WO2023178998A1 - Ta估计方法、网络设备、装置及存储介质 - Google Patents

Ta估计方法、网络设备、装置及存储介质 Download PDF

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WO2023178998A1
WO2023178998A1 PCT/CN2022/125907 CN2022125907W WO2023178998A1 WO 2023178998 A1 WO2023178998 A1 WO 2023178998A1 CN 2022125907 W CN2022125907 W CN 2022125907W WO 2023178998 A1 WO2023178998 A1 WO 2023178998A1
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peak power
time delay
absolute value
fractional
fractional time
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PCT/CN2022/125907
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English (en)
French (fr)
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张艳
李成钢
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大唐移动通信设备有限公司
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Priority to JP2023570258A priority Critical patent/JP2024518572A/ja
Priority to MX2023014215A priority patent/MX2023014215A/es
Publication of WO2023178998A1 publication Critical patent/WO2023178998A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements

Definitions

  • the present disclosure relates to the field of wireless communication technology, and in particular, to a TA estimation method, network equipment, device and storage medium.
  • the Physical Random Access Channel is used to complete the uplink synchronization between the terminal (also called User Equipment (UE)) and the network equipment (such as the base station). It is the third channel sent during the random access process.
  • An uplink signal (msg1).
  • the network device estimates the signal transmission delay between the terminal and the network device through the received PRACH signal, calculates the uplink transmission time advance (Timing Advance, TA) and sends it to the terminal.
  • Timing Advance, TA uplink transmission time advance
  • the terminal advances the sending time of the Physical Uplink Shared Channel (PUSCH) by the TA based on the uplink timing obtained from the downlink timing, so as to ensure that the PUSCH arrives before and after the reception time expected by the network device. All terminals in the same cell complete uplink synchronization according to this process.
  • the uplink signals sent by it can basically reach the network equipment synchronously. If the TA error estimated by the network equipment is large, on the one hand it will affect the demodulation performance of other uplink signals sent by the terminal after sending the PRACH. On the other hand, it will cause the signals of different terminals to be asynchronous in time and interfere with each other. Therefore, the accuracy of TA estimation is very important.
  • TA is estimated based on the correlation peak position, and the estimation accuracy depends on the time domain resolution of the correlation sequence.
  • a commonly used method to improve the time domain resolution of related sequences is to increase the number of Inverse Fast Fourier Transform (IFFT) points by padding zeros in the frequency domain data.
  • IFFT Inverse Fast Fourier Transform
  • Embodiments of the present disclosure provide a TA estimation method, network equipment, device and storage medium to improve the accuracy of TA estimation.
  • embodiments of the present disclosure provide a time advance TA estimation method, including:
  • the fractional multiple of the target normalized total delay is determined; the target normalized total delay is used to characterize the signal detected by the target detection window.
  • the transmission delay is a multiple of the sample interval of the relevant sequence;
  • the updated position index value of the peak power determine the offset of the position of the peak power relative to the starting position of the target detection window
  • the TA estimation value corresponding to the target detection window is determined.
  • determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window includes:
  • the fractional time delay is determined based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power.
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined based on the first peak power ratio and the length of the ZC root sequence corresponding to the target detection window.
  • the absolute value of the fractional time delay is determined by the following formula:
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay.
  • determining the absolute value of the fractional time delay based on the first peak power ratio and a preset correspondence between the peak power ratio and the absolute value of the fractional time delay includes:
  • the first peak power ratio is compared with the peak power ratio in the preset correspondence table, and it is determined that the value in the preset correspondence table is less than the first peak power.
  • the index value corresponding to the first peak power ratio of the ratio, and the preset correspondence table includes a preset correspondence between the peak power ratio and the absolute value of the decimal time delay;
  • the absolute value of the fractional time delay is determined according to the index value corresponding to the first peak power ratio that is smaller than the first peak power ratio.
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and a piecewise function used to characterize the correlation between the peak power ratio and the absolute value of the fractional time delay.
  • the absolute value of the fractional time delay is determined by the following formula:
  • determining the fractional time delay based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power includes:
  • the fractional time delay is determined to be a positive number.
  • updating the location index value of the peak power according to the fractional time delay includes:
  • the position index value of the peak power is updated according to the sum of the initial position index value of the peak power and the fractional time delay.
  • the method before determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window, the method further includes:
  • the sub-peak power is determined based on the maximum value of the power of the two sample point positions of the left and right nearest neighbors.
  • embodiments of the present disclosure also provide a network device, including a memory, a transceiver, and a processor:
  • Memory used to store computer programs
  • transceiver used to send and receive data under the control of the processor
  • processor used to read the computer program in the memory and perform the following operations:
  • the fractional multiple of the target normalized total delay is determined; the target normalized total delay is used to characterize the signal detected by the target detection window.
  • the transmission delay is a multiple of the sample interval of the relevant sequence;
  • the updated position index value of the peak power determine the offset of the position of the peak power relative to the starting position of the target detection window
  • an estimated time advance TA corresponding to the target detection window is determined.
  • determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window includes:
  • the fractional time delay is determined based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power.
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined based on the first peak power ratio and the length of the ZC root sequence corresponding to the target detection window.
  • the absolute value of the fractional time delay is determined by the following formula:
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay.
  • determining the absolute value of the fractional time delay based on the first peak power ratio and a preset correspondence between the peak power ratio and the absolute value of the fractional time delay includes:
  • the first peak power ratio is compared with the peak power ratio in the preset correspondence table, and it is determined that the value in the preset correspondence table is less than the first peak power.
  • the index value corresponding to the first peak power ratio of the ratio, and the preset correspondence table includes a preset correspondence between the peak power ratio and the absolute value of the decimal time delay;
  • the absolute value of the fractional time delay is determined according to the index value corresponding to the first peak power ratio that is smaller than the first peak power ratio.
  • determining the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window includes:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and a piecewise function used to characterize the correlation between the peak power ratio and the absolute value of the fractional time delay.
  • the absolute value of the fractional time delay is determined by the following formula:
  • determining the fractional time delay based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power includes:
  • the fractional time delay is determined to be a positive number.
  • updating the location index value of the peak power according to the fractional time delay includes:
  • the position index value of the peak power is updated according to the sum of the initial position index value of the peak power and the fractional time delay.
  • the operation before determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window, the operation further includes:
  • the sub-peak power is determined based on the maximum value of the power of the two sample point positions of the left and right nearest neighbors.
  • embodiments of the present disclosure also provide a device for estimating time advance TA, including:
  • the first determination unit is used to determine the fractional multiple of the target normalized total delay according to the peak power and sub-peak power of the target detection window; the target normalized total delay is used to characterize the target
  • the transmission delay of the signal detected by the detection window is a multiple of the sample interval of the relevant sequence;
  • a second determination unit configured to determine the offset of the position of the peak power relative to the starting position of the target detection window according to the updated position index value of the peak power
  • a third determination unit is configured to determine the TA estimation value corresponding to the target detection window according to the offset.
  • embodiments of the present disclosure further provide a computer-readable storage medium storing a computer program, the computer program being used to cause the computer to perform the TA estimation described in the first aspect as above. Method steps.
  • an embodiment of the present disclosure also provides a communication device, a computer program is stored in the communication device, and the computer program is used to cause the communication device to execute the steps of the TA estimation method described in the first aspect.
  • embodiments of the present disclosure also provide a processor-readable storage medium that stores a computer program, and the computer program is used to cause the processor to execute the above-described first aspect.
