion caused by insufficient sampling rate, and ensures signal integrity during frequency scanning. Furthermore, by selecting the "minimum sampling rate," it minimizes computational load and hardware storage overhead during signal processing, reducing the resource consumption of the multi-mode receiver. This sampling rate configuration, which balances performance and efficiency, adapts to the wide frequency domain coverage requirements of converged satellite and terrestrial mobile communication networks, and lays an efficient foundation for subsequent processing steps such as Fast Fourier Transform, thus balancing scanning accuracy and system implementation cost.

[0033] 3. Calculate the Fast Fourier Transform length: based on the time-domain sampling rate. With frequency domain resolution Calculate the ratio of the length of the Fast Fourier Transform. ; 4. Subband Division and Parameter Adjustment: If the calculated Fast Fourier Transform length exceeds the maximum Fast Fourier Transform length supported by the system... Then adjust the time-domain sampling rate. and according to the formula The number of subbands that divide the frequency domain bandwidth range, among which For the number of sub-bands, Indicates rounding up. This refers to the frequency bandwidth range that needs to be covered.

[0034] Specifically, the length is The computational complexity of the Fast Fourier Transform is generally O(n log n). Meanwhile, the required storage space complexity is generally... In memory-constrained embedded systems, the maximum length of the supported Fast Fourier Transform is typically limited. .if The required frequency bandwidth range Divided into Sub-band, specified = ,but , This effectively overcomes the hardware limitations on the length of the Fast Fourier Transform (FFT). It ensures that the frequency domain resolution remains unchanged, maintaining the required frequency scanning accuracy, while achieving complete coverage of the required frequency bandwidth through sub-band division, avoiding incomplete frequency domain coverage issues caused by hardware limitations. Simultaneously, fixing the FFT length to the maximum supported by the hardware simplifies the hardware implementation logic of signal processing, reduces computational complexity and resource consumption, and balances the wide-frequency coverage requirements with hardware engineering constraints, enabling the solution to flexibly adapt to multi-mode receivers with different hardware configurations.

[0035] Step S3: Downsample the received signal to the time domain sampling rate, and perform a Fast Fourier Transform (FFT) according to the FFT length to obtain the frequency domain power spectrum.

[0036] Specifically, a total of Second Fast Fourier Transform For the duration of signal reception, For time-domain sampling rate, The fast Fourier transform (FFT) length is specified. In this embodiment, the received signal is first downsampled to a preset time-domain sampling rate to ensure the signal matches the parameters of subsequent processing, avoiding resource waste caused by redundant sampling. Then, the FFT is performed according to the determined length to obtain the frequency domain power spectrum, ensuring the accuracy of frequency domain analysis. The above formula clearly defines the number of FFT executions, achieving full utilization of complete data within the received signal duration, ensuring the frequency domain power spectrum comprehensively reflects the signal frequency characteristics. Furthermore, by fixing the matching relationship between the transform length and the sampling rate, the transform process is quantifiable and reproducible. This standardized processing flow avoids scanning errors caused by data omissions or redundancy, and provides a precise basis for hardware resource scheduling through explicit calculation of the number of iterations, reducing the complexity of signal processing. It also balances the efficiency and accuracy of frequency point scanning, laying a reliable foundation for subsequent steps such as power value averaging and subband splicing, adapting to the signal processing needs of various scenarios in fused networks.

[0037] Step S4: Determine the minimum statistical granularity of the time dimension, and within the range of the minimum statistical granularity of the time dimension, perform point-by-point averaging on the frequency domain power values ​​to obtain a set of averaged frequency domain power values. The statistical granularity of this invention is the smallest unit of time scheduling or the length of a determined signal duration; the smallest statistical granularity in the time dimension. The smallest unit for time-dimensional scheduling can be selected, such as a time slot or a symbol. 4G mobile communication systems map to a persistent broadband pilot signal. It can be directly equal to If the duration of the signal mapped to the target frequency is greater than the minimum unit of time-dimension scheduling, it can also be... Configure it to this time length.

[0038] Averaging the frequency domain power values ​​within the smallest statistical granularity of the time dimension: There are a total of The second fast Fourier transform yields Group length is The frequency domain power values ​​are averaged point by point to obtain a set of lengths. The frequency domain power value. During the reception duration. There are a total of Group length is The frequency domain power value.

[0039] Step S5: If there are sub-bands, perform transformation and averaging processes on each sub-band, and stitch the processing results of all sub-bands together in the frequency dimension. After stitching, the signal range and the maximum supported frequency offset are determined by covering all candidate frequency points.