  • the steps of TA estimation method are described in detail below.
  • embodiments of the present disclosure also provide a chip product.
  • a computer program is stored in the chip product.
  • the computer program is used to cause the chip product to execute the steps of the TA estimation method described in the first aspect.
  • the TA estimation method, network equipment, device and storage medium provided by the embodiments of the present disclosure determine the fractional time delay based on the peak power and the sub-peak power, and then adjust the position of the peak power based on the fractional time delay. According to the adjusted more Using fine peak power positions for TA estimation can not only improve the accuracy of TA estimation, but also eliminates the need to add zeros to the data to improve the time domain resolution of the relevant sequence, thus avoiding the resulting power dispersion problem.
  • Figure 1 is a schematic flowchart of a TA estimation method provided by an embodiment of the present disclosure
  • Figure 2 is a graph illustrating the change of the peak power ratio with the absolute value of the fractional time delay provided by the embodiment of the present disclosure
  • Figure 3 is a schematic structural diagram of a network device provided by an embodiment of the present disclosure.
  • Figure 4 is a schematic structural diagram of a TA estimation device provided by an embodiment of the present disclosure.
  • the term "and/or” describes the association relationship of associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone. these three situations.
  • the character "/” generally indicates that the related objects are in an "or” relationship.
  • the term “plurality” refers to two or more than two, and other quantifiers are similar to it.
  • Both 4G Long Term Evolution (LTE) and 5G New Radio (NR) systems use Orthogonal Frequency Division Multiple Access (OFDMA) technology to ensure the signal transmission of different terminals in the community.
  • OFDMA Orthogonal Frequency Division Multiple Access
  • the uplink signal transmission time advance TA of each terminal should be equal to 2 times the one-way transmission delay TP of the signal between the terminal and the base station.
  • the base station passes each PRACH sent by each terminal to estimate the TA of the terminal.
  • the PRACH of the NR system consists of three parts: the cyclic prefix CP, the Zadoff-Chu (ZC) sequence (i.e., the preamble sequence) and the guard interval GT.
  • the ZC sequence used in the PRACH has good autocorrelation and cross-correlation properties, so the sequence correlation can be used.
  • the method detects the received PRACH signal and estimates TA.
  • Step1 Extract the preamble sequence from the received PRACH time domain signal and remove the CP and GT parts.
  • Step2 Use the received preamble sequence to correlate with the ZC root sequence, and calculate the power of each sample point in the correlation sequence.
  • Sequence correlation can be implemented using FFT & IFFT, and the time domain resolution of the correlation sequence can be improved by adding 0s in the frequency domain to increase the number of IFFT points.
  • Step3 Divide the correlation sequence into several detection windows, search for the sample point with the highest power (i.e. correlation peak) in each detection window, and calculate the offset ⁇ pos of the correlation peak position relative to the starting position of the detection window, The starting position of the detection window is the corresponding correlation peak position when the signal transmission delay is 0.
  • Step 4 Convert the relevant peak position offset ⁇ pos into TA according to the following formula.
  • TA float represents the TA estimate
  • ⁇ f RA is the PRACH subcarrier spacing
  • N IFFT is the number of IFFT points in the sequence correlation process
  • N IFFT ⁇ L RA L RA refers to the ZC sequence length
  • u is the subcarrier spacing index of PUSCH .
  • the TA actually sent by the base station to the terminal is an integer, so the above floating point result TA float needs to be rounded.
  • the rounding method can be rounding down or rounding.
  • TA is estimated based on the correlation peak position.
  • the estimation accuracy depends on the time domain resolution of the correlation sequence, that is, the time interval between two adjacent sample points of the correlation sequence. The smaller ⁇ t is, the higher the time domain resolution is.
  • the relevant sequence generally has only one large peak value.
  • the signal transmission delay calculated based on the peak position is the same as the direct path delay. The maximum difference between delays is Therefore, reducing ⁇ t and improving the time domain resolution of the correlation sequence can bring the correlation peak position closer to the direct path delay, making TA estimation more accurate.
  • a commonly used method to improve the time domain resolution of the correlation sequence is to increase the number of IFFT points N IFFT by padding the frequency domain data with 0s.
  • this will cause the power dispersion of the correlation sequence while improving the time domain resolution, that is, the correlation peak power will It is dispersed to adjacent sample points on the left and right.
  • noise and interference are usually superimposed on the received signal, which may cause If the peak position is selected incorrectly, the TA estimation error will be large.
  • the frequency domain data is not filled with zeros and the L RA point discrete Fourier Transform (IDFT) is directly performed, the above power dispersion problem will not exist, but at this time If it is large, the correlation peak position is not precise enough, and the deviation between the estimated signal transmission delay and the real direct path delay may be large, so the TA estimation error will also be large.
  • IDFT discrete Fourier Transform
  • various embodiments of the present disclosure provide a solution to accurately calculate the decimal fraction of the normalized total delay based on the ratio of the correlation peak power to the left and right adjacent sub-peak power and the position relationship between the correlation peak and the sub-peak value. times the delay to accurately estimate TA. Moreover, since the fractional times delay can be accurately obtained, even if the time domain resolution of the correlation sequence is not improved, a more precise correlation peak position can be obtained based on the fractional times delay, thereby avoiding the need to add 0 to the frequency domain data. The power dispersion problem caused by other methods to improve the time domain resolution of the correlation sequence.
  • N is the length of the ZC sequence
  • n+n 0 is the normalized total delay, that is, the signal delay is a multiple of the ZC sequence sample interval, where n is a non-negative integer, which represents the normalized The delay is an integer multiple of the total delay.
  • n 0 is a decimal between -0.5 and 0.5, which represents the fractional multiple of the normalized total delay.
  • n 0 0
  • the ZC sequence correlation power occurs Diffusion, but the diffuse power is mainly distributed on adjacent sample points to the left and right of the peak. The farther away from the peak, the smaller the diffuse power is.
  • the following are the relevant power values at m n-1, n and n+1 when n 0 ⁇ 0.
  • the TA estimation scheme does not need to increase the number of IFFT points by adding 0 to improve the time domain resolution of the correlation sequence. It only needs to use N-point correlation power data, according to the correlation peak and The ratio of the left and right adjacent sub-peak powers and the positional relationship between the correlation peak and the sub-peak can accurately calculate the decimal time delay n 0 , and replace the correlation peak position n with n+n 0 to obtain a more precise correlation peak position , thereby accurately estimating TA.
  • FIG. 1 is a schematic flowchart of a TA estimation method provided by an embodiment of the present disclosure. This method can be applied to network equipment (such as a base station). As shown in Figure 1, the method includes the following steps:
  • Step 100 Determine the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window; the target normalized total delay is used to characterize the transmission of the signal detected by the target detection window
  • the time delay is a multiple of the sample interval of the relevant sequence.
  • the network device extracts the preamble sequence from the received PRACH time domain signal, uses the received preamble sequence to correlate with the ZC root sequence, and calculates the value of each sample point in the related sequence. power.
  • the relevant sequence is divided into several detection windows.
  • the network device can use the peak power of the target detection window (i.e., the maximum value among the power of various sample points in the detection window) and the sub-peak power (i.e., the detection window The second largest value among the power of each sample point in the window), determine the fractional multiple of the target normalized total delay, which is n 0 as mentioned above.
  • the value of n 0 can be obtained through the formula mentioned above based on the ratio between the peak power and the sub-peak power and the relative position relationship between the peak power and the sub-peak power.
  • the method before determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window, the method also includes:
  • the sub-peak power is determined based on the maximum value of the power of the two nearest neighbor sample points on the left and right.
  • the ZC sequence correlation power has only one non-zero value, and this non-zero value is the correlation peak.
  • the correlation peak position relative to its location can be directly calculated based on the position of the correlation peak. Detect the offset ⁇ pos of the starting position of the window, and then obtain the TA estimate.
  • the ZC sequence correlation power will be dispersed, that is, multiple non-zero values will appear.
  • the dispersed power is mainly distributed on the adjacent sample points to the left and right of the peak. The farther away from the peak, the greater the dispersed power on the sample points. Small, so the peak power usually appears at the left or right sample point position closest to the peak power position.
  • the power of the two sample point positions nearest to the left and right neighbors of the initial position of the peak power can be first determined, and then the power of the two sample point positions is compared, and the updated Larger power is used as sub-peak power.
  • the initial position of the peak power is n
  • the sample position of the nearest neighbor on the left is n-1
  • the sample position of the nearest neighbor on the right is n+1
  • the n-1 position and n+1 position can be obtained respectively.
  • compare the sample power at these two positions and take the larger sample power as the sub-peak power.
  • the sub-peak power can be determined by simply comparing the power of the two sample point positions that are the nearest neighbors to the left and right of the initial position of the peak power, which greatly reduces the amount of calculations.
  • Step 101 Update the location index value of the peak power according to the fractional time delay.
  • the position index value of the peak power can be updated according to the value of n 0 , so that the relevant peak position used to estimate TA is more refined and accurate.
  • updating the location index value of the peak power based on the fractional multiple of the delay may include: updating the location index value of the peak power based on the sum of the initial location index value of the peak power and the fractional multiple of the delay. For example, assuming that the initial position index value of the peak power is n, after determining the value of the fractional time delay n 0 , the initial position index value n of the peak power can be added to n 0 as the updated position index of the peak power. value, that is, replace n with n+n 0 for TA estimation.
  • Step 102 Determine the offset of the position of the peak power relative to the starting position of the target detection window based on the updated position index value of the peak power.
  • the offset of the position of the peak power relative to the starting position of the target detection window can be calculated based on the updated position index value of the peak power.
  • the initial position index value of the peak power is n
  • the position index value of the updated peak power is n+n 0
  • the index value of the starting position of the target detection window is x
  • the value between n+n 0 and x can be The difference is taken as the offset of the position of the peak power relative to the starting position of the target detection window.
  • Step 103 Determine the TA estimation value corresponding to the target detection window according to the offset.
  • the estimated TA value corresponding to the target detection window can be calculated based on the offset, and the estimated TA value can subsequently be rounded. and then sent to the terminal corresponding to the target detection window.
  • the TA estimate corresponding to the target detection window can be calculated according to the following formula:
  • TA float represents the TA estimate corresponding to the target detection window
  • ⁇ pos represents the offset determined above
  • N IFFT represents the number of IFFT points in the sequence correlation process corresponding to the target detection window
  • ⁇ f RA represents the PRACH sub-section corresponding to the target detection window Carrier spacing
  • u represents the subcarrier spacing index of the terminal sending PUSCH corresponding to the target detection window.
  • the TA estimation method determines the fractional time delay based on the peak power and the sub-peak power, then adjusts the position of the peak power based on the fractional time delay, and performs TA based on the more refined peak power position after adjustment. Estimation can not only improve the accuracy of TA estimation, but also eliminate the need to add 0 to the data to improve the time domain resolution of the relevant sequence, thus avoiding the power dispersion problem caused by it.
  • determine the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined
  • the fractional delay is determined based on the absolute value of the fractional delay and the initial position relationship between the peak power and the sub-peak power.
  • the fractional time delay you can first determine the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window, for example , the peak power of the target detection window can be divided by the sub-peak power to obtain the first peak power ratio.
  • the small power ratio can be obtained through various methods such as theoretical calculation, table lookup, piecewise function approximation or weighted average approximation. The absolute value of several times the delay.
  • the sign of the fractional time delay is determined based on the initial position relationship between the peak power and the sub-peak power, and finally the value of the fractional time delay is obtained.
  • the method of determining the fractional delay can be more flexible and diverse, thereby improving The flexibility of TA estimation facilitates simple and fast TA estimation.
  • determine the fractional time delay based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power including:
  • the fractional time delay is determined to be a positive number.
  • the ZC sequence correlation power will be dispersed.
  • the dispersed power is mainly distributed on the adjacent sample points to the left and right of the peak. The farther away from the peak, the smaller the dispersed power is on the sample points. Therefore, this time
  • the peak power usually appears at the left or right sample point position closest to the peak power position.
  • the sub-peak power position is to the left of the peak power position.
  • the sub-peak power position is at The position of the peak power is to the right, so whether n 0 is a positive or negative number can be determined based on the relative position relationship between the peak power and the sub-peak power.
  • the relative position relationship between the peak power and the sub-peak power can be determined by comparing the initial position index value of the peak power and the initial position index value of the sub-peak power, thereby determining the sign of the fractional time delay. For example, if the initial position index value of the sub-peak power is smaller than the initial position index value of the peak power, it indicates that the initial position of the sub-peak power is to the left of the initial position of the peak power, then it can be determined that the fractional delay is a negative number; if the sub-peak power The initial position index value is greater than the initial position index value of the peak power, indicating that the initial position of the sub-peak power is to the right of the initial position of the peak power, then it can be determined that the fractional delay is a positive number.
  • determine the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined.
  • the absolute fractional time delay can be determined based on the first peak power ratio between the peak power and the sub-peak power of the target detection window and the length of the ZC root sequence corresponding to the target detection window. value. It can be seen from the above that there is a certain functional relationship between the decimal time delay, the peak power ratio and the length of the ZC root sequence. Therefore, the peak power ratio and ZC can be determined based on the functional relationship between the three. After determining the length of the root sequence, the absolute value of the fractional time delay is calculated, so that the most accurate calculation result of the fractional time delay can be obtained through theoretical calculation.
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay.
  • the corresponding relationship between different peak power ratios and the absolute value of the decimal time delay can be set in advance, so as to obtain the first peak value between the peak power and the sub-peak power of the target detection window.
  • the absolute value of the fractional delay corresponding to the first peak power ratio can be determined based on a preset correspondence between the peak power ratio and the absolute value of the fractional delay.
  • the preset correspondence can be quickly The absolute value of the fractional delay corresponding to the first peak power ratio is obtained, thereby improving the efficiency of TA estimation.
  • the preset correspondence relationship may be embodied in the form of a preset correspondence relationship table.
  • the preset correspondence between the peak power ratio and the absolute value of the fractional delay can also be embodied in other ways, which is not limited here.
  • the peak power ratio between the peak power and the sub-peak power vs. the absolute value of the fractional time delay can be pre-stored. After calculating the first peak power ratio, look up the table to obtain the corresponding absolute value of the decimal time delay
  • each absolute value of the decimal delay corresponds to a peak power ratio.
  • the first peak power ratio obtained based on the peak power and sub-peak power of the target detection window is 2000.
  • the peak power ratio is a decimal multiple of 1045.44.
  • determine the absolute value of the fractional time delay based on the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay including:
  • the preset correspondence table includes the preset correspondence between the peak power ratio and the absolute value of the decimal time delay;
  • the absolute value of the fractional time delay is determined based on the index value corresponding to the first peak power ratio that is smaller than the first peak power ratio.