[0040] Specifically, if there are sub-bands, for Each sub-band within the sub-band is calculated using steps S3 and S4, and then the data is spliced ​​together in the frequency dimension. The spliced ​​frequency domain power value still has two dimensions: time and frequency, with the number of points in the time dimension remaining the same. In the frequency dimension, it covers the range of all candidate frequency points to determine the signal range (including the maximum supported frequency offset).

[0041] Step S6: Obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, select the frequency domain power value corresponding to the frequency point according to the center frequency of the candidate frequency point, the bandwidth of the determined signal, and the maximum frequency offset range.

[0042] Specifically, for each candidate frequency in the preset frequency list, based on the center frequency of the candidate frequency... and determine the bandwidth of the signal and maximum frequency offset range (Frequency offset includes crystal oscillator frequency offset and Doppler frequency offset), select the frequency domain power value corresponding to this frequency point. The number of power value points in the frequency dimension after selection is... The number of points in the time dimension is .

[0043] Step S7: Calculate the detection metric for each candidate frequency point based on the physical channel time-frequency domain mapping characteristics of different communication systems, and use the detection metric to calculate at least one of coarse frequency offset or coarse time offset. Sort the detection metric values ​​of all candidate frequency points from largest to smallest, select a preset number of candidate frequency points as output, and combine at least one of coarse frequency offset or coarse time offset for subsequent cell search.

[0044] Specifically, for each candidate frequency point, using Each power value is calculated as a detection metric, with each frequency dimension... Calculate each power value ( (This step can be omitted at times) An initial detection metric value is obtained, the process of which includes: determining the number of frequency domain points corresponding to the bandwidth of the determined signal (i.e., ... Using a window length of , a sliding window average is applied to the frequency domain power values ​​corresponding to the selected candidate frequency points, and the maximum average value is selected as the initial detection metric; furthermore, the frequency corresponding to the maximum average value... Used to calculate initial coarse frequency offset ,Right now .

[0045] The embodiments of the present invention are based on the time dimension. The initial detection metric is further calculated ( (This step can be omitted when the value is 1) to obtain a final detection metric. If the determined signal is a periodic burst signal, then regarding the time dimension... The initial detection metric is used to calculate the peak-to-average ratio (PAR) by sliding the PAR values. The maximum PAR value is used as the final detection metric. Further, the initial coarse time bias is estimated based on the deviation distance between the position of the maximum PAR value and the assumed position of the determined signal. Alternatively, the number of initial detection metric values ​​that exceed a preset threshold is selected as the final detection metric, and the initial coarse time bias is estimated based on the deviation distance between the position of the maximum initial detection metric and the assumed position of the determined signal.

[0046] In one example, the preset threshold is a noise threshold, which is obtained by averaging the smallest preset quantity value among the initial detection metrics and multiplying it by a preset scaling factor, thus achieving dynamic adaptive adjustment of the threshold. This not only accurately captures the noise floor level in the current communication scenario, avoiding false detections or missed detections that occur in complex channel environments (such as time-varying noise in satellite channels and superimposed interference from terrestrial communication) due to fixed thresholds, but also adapts to the noise characteristics and detection performance requirements of different communication systems (4G / 5G terrestrial communication, satellite communication) through the configurability of the preset quantity value and scaling factor. This dynamic threshold mechanism improves the robustness of detection metric calculation, ensures accurate selection of target frequency points, and reduces system operation and maintenance costs by eliminating the need for manual intervention to adjust threshold parameters. It provides a reliable threshold judgment basis for frequency point scanning in multiple scenarios of converged networks, further ensuring the stability and efficiency of network access.

[0047] Furthermore, the final detection metric for all candidate frequency points. Sort from largest to smallest and select... (Make reasonable settings according to actual needs) 10 candidate frequency points, and combine them with at least one of coarse frequency offset or coarse time offset for subsequent cell search operations.

[0048] The embodiments of the present invention are as follows: The detection metric is calculated using power values, and layered processing of frequency and time dimensions ensures both accuracy and simultaneous estimation of coarse frequency and time offsets. In the frequency dimension, a sliding window average is used with a window length corresponding to the number of frequency points within the signal bandwidth. The maximum average value is selected as the initial detection metric, and coarse frequency offset estimation effectively filters noise interference, improving the reliability of target frequency identification. In the time dimension, for periodic burst signals, two methods for obtaining the final detection metric are provided: peak-to-average power ratio calculation and threshold counting, adapting to different signal patterns. Simultaneously, coarse time offset is estimated based on positional deviation distance, eliminating the need for subsequent independent time offset estimation steps. The L value is clearly defined. f =1、L t The logic for omitting values ​​when the value is 1 is optimized to reduce computational overhead; the dynamic calculation method for the noise threshold further improves the robustness of the metric.