  • the first peak power ratio can be sequentially compared with the preset correspondence table in order from the largest to the smallest peak power ratio. Compare the peak power ratios in , and determine the index value corresponding to the first peak power ratio smaller than the first peak power ratio in the preset correspondence table.
  • the index value can increase sequentially in the order of the absolute value of the decimal multiple delay from small to large, or can also increase in the order of the absolute value of the decimal multiple delay from large to small, or it can be the same as There are other correspondences between the absolute values of fractional time delays, which are not limited here.
  • each group of decimal delay absolute value-peak power ratio in the table corresponds to an index value
  • the index values increase in order from small to large decimal delay absolute values, such as 0.01- 9800.96 corresponds to index value 1
  • 0.02-2400.99 corresponds to index value 2
  • 0.50-1.00 corresponds to index value 50.
  • the first peak power ratio is 2000 based on the peak power and sub-peak power of the target detection window
  • Table 1 can be determined
  • the first peak power ratio that is smaller than the first peak power ratio is 1045.44, and its corresponding index value is 3.
  • the absolute value of the decimal multiple of the delay corresponding to the first peak power ratio can be determined based on the index value. .
  • the absolute value of the fractional time delay corresponding to the index value 3, 0.03, can be used as the absolute value of the fractional time delay corresponding to the first peak power ratio, or the absolute value of the fractional time delay corresponding to the index value 3 can be used
  • the absolute value of the fractional time delay corresponding to the index value 2 is averaged and used as the absolute value of the fractional time delay corresponding to the first peak power ratio.
  • Other processing methods may also be used. Obtaining the corresponding absolute value of the fractional delay through the index value can effectively improve the table lookup efficiency.
  • the absolute value of the fractional delay can be determined by the following formula:
  • the data stored in the table is recorded as a matrix table, its dimension is L*2, L is the number of absolute values of decimal times of delay in Table 1, table(index,1) returns the index The absolute value of the decimal multiple of the delay corresponding to the value index.
  • the results obtained by looking up the table can be made closer to the theoretical calculation value.
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the piecewise function used to characterize the correlation between the peak power ratio and the absolute value of the fractional time delay.
  • a piecewise function for characterizing the correlation between the peak power ratio and the absolute value of the fractional delay can be set in advance.
  • the piecewise function can be calculated by comparing the peak power ratio and the fractional delay.
  • the theoretical expression of the functional relationship between absolute values is obtained by piecewise approximation, so that complex calculation expressions can be approximated into simple linear functions, which can effectively reduce the amount of calculation when calculating the absolute value of fractional times of delay.
  • the peak power ratio corresponding to different absolute values of fractional delay can be calculated based on the theoretical expression of the functional relationship between the peak power ratio and the absolute value of the fractional delay.
  • Figure 2 is The graph of the peak power ratio changing with the absolute value of the fractional time delay provided by the embodiment of the present disclosure is as shown in Figure 2.
  • the curve in the figure is the abscissa of the absolute value of the fractional time delay, and the peak and sub-peak power ratio. (i.e., the peak power ratio between peak power and sub-peak power) is the theoretical curve drawn as the ordinate.
  • this embodiment of the disclosure provides an expression of a piecewise function.
  • the absolute value of the fractional delay can be determined by the following formula:
  • the absolute value of the fractional delay can also be determined by the following formula:
  • embodiments of the present disclosure provide a method for determining the absolute value of a fractional multiple of the delay. Its essence is to perform a weighted average of the peak position and the sub-peak position using their respective power values, and use the averaged result as the updated peak position to calculate TA.
  • the derivation is as follows:
  • the updated peak position is:
  • Figure 3 is a schematic structural diagram of a network device provided by an embodiment of the present disclosure.
  • the network device includes a memory 320, a transceiver 310 and a processor 300; the processor 300 and the memory 320 can also be physically arranged separately. .
  • the memory 320 is used to store computer programs; the transceiver 310 is used to send and receive data under the control of the processor 300.
  • the transceiver 310 is used to receive and transmit data under the control of the processor 300.
  • the bus architecture may include any number of interconnected buses and bridges, specifically one or more processors represented by processor 300 and various circuits of the memory represented by memory 320 are linked together.
  • the bus architecture can also link together various other circuits such as peripherals, voltage regulators, power management circuits, etc., which are all well known in the art and therefore will not be described further in this disclosure.
  • the bus interface provides the interface.
  • the transceiver 310 may be a plurality of elements, including a transmitter and a receiver, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical cables, and other transmission media.
  • the processor 300 is responsible for managing the bus architecture and general processing, and the memory 320 can store data used by the processor 300 when performing operations.
  • the processor 300 may be a central processing unit (CPU), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field-Programmable Gate Array, FPGA) or a complex programmable logic device (Complex Programmable Logic Device (CPLD), the processor can also adopt a multi-core architecture.
  • CPU central processing unit
  • ASIC Application Specific Integrated Circuit
  • FPGA field programmable gate array
  • CPLD Complex Programmable Logic Device
  • the processor 300 is configured to execute any of the methods provided by the embodiments of the present disclosure according to the obtained executable instructions by calling the computer program stored in the memory 320, for example: determining the target return based on the peak power and sub-peak power of the target detection window.
  • the fractional times delay in the normalized total delay; the target normalized total delay is used to characterize the transmission delay of the signal detected by the target detection window relative to the multiple of the relevant sequence sample interval; according to the fractional times delay , update the position index value of the peak power; according to the updated position index value of the peak power, determine the offset of the position of the peak power relative to the starting position of the target detection window; according to the offset, determine the TA corresponding to the target detection window estimated value.
  • determine the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined
  • the fractional delay is determined based on the absolute value of the fractional delay and the initial position relationship between the peak power and the sub-peak power.
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined.
  • the absolute value of the fractional delay is determined by the following formula:
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay.
  • determine the absolute value of the fractional time delay based on the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay including:
  • the preset correspondence table includes the preset correspondence between the peak power ratio and the absolute value of the decimal time delay;
  • the absolute value of the fractional time delay is determined based on the index value corresponding to the first peak power ratio that is smaller than the first peak power ratio.
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the piecewise function used to characterize the correlation between the peak power ratio and the absolute value of the fractional time delay.
  • the absolute value of the fractional delay is determined by the following formula:
  • determine the fractional time delay based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power including:
  • the fractional time delay is determined to be a positive number.
  • update the location index value of the peak power based on the fractional delay including:
  • the position index value of the peak power is updated based on the sum of the initial position index value of the peak power and the fractional time delay.
  • the method before determining the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window, the method also includes:
  • the sub-peak power is determined based on the maximum value of the power of the two nearest neighbor sample points on the left and right.
  • Figure 4 is a schematic structural diagram of a TA estimation device provided by an embodiment of the present disclosure.
  • the device can be applied to network equipment. As shown in Figure 4, the device includes:
  • the first determination unit 400 is used to determine the fractional multiple of the target normalized total delay according to the peak power and sub-peak power of the target detection window; the target normalized total delay is used to characterize the target detection window.
  • the transmission delay of the detected signal is a multiple of the sample interval of the relevant sequence;
  • the update unit 410 is used to update the location index value of the peak power according to the fractional time delay
  • the second determination unit 420 is configured to determine the offset of the position of the peak power relative to the starting position of the target detection window according to the updated position index value of the peak power;
  • the third determination unit 430 is used to determine the TA estimation value corresponding to the target detection window according to the offset.
  • determine the fractional multiple of the target normalized total delay based on the peak power and sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined
  • the fractional delay is determined based on the absolute value of the fractional delay and the initial position relationship between the peak power and the sub-peak power.
  • determine the absolute value of the fractional time delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined.
  • the absolute value of the fractional delay is determined by the following formula:
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay.
  • determine the absolute value of the fractional time delay based on the first peak power ratio and the preset correspondence between the peak power ratio and the absolute value of the fractional time delay including:
  • the preset correspondence table includes the preset correspondence between the peak power ratio and the absolute value of the decimal time delay;
  • the absolute value of the fractional time delay is determined based on the index value corresponding to the first peak power ratio that is smaller than the first peak power ratio.
  • determine the absolute value of the fractional multiple of the delay based on the first peak power ratio between the peak power and the sub-peak power of the target detection window including:
  • the absolute value of the fractional time delay is determined according to the first peak power ratio and the piecewise function used to characterize the correlation between the peak power ratio and the absolute value of the fractional time delay.
  • the absolute value of the fractional delay is determined by the following formula:
  • determine the fractional time delay based on the absolute value of the fractional time delay and the initial position relationship between the peak power and the sub-peak power including:
  • the fractional time delay is determined to be a positive number.
  • update the location index value of the peak power based on the fractional delay including:
  • the position index value of the peak power is updated based on the sum of the initial position index value of the peak power and the fractional time delay.
  • the first determining unit 400 is also used to:
  • the sub-peak power is determined based on the maximum value of the power of the two nearest neighbor sample points on the left and right.
  • each functional unit in various embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above integrated units can be implemented in the form of hardware or software functional units.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a processor-readable storage medium.
  • the technical solution of the present disclosure is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to cause a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present disclosure.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code. .
  • embodiments of the present disclosure also provide a computer-readable storage medium that stores a computer program, and the computer program is used to cause the computer to execute the TA estimation method provided by the above embodiments.
  • the computer-readable storage medium may be any available media or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor memories (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid state drive (SSD)), etc.
  • magnetic storage such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.
  • optical storage such as CD, DVD, BD, HVD, etc.
  • semiconductor memories such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid state drive (SSD)
  • GSM global system of mobile communication
  • CDMA code division multiple access
  • WCDMA wideband code division multiple access
  • GPRS general packet Wireless service
  • LTE long term evolution
  • FDD frequency division duplex
  • TDD LTE time division duplex
  • UMTS Universal mobile telecommunication system
  • WiMAX microwave access
  • 5G New Radio, NR 5G New Radio
  • EPS Evolved Packet System
  • 5GS 5G system
  • EPS Evolved Packet System
  • 5GS 5G system
  • the terminal involved in the embodiments of the present disclosure may be a device that provides voice and/or data connectivity to users, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem, etc.
  • the name of the terminal may be different.
  • the terminal may be called user equipment (User Equipment, UE).
  • Wireless terminal equipment can communicate with one or more core networks (Core Network, CN) via the Radio Access Network (RAN).
  • the wireless terminal equipment can be a mobile terminal equipment, such as a mobile phone (also known as a "cell phone").
  • Wireless terminal equipment can also be called a system, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, and an access point.
  • remote terminal equipment remote terminal equipment
  • access terminal equipment access terminal
  • user terminal user terminal
  • user agent user agent
  • user device user device
  • the network device involved in the embodiment of the present disclosure may be a base station, and the base station may include multiple cells that provide services for terminals.
  • a base station can also be called an access point, or it can be a device in the access network that communicates with wireless terminal equipment through one or more sectors on the air interface, or it can be named by another name.
  • Network equipment can be used to exchange received air frames with Internet Protocol (IP) packets and act as a router between the wireless terminal equipment and the rest of the access network, which can include the Internet. Protocol (IP) communication network.
  • IP Internet Protocol
  • Network devices also coordinate attribute management of the air interface.
  • the network equipment involved in the embodiments of the present disclosure may be a network equipment (Base Transceiver Station, BTS) in the Global System for Mobile communications (GSM) or Code Division Multiple Access (CDMA). ), or it can be a network device (NodeB) in a Wide-band Code Division Multiple Access (WCDMA), or an evolutionary network device in a long term evolution (LTE) system (evolutional Node B, eNB or e-NodeB), 5G base station (gNB) in the 5G network architecture (next generation system), or home evolved base station (Home evolved Node B, HeNB), relay node (relay node) , home base station (femto), pico base station (pico), etc., are not limited in the embodiments of the present disclosure.
  • network equipment may include centralized unit (CU) nodes and distributed unit (DU) nodes.
  • the centralized units and distributed units may also be arranged geographically separately.
  • MIMO transmission can be single-user MIMO (Single User MIMO, SU-MIMO) or multi-user MIMO ( Multiple User MIMO,MU-MIMO).
  • MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO or massive-MIMO, or it can be diversity transmission, precoding transmission or beamforming transmission, etc.
  • embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) embodying computer-usable program code therein.
  • a computer-usable storage media including, but not limited to, magnetic disk storage, optical storage, and the like
  • processor-executable instructions may also be stored in a processor-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the generation of instructions stored in the processor-readable memory includes the manufacture of the instruction means product, the instruction device implements the function specified in one process or multiple processes in the flow chart and/or one block or multiple blocks in the block diagram.
  • processor-executable instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby causing the computer or other programmable device to
  • the instructions that are executed provide steps for implementing the functions specified in a process or processes of the flowchart diagrams and/or a block or blocks of the block diagrams.