[0049] Finally, candidate frequency points are selected by sorting the final detection metric values. At least one of coarse frequency offset or coarse time offset is used for subsequent cell search to filter high-priority targets, which greatly reduces the complexity and time consumption of cell search. It takes into account the adaptability of converged network multi-standard scenarios, scanning accuracy and access efficiency, and helps to realize seamless communication across the entire domain quickly.

[0050] This invention also provides a universal frequency scanning system for converged satellite and mobile communication networks, such as... Figure 2 As shown, it includes: Signal acquisition module 21 is used to receive a time-domain signal containing candidate frequency points to determine the signal frequency range; The parameter configuration module 22 is used to determine the time domain sampling rate and the fast Fourier transform length according to the bandwidth and time slot structure of the communication system. If the fast Fourier transform length exceeds the preset maximum limit, the frequency domain bandwidth range is divided into sub-bands, the fast Fourier transform length is set to the preset maximum value, and the time domain sampling rate is adjusted accordingly. The frequency domain conversion module 23 is used to downsample the received signal to the time domain sampling rate and perform a fast Fourier transform according to the fast Fourier transform length to obtain the frequency domain power spectrum. Power processing module 24 is used to determine the minimum statistical granularity in the time dimension, and to perform point-by-point averaging on the frequency domain power values ​​within the range of the minimum statistical granularity in the time dimension to obtain a set of averaged frequency domain power values. Subband processing module 25 is used to perform transformation and averaging processing on each subband if there are subbands, and to stitch together the processing results of all subbands in the frequency dimension. After stitching, it covers all candidate frequency points to determine the signal range and the maximum supported frequency offset. The frequency point filtering module 26 is used to obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, the frequency domain power value corresponding to the frequency point is selected according to the center frequency of the candidate frequency point, the bandwidth of the determined signal and the maximum frequency deviation range. The metric calculation and filtering module 27 is used to calculate the detection metric of each candidate frequency point based on the physical channel time-frequency domain mapping characteristics of different communication systems, and to calculate at least one of coarse frequency offset or coarse time offset using the detection metric. The detection metric values ​​of all candidate frequency points are sorted from largest to smallest, and a preset number of candidate frequency points are selected as output. The coarse frequency offset or coarse time offset is combined with at least one of the coarse frequency offset or coarse time offset for subsequent cell search.

[0051] In an optional embodiment, the parameter configuration module 22 includes: Frequency domain resolution determination unit: If the communication system is a multi-carrier communication system, the frequency domain resolution is set to the minimum subcarrier spacing of the downlink signal of the system; if the communication system is a single-carrier satellite communication system, the frequency domain resolution is determined by combining the system signal bandwidth and the requirements of subsequent cell search for residual frequency offset, and the frequency domain resolution is less than the absolute value of the maximum Doppler frequency shift of the system. The initial time-domain sampling rate determination unit is used to determine the frequency domain bandwidth range that the communication system needs to cover. The minimum sampling rate that conforms to the Nyquist sampling theorem is selected as the time-domain sampling rate. ; Calculate the Fast Fourier Transform length unit to determine the sampling rate in the time domain. With frequency domain resolution The ratio is used to calculate the length of the Fast Fourier Transform; The subband division and parameter adjustment unit is used when the calculated Fast Fourier Transform (FFT) length exceeds the maximum FFT length supported by the system. Then adjust the time-domain sampling rate. and according to the formula Number of subbands dividing the frequency domain bandwidth range The number of sub-bands, where Indicates rounding up. This refers to the frequency bandwidth range that needs to be covered.

[0052] The number of power value points in the frequency dimension after selecting the frequency point and its corresponding frequency domain power value is: , Indicates the maximum frequency offset. This indicates the bandwidth of the signal; the number of points in the time dimension is... .