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Abstract

本公开实施例提供一种TA估计方法、网络设备、装置及存储介质，该方法包括：根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；目标归一化总时延用于表征目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；根据小数倍时延，更新峰值功率的位置索引值；根据更新后的峰值功率的位置索引值，确定峰值功率的位置相对于目标检测窗起始位置的偏移量；根据偏移量，确定目标检测窗对应的TA估计值。通过小数倍时延调整峰值功率的位置，根据调整后更加精细的峰值功率位置估计TA，不仅可以提升TA估计的准确度，且不需要通过对数据补0等方法提升相关序列时域分辨率，避免了由此带来的功率弥散问题。

Description

TA估计方法、网络设备、装置及存储介质
相关申请的交叉引用
本申请要求于2022年03月21日提交的申请号为2022102839148，发明名称为“TA估计方法、网络设备、装置及存储介质”的中国专利申请的优先权，其通过引用方式全部并入本文。
技术领域
本公开涉及无线通信技术领域，尤其涉及一种TA估计方法、网络设备、装置及存储介质。
背景技术
物理随机接入信道(Physical Random Access Channel，PRACH)用于完成终端(也称用户设备(User Equipment，UE))与网络设备(例如基站)间的上行同步，为随机接入过程中发送的第一个上行信号(msg1)。网络设备通过接收到的PRACH信号估计终端和网络设备之间的信号传输时延，计算上行发送时间提前量(Timing Advance，TA)发送给终端。终端收到TA后，在根据下行定时得到的上行定时基础上将物理上行共享信道(Physical Uplink Shared Channel，PUSCH)的发送时间提前TA，即可保证PUSCH在网络设备期望的接收时刻前后到达。同一小区内所有终端均按照这个过程完成上行同步，这样无论每个终端和网络设备之间的距离多远，其发送的上行信号基本可以同步到达网络设备。如果网络设备估计的TA误差较大，一方面会影响终端在发送PRACH之后发送的其它上行信号的解调性能，另一方面会导致不同终端的信号时间上不同步，相互之间产生干扰。因此，TA估计的准确性非常重要。
现有技术中，根据相关峰值位置估计TA，估计准确度取决于相关序列的时域分辨率。目前常用的提升相关序列时域分辨率的方法是通过频域数据补0来增大快速傅里叶逆变换(Inverse Fast Fourier Transform，IFFT)点数，但这在提高时域分辨率的同时会造成相关序列的功率弥散，即相关峰值功率会 分散到左右相邻样点上，补0的个数越多，峰值功率弥散越严重，峰值功率与其他样点功率的比值越小，而接收信号中通常会叠加噪声及干扰，这样有可能会出现峰值位置选错的情况，导致TA估计误差较大。如果频域数据不补0，则相关峰值位置不够精细，同样会导致TA估计误差较大。
发明内容
本公开实施例提供一种TA估计方法、网络设备、装置及存储介质，以提升TA估计的准确度。
第一方面，本公开实施例提供一种时间提前量TA估计方法，包括：
根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
根据所述小数倍时延，更新所述峰值功率的位置索引值；
根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
根据所述偏移量，确定所述目标检测窗对应的TA估计值。
可选地，所述根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值；
根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及所述目标检测窗对应的ZC根序列的长度，确定所述小数倍时延的绝对值。
可选地，所述小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000001
式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值，N表示所述目标检测窗对应的ZC根序列的长度。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值。
可选地，所述根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值，包括：
按照峰值功率比值从大到小的顺序，依次将所述第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定所述预设对应关系表中小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，所述预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
根据所述小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定所述小数倍时延的绝对值。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定所述小数倍时延的绝对值。
可选地，所述小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000002
式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值。
可选地，所述根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延，包括：
在所述次峰值功率的初始位置索引值小于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为负数；或者，
在所述次峰值功率的初始位置索引值大于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为正数。
可选地，所述根据所述小数倍时延，更新所述峰值功率的位置索引值，包括：
根据所述峰值功率的初始位置索引值和所述小数倍时延之和，更新所述峰值功率的位置索引值。
可选地，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，所述方法还包括：
确定与所述峰值功率的初始位置左、右最近邻的两个样点位置的功率；
根据所述左、右最近邻的两个样点位置的功率中的最大值，确定所述次峰值功率。
第二方面，本公开实施例还提供一种网络设备，包括存储器，收发机，处理器：
存储器，用于存储计算机程序；收发机，用于在所述处理器的控制下收发数据；处理器，用于读取所述存储器中的计算机程序并执行以下操作：
根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
根据所述小数倍时延，更新所述峰值功率的位置索引值；
根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
根据所述偏移量，确定所述目标检测窗对应的时间提前量TA估计值。
可选地，所述根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值；
根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及所述目标检测窗对应的ZC根序列的长度，确定所述小数倍时延的绝对值。
可选地，所述小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000003
式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值，N表示所述目标检测窗对应的ZC根序列的长度。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值。
可选地，所述根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值，包括：
按照峰值功率比值从大到小的顺序，依次将所述第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定所述预设对应关系表中小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，所述预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
根据所述小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定所述小数倍时延的绝对值。
可选地，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
根据所述第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定所述小数倍时延的绝对值。
可选地，所述小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000004
式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值 功率比值。
可选地，所述根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延，包括：
在所述次峰值功率的初始位置索引值小于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为负数；或者，
在所述次峰值功率的初始位置索引值大于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为正数。
可选地，所述根据所述小数倍时延，更新所述峰值功率的位置索引值，包括：
根据所述峰值功率的初始位置索引值和所述小数倍时延之和，更新所述峰值功率的位置索引值。
可选地，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，所述操作还包括：
确定与所述峰值功率的初始位置左、右最近邻的两个样点位置的功率；
根据所述左、右最近邻的两个样点位置的功率中的最大值，确定所述次峰值功率。
第三方面，本公开实施例还提供一种时间提前量TA估计装置，包括：
第一确定单元，用于根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
更新单元，用于根据所述小数倍时延，更新所述峰值功率的位置索引值；
第二确定单元，用于根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
第三确定单元，用于根据所述偏移量，确定所述目标检测窗对应的TA估计值。
第四方面，本公开实施例还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序用于使计算机执行如上所述第一方面所述的TA估计方法的步骤。
第五方面，本公开实施例还提供一种通信设备，所述通信设备中存储有计算机程序，所述计算机程序用于使通信设备执行如上所述第一方面所述的TA估计方法的步骤。
第六方面，本公开实施例还提供一种处理器可读存储介质，所述处理器可读存储介质存储有计算机程序，所述计算机程序用于使处理器执行如上所述第一方面所述的TA估计方法的步骤。
第七方面，本公开实施例还提供一种芯片产品，所述芯片产品中存储有计算机程序，所述计算机程序用于使芯片产品执行如上所述第一方面所述的TA估计方法的步骤。
本公开实施例提供的TA估计方法、网络设备、装置及存储介质，通过根据峰值功率和次峰值功率确定小数倍时延，再根据小数倍时延调整峰值功率的位置，根据调整后更加精细的峰值功率位置来进行TA估计，不仅可以提升TA估计的准确度，且不需要通过对数据补0等方法提升相关序列时域分辨率，可以避免由此带来的功率弥散问题。
附图说明
为了更清楚地说明本公开实施例或相关技术中的技术方案，下面将对实施例或相关技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本公开实施例提供的TA估计方法的流程示意图；
图2是本公开实施例提供的峰值功率比值随小数倍时延绝对值变化的曲线图；
图3是本公开实施例提供的网络设备的结构示意图；
图4是本公开实施例提供的TA估计装置的结构示意图。
具体实施方式
本公开实施例中术语“和/或”，描述关联对象的关联关系，表示可以存 在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。
本公开实施例中术语“多个”是指两个或两个以上，其它量词与之类似。
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本公开一部分实施例，并不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
为了便于更加清晰地理解本公开各实施例的技术方案，首先对本公开各实施例相关的一些技术内容进行介绍。
4G长期演进(Long Term Evolution，LTE)与5G新空口(New Radio，NR)系统均采用正交频分复用多址(Orthogonal Frequency Division Multiple Access，OFDMA)技术，为保证小区内不同终端信号之间的正交性，避免终端间干扰，引入了上行定时同步过程，每个终端的上行信号发送时间提前量TA应该等于该终端和基站间信号单程传输时延T P的2倍，基站通过每个终端发送的PRACH来估计该终端的TA。
NR系统的PRACH由循环前缀CP、Zadoff-Chu(ZC)序列(即preamble序列)和保护间隔GT三部分组成，PRACH所用的ZC序列具有良好的自相关和互相关特性，因此可以采用序列相关的方法对接收到的PRACH信号进行检测，并估计TA。
以下提供一种TA估计方法的主要流程：
Step1：从接收的PRACH时域信号中提取preamble序列，去掉CP和GT部分。
Step2：用接收preamble序列与ZC根序列做相关，并计算相关序列中每个样点的功率。序列相关可以用FFT&IFFT实现，可以通过频域补0增加IFFT点数的方式提高相关序列的时域分辨率。
Step3：将相关序列划分为若干个检测窗，在每个检测窗内搜索功率最大的样点(即相关峰值)，计算相关峰值位置相对于其所在检测窗起始位置的偏 移量Δ pos，其中检测窗起始位置为信号传输时延为0时对应的相关峰值位置。
Step4：将相关峰值位置偏移量Δ pos按下式折算为TA。
Figure PCTCN2022125907-appb-000005
上式中，TA float表示TA估计值，Δf RA为PRACH子载波间隔，N IFFT为序列相关过程中IFFT点数，N IFFT≥L RA，L RA指ZC序列长度，u为PUSCH的子载波间隔指数。
基站实际发给终端的TA为整数，因此需要对以上浮点结果TA float进行取整，取整方式可以为下取整或者四舍五入。
根据相关峰值位置估计TA，估计准确度取决于相关序列的时域分辨率，即，相关序列相邻2个样点的时间间隔
Figure PCTCN2022125907-appb-000006
Δt越小，则时域分辨率越高。在有较强直射径的信道环境中，多径分量较少，信号传输时延基本等于直射径时延，相关序列一般只有一个较大峰值，根据峰值位置计算的信号传输时延与直射径时延之间的差值最大为
Figure PCTCN2022125907-appb-000007
因此，减小Δt，提高相关序列时域分辨率，可以使相关峰值位置更接近直射径时延，使TA估计更加准确。
常用的提升相关序列时域分辨率的方法是通过频域数据补0来增大IFFT点数N IFFT，但这在提高时域分辨率的同时会造成相关序列的功率弥散，即，相关峰值功率会分散到左右相邻样点上，补0的个数越多，峰值功率弥散越严重，峰值功率与其他样点功率的比值越小，而接收信号中通常会叠加噪声及干扰，这样有可能会出现峰值位置选错的情况，导致TA估计误差较大。
如果频域数据不补0，直接做L RA点离散傅里叶逆变换(Inverse Discrete Fourier Transform，IDFT)，不会存在上述功率弥散问题，但是此时
Figure PCTCN2022125907-appb-000008
较大，相关峰值位置不够精细，估计的信号传输时延与真实的直射径时延之间的偏差可能会较大，这样TA估计误差也较大。
针对上述问题，本公开各实施例提供一种解决方案，根据相关峰值与左右相邻的次峰值功率的比值以及相关峰值与次峰值的位置关系准确计算出归一化总时延中的小数倍时延，从而精确估计TA。而且，由于可以准确得到小 数倍时延，所以即便不提高相关序列的时域分辨率，也可以根据小数倍时延得到更加精细的相关峰值位置，从而避免了通过对频域数据补0等方法提升相关序列的时域分辨率时所带来的功率弥散问题。
以下对本公开各实施例提供的技术方案的思想进行介绍。
有时延时ZC序列相关功率理论表达式如下：
Figure PCTCN2022125907-appb-000009
上式中，N为ZC序列长度，n+n 0为归一化总时延，即，信号时延相对于ZC序列样点间隔的倍数，其中n为非负整数，表示的是归一化总时延中的整数倍时延，n 0为-0.5～0.5之间的小数，表示的是归一化总时延中的小数倍时延。
如果n 0＝0，上式只在m＝n处有一个非零值，m取其它值处均为0。如果n 0≠0，上式在m＝n-1、n或n+1处出现极大值，m等于其它值处|R(m)| 2也有非零值，此时ZC序列相关功率发生弥散，但弥散的功率主要分布在峰值左右相邻样点上，距离峰值越远的样点上弥散的功率越小。以下为n 0≠0时，m＝n-1、n和n+1处的相关功率值。
Figure PCTCN2022125907-appb-000010
Figure PCTCN2022125907-appb-000011
Figure PCTCN2022125907-appb-000012
如果0<n 0≤0.5，|R(n)| 2≥|R(n+1)| 2>|R(n-1)| 2，峰值功率与次峰值功率比值
Figure PCTCN2022125907-appb-000013
由此可以计算出小数倍时延
Figure PCTCN2022125907-appb-000014
再将相关峰值位置n替换为n+n 0用来计算TA。
如果-0.5≤n 0<0，|R(n)| 2≥|R(n-1)| 2>|R(n+1)| 2，峰值功率与次峰值功率比值
Figure PCTCN2022125907-appb-000015
由此可以计算出小数倍时延
Figure PCTCN2022125907-appb-000016
再将相关峰值位 置n替换为n+n 0用来计算TA。
综合以上两种情况可以看出，本公开各实施例提供的TA估计方案，不需要通过补0增大IFFT点数来提升相关序列时域分辨率，只要利用N点相关功率数据，根据相关峰值与左右相邻的次峰值功率的比值以及相关峰值与次峰值的位置关系即可准确计算出小数倍时延n 0，将相关峰值位置n替换为n+n 0，得到更加精细的相关峰值位置，从而精确估计TA。
图1为本公开实施例提供的TA估计方法的流程示意图，该方法可应用于网络设备(例如基站)，如图1所示，该方法包括如下步骤：
步骤100、根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；目标归一化总时延用于表征目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数。
具体地，网络设备在接收到任一终端发送的PRACH后，从接收的PRACH时域信号中提取preamble序列，用接收的preamble序列与ZC根序列做相关，并计算相关序列中每个样点的功率。相关序列划分为若干个检测窗，对于该终端对应的目标检测窗，网络设备可以根据该目标检测窗的峰值功率(即检测窗的各样点功率中的最大值)和次峰值功率(即检测窗的各样点功率中的第二大值)，确定目标归一化总时延中的小数倍时延，也即前文所述的n 0。例如，可以根据峰值功率和次峰值功率之间的比值，以及峰值功率与次峰值功率之间的相对位置关系，通过前文所述的公式得到n 0的值。