[0053] In an optional embodiment, the metric calculation and filtering module 27 includes: The initial detection metric calculation and coarse frequency offset estimation unit is used to calculate the selected candidate frequency points using a window length corresponding to the number of frequency domain points corresponding to the bandwidth of the determined signal. The corresponding frequency domain power values ​​are averaged using a sliding window, and the maximum average value is selected as the initial detection metric. The initial coarse frequency offset is estimated based on the difference between the frequency corresponding to the maximum average value and the center frequency of the candidate frequency point, where when… When =1, the coarse frequency offset estimation step is omitted; The final detection metric calculation and coarse time bias estimation unit is used to, if the determined signal is a periodic burst signal, estimate the time dimension. The initial detection metric is used to calculate the peak-to-average power ratio (PAPR) using a sliding method. The maximum PAPR value is taken as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum PAPR value and the assumed position of the determined signal. Alternatively, the number of initial detection metric values ​​exceeding a preset threshold is selected as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum initial detection metric and the assumed position of the determined signal. When =1, the coarse time-partial estimation step is omitted.

[0054] In an optional embodiment, the preset threshold of the coarse time bias estimation unit is a noise threshold, which is obtained by averaging the smallest preset quantity value among the initial detection metrics and multiplying it by a preset scaling factor.

[0055] In an optional embodiment, the determination signal of the signal acquisition module 21 includes at least one of a synchronization signal, a frequency acquisition signal, or a pilot signal in different communication systems; the maximum frequency offset includes the crystal oscillator frequency offset of the communication system and the Doppler frequency offset of the satellite communication.

[0056] The system provided in this embodiment of the invention can execute the general frequency scanning method for satellite and mobile communication converged networks provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0057] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0058] The following is a detailed reference. Figure 3 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0059] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0060] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a memory 308, or installed from a ROM 302. When the computer program is executed by the processor 301, it performs the functions defined in the general frequency scanning method for a converged satellite and mobile communication network according to embodiments of the present invention.

[0061] Figure 3 The device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0062] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the general frequency scanning method for satellite and mobile communication converged networks shown in the above embodiments is implemented.

[0063] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0064] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A general frequency scanning method for converged satellite and mobile communication networks, characterized in that, Includes the following steps: Receive time-domain signals containing candidate frequency points to determine the signal frequency range; Based on the bandwidth and time slot structure of the communication system, the time domain sampling rate and the fast Fourier transform length are determined. If the fast Fourier transform length exceeds the preset maximum limit, the frequency domain bandwidth range is divided into sub-bands, the fast Fourier transform length is set to the preset maximum value, and the time domain sampling rate is adjusted accordingly. The received signal is downsampled to the time-domain sampling rate, and a fast Fourier transform is performed according to the fast Fourier transform length to obtain the frequency-domain power spectrum. Determine the minimum statistical granularity in the time dimension, and within the range of the minimum statistical granularity in the time dimension, perform point-by-point averaging on the frequency domain power values ​​to obtain a set of averaged frequency domain power values. If there are sub-bands, perform transformation and averaging processes on each sub-band separately, and then stitch the processing results of all sub-bands together in the frequency dimension. After stitching, the signal range and the maximum supported frequency offset are determined by covering all candidate frequency points. Obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, select the frequency domain power value corresponding to the frequency point based on the center frequency of the candidate frequency point, the bandwidth of the determined signal, and the maximum frequency offset range. The detection metric of each candidate frequency point is calculated based on the physical channel time-frequency domain mapping characteristics of different communication systems. The detection metric is then used to calculate at least one of coarse frequency offset or coarse time offset. The detection metric values ​​of all candidate frequency points are sorted from largest to smallest. A preset number of candidate frequency points are selected as output and combined with at least one of coarse frequency offset or coarse time offset for subsequent cell search.

2. The method according to claim 1, characterized in that, The step of determining the time-domain sampling rate and Fast Fourier Transform (FFT) length based on the bandwidth and time slot structure of the communication system, and if the FFT length exceeds a preset maximum limit, then dividing the frequency domain bandwidth into sub-bands, configuring the FFT length to a preset maximum value, and adjusting the time-domain sampling rate, includes: Determine the frequency domain resolution: If the communication system is a multi-carrier communication system, the frequency domain resolution is set to the minimum subcarrier spacing of the downlink signal of the system; if the communication system is a single-carrier satellite communication system, the frequency domain resolution is determined by combining the system signal bandwidth and the requirements of subsequent cell search for residual frequency offset, and the frequency domain resolution is less than the absolute value of the maximum Doppler frequency shift of the system. Determine the initial time-domain sampling rate: based on the frequency domain bandwidth range that the communication system needs to cover. The minimum sampling rate that conforms to the Nyquist sampling theorem is selected as the time-domain sampling rate. ; Calculate the Fast Fourier Transform length: based on the time-domain sampling rate With frequency domain resolution The ratio is used to calculate the length of the Fast Fourier Transform; Subband division and parameter adjustment: If the calculated Fast Fourier Transform length exceeds the maximum Fast Fourier Transform length supported by the system. Then adjust the time-domain sampling rate. and according to the formula The number of subbands that divide the frequency domain bandwidth range, among which For the number of sub-bands, Indicates rounding up. This refers to the frequency bandwidth range that needs to be covered.

3. The method according to claim 1 or 2, characterized in that, The number of power value points in the frequency dimension after selecting the frequency point and its corresponding frequency domain power value is: , Indicates the maximum frequency offset. This indicates the bandwidth of the signal; the number of points in the time dimension is... .

4. The method according to claim 3, characterized in that, The step of calculating the detection metric for each candidate frequency point based on the time-frequency domain mapping characteristics of the physical channels of different communication systems, and using the detection metric to calculate at least one of coarse frequency offset or coarse time offset, includes: Using the number of frequency domain points corresponding to the bandwidth of the determined signal as the window length, the selected candidate frequency points are... The corresponding frequency domain power values ​​are averaged using a sliding window, and the maximum average value is selected as the initial detection metric. The initial coarse frequency offset is estimated based on the difference between the frequency corresponding to the maximum average value and the center frequency of the candidate frequency point, where when… When =1, the coarse frequency offset estimation step is omitted; If the determined signal is a periodic burst signal, then regarding the time dimension... The initial detection metric is used to calculate the peak-to-average power ratio (PAPR) using a sliding method. The maximum PAPR value is taken as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum PAPR value and the assumed position of the determined signal. Alternatively, the number of initial detection metric values ​​exceeding a preset threshold is selected as the final detection metric, and the initial coarse time offset is estimated based on the deviation between the position of the maximum initial detection metric value and the assumed position of the determined signal. When =1, the coarse time-partial estimation step is omitted.

5. The method according to claim 4, characterized in that, The preset threshold is a noise threshold, which is obtained by averaging the smallest preset quantity value among the initial detection metrics and multiplying it by a preset scaling factor.

6. The method according to claim 1, characterized in that, The determining signal includes at least one of a synchronization signal, a frequency acquisition signal, or a pilot signal in different communication systems; the maximum frequency offset includes the crystal oscillator frequency offset of the communication system and the Doppler frequency offset of the satellite communication.

7. A universal frequency scanning system for converged satellite and mobile communication networks, characterized in that, include: The signal acquisition module is used to receive a time-domain signal containing candidate frequency points to determine the signal frequency range; The parameter configuration module is used to determine the time domain sampling rate and the fast Fourier transform length according to the bandwidth and time slot structure of the communication system. If the fast Fourier transform length exceeds the preset maximum limit, the frequency domain bandwidth range is divided into sub-bands, the fast Fourier transform length is set to the preset maximum value, and the time domain sampling rate is adjusted accordingly. The frequency domain conversion module is used to downsample the received signal to the time domain sampling rate and perform a fast Fourier transform according to the fast Fourier transform length to obtain the frequency domain power spectrum. The power processing module is used to determine the minimum statistical granularity in the time dimension, and to perform point-by-point averaging on the frequency domain power values ​​within the range of the minimum statistical granularity in the time dimension to obtain a set of averaged frequency domain power values. The sub-band processing module is used to perform transformation and averaging processes on each sub-band if there are sub-bands, and to stitch the processing results of all sub-bands together in the frequency dimension. After stitching, it covers all candidate frequency points to determine the signal range and the maximum supported frequency offset. The frequency point filtering module is used to obtain a preset frequency point list covering the candidate frequency point range of satellite communication and terrestrial mobile communication. For each candidate frequency point in the preset frequency point list, the frequency domain power value corresponding to the frequency point is selected according to the center frequency of the candidate frequency point, the bandwidth of the determined signal and the maximum frequency deviation range. The metric calculation and filtering module is used to calculate the detection metric of each candidate frequency point based on the physical channel time-frequency domain mapping characteristics of different communication systems, and to calculate at least one of coarse frequency offset or coarse time offset using the detection metric. The detection metric values ​​of all candidate frequency points are sorted from largest to smallest, and a preset number of candidate frequency points are selected as output. The output is combined with at least one of coarse frequency offset or coarse time offset for subsequent cell search.

8. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the general frequency scanning method for a converged satellite and mobile communication network as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the general frequency scanning method for a converged satellite and mobile communication network as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the general frequency scanning method for a converged satellite and mobile communication network as described in any one of claims 1 to 6.

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