可选地，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，该方法还包括：
确定与峰值功率的初始位置左、右最近邻的两个样点位置的功率；
根据左、右最近邻的两个样点位置的功率中的最大值，确定次峰值功率。
具体地，根据前文所述，如果n 0＝0，ZC序列相关功率只有一个非零值，该非零值即为相关峰值，此时可以直接根据相关峰值的位置计算相关峰值位置相对于其所在检测窗起始位置的偏移量Δ pos，进而得到TA估计值。而如果n 0≠0，ZC序列相关功率会发生弥散，即会出现多个非零值，弥散的功率主要分布在峰值左右相邻样点上，距离峰值越远的样点上弥散的功率越小，因 此次峰值功率通常出现在离峰值功率的位置最近的左边或右边样点位置上。
本公开实施例中，在确定次峰值功率时，可以先确定与峰值功率的初始位置左、右最近邻的两个样点位置的功率，再比较这两个样点位置的功率，将其中更大的功率作为次峰值功率。例如，峰值功率的初始位置为n，其左边最近邻的样点位置为n-1，其右边最近邻的样点位置为n+1，则可以分别获取n-1位置处和n+1位置处的样点功率，然后，比较这两个位置处的样点功率，取其中更大的一个样点功率作为次峰值功率。仅比较与峰值功率的初始位置左、右最近邻的两个样点位置的功率即可确定次峰值功率，大大减少了运算量。
步骤101、根据小数倍时延，更新峰值功率的位置索引值。
具体地，确定n 0的值之后，便可以根据n 0的值更新峰值功率的位置索引值，使得用于估计TA的相关峰值位置更加精细和准确。
可选地，根据小数倍时延，更新峰值功率的位置索引值，可以包括：根据峰值功率的初始位置索引值和小数倍时延之和，更新峰值功率的位置索引值。例如，假设峰值功率的初始位置索引值为n，在确定小数倍时延n 0的值之后，可以将峰值功率的初始位置索引值n加上n 0，作为更新后的峰值功率的位置索引值，也即用n+n 0替换n进行TA估计。
步骤102、根据更新后的峰值功率的位置索引值，确定峰值功率的位置相对于目标检测窗起始位置的偏移量。
具体地，更新峰值功率的位置索引值之后，可以根据更新后的峰值功率的位置索引值，来计算峰值功率的位置相对于其所在目标检测窗起始位置的偏移量。例如，峰值功率的初始位置索引值为n，更新后峰值功率的位置索引值为n+n 0，目标检测窗起始位置的索引值为x，则可以将n+n 0和x之间的差值作为峰值功率的位置相对于其所在目标检测窗起始位置的偏移量。
步骤103、根据偏移量，确定目标检测窗对应的TA估计值。
具体地，确定峰值功率的位置相对于目标检测窗起始位置的偏移量之后，便可以根据该偏移量，计算该目标检测窗对应的TA估计值，后续可以将估计的TA值取整后发送给该目标检测窗对应的终端。
一种可能的实现方式中，可以根据以下公式计算目标检测窗对应的TA估计值：
Figure PCTCN2022125907-appb-000017
式中，TA float表示目标检测窗对应的TA估计值，Δ pos表示上述确定的偏移量，N IFFT表示目标检测窗对应的序列相关过程中IFFT点数，Δf RA表示目标检测窗对应的PRACH子载波间隔，u表示目标检测窗对应的终端发送PUSCH的子载波间隔指数。
本公开实施例提供的TA估计方法，通过根据峰值功率和次峰值功率确定小数倍时延，再根据小数倍时延调整峰值功率的位置，根据调整后更加精细的峰值功率位置来进行TA估计，不仅可以提升TA估计的准确度，且不需要通过对数据补0等方法提升相关序列时域分辨率，可以避免由此带来的功率弥散问题。
可选地，根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值；
根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的初始位置关系，确定小数倍时延。
具体地，本公开实施例中，确定小数倍时延时，可以先根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，例如，可以将目标检测窗的峰值功率除以次峰值功率得到第一峰值功率比值，根据该第一峰值功率比值，通过理论计算、查表、分段函数近似或加权平均近似等多种方法得到小数倍时延的绝对值。
然后，根据峰值功率和次峰值功率之间的初始位置关系确定小数倍时延的符号，最终得到小数倍时延的值。
通过先确定小数倍时延的绝对值，再根据峰值功率和次峰值功率的相对 位置关系确定小数倍时延的符号，使得确定小数倍时延的方式可以更加灵活多样，从而提升了TA估计的灵活性，有利于简单快速地进行TA估计。
可选地，根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的初始位置关系，确定小数倍时延，包括：
在次峰值功率的初始位置索引值小于峰值功率的初始位置索引值的情况下，确定小数倍时延为负数；或者，
在次峰值功率的初始位置索引值大于峰值功率的初始位置索引值的情况下，确定小数倍时延为正数。
可以理解，在n 0≠0的情况下，ZC序列相关功率会发生弥散，弥散的功率主要分布在峰值左右相邻样点上，距离峰值越远的样点上弥散的功率越小，因此次峰值功率通常出现在离峰值功率的位置最近的左边或右边样点位置上，n 0<0时，次峰值功率的位置在峰值功率的位置左边，n 0＞0时，次峰值功率的位置在峰值功率的位置右边，故而可以根据峰值功率和次峰值功率的相对位置关系确定n 0为正数还是负数。
本公开实施例中，可以通过比较峰值功率的初始位置索引值和次峰值功率的初始位置索引值，确定峰值功率和次峰值功率的相对位置关系，从而确定小数倍时延的正负号。例如，若次峰值功率的初始位置索引值小于峰值功率的初始位置索引值，表明次峰值功率的初始位置在峰值功率的初始位置左边，则可以确定小数倍时延为负数；若次峰值功率的初始位置索引值大于峰值功率的初始位置索引值，表明次峰值功率的初始位置在峰值功率的初始位置右边，则可以确定小数倍时延为正数。通过位置索引值判断峰值功率和次峰值功率的相对位置关系，可以准确地确定小数倍时延的符号，且实现简单。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及目标检测窗对应的ZC根序列的长度，确定小数倍时延的绝对值。
具体地，本公开实施例中，可以根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，以及目标检测窗对应的ZC根序列的长度，确定 小数倍时延的绝对值。从前文所述可以看出，小数倍时延、峰值功率比值以及ZC根序列长度三者之间存在一定的函数关系，因此可以根据三者之间的函数关系，在确定峰值功率比值以及ZC根序列长度之后，计算出小数倍时延的绝对值，从而可以通过理论计算得到最为准确的小数倍时延计算结果。
可选地，小数倍时延的绝对值可以通过以下公式确定：
Figure PCTCN2022125907-appb-000018
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值，N表示目标检测窗对应的ZC根序列的长度。
具体地，峰值功率和次峰值功率比值peak ratio与小数倍时延绝对值|n 0|之间的函数关系理论表达式分别如下：
Figure PCTCN2022125907-appb-000019
Figure PCTCN2022125907-appb-000020
因此，找到峰值功率和次峰值功率，计算得到峰值功率比值peak ratio之后，可以先代入上式计算得到小数倍时延的绝对值|n 0|，然后根据峰值功率和次峰值功率之间的相对位置关系，确定n 0的正负号，进而确定n 0的值。
在确定峰值功率比值以及ZC根序列长度之后，代入预设的|n 0|理论计算公式，可以快速得到准确的小数倍时延计算结果。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值。
具体地，本公开实施例中，可以预先设置不同的峰值功率比值和小数倍时延绝对值之间的对应关系，从而在得到目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值之后，可以根据峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定该第一峰值功率比值所对应的小数倍时延的绝对值。
通过预设峰值功率比值和小数倍时延绝对值之间的对应关系，在得到目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值之后，可以快速地根据预设对应关系得到第一峰值功率比值所对应的小数倍时延的绝对值，从而提升了TA估计的效率。
一种可能的实现方式中，预设对应关系可以是通过预设对应关系表的形式体现。比如可以根据前文所述的小数倍时延绝对值的理论计算公式，计算得到不同峰值功率比值所对应的小数倍时延的绝对值，然后将不同峰值功率比值对应的小数倍时延绝对值预存在表格中。当然，峰值功率比值和小数倍时延绝对值之间的预设对应关系也可以是以其他方式体现，在此并不限制。
峰值功率比值和小数倍时延绝对值之间的预设对应关系以预设对应关系表的形式体现时，可以预存峰值功率和次峰值功率之间的峰值功率比值vs小数倍时延绝对值的表格，计算得到第一峰值功率比值之后，查表得到对应的小数倍时延绝对值|n 0|，再根据峰值功率和次峰值功率的相对位置关系确定n 0的正负号。其中，查表方法可以有多种，比如可以用第一峰值功率比值左右边界对应的|n 0|的均值作为查表返回的值，也可以是直接返回左边界或者右边界对应的|n 0|的值，还可以是其它的处理方法。
以下面的表1为例，ZC根序列长度N＝839，小数倍时延绝对值的颗粒度为0.01(为保证小数倍时延估计精度，表格中小数倍时延绝对值的颗粒度可以设置的小一点)，每个小数倍时延绝对值对应一个峰值功率比值，表格中总共有0.5/0.01*2＝100个数值。假设根据目标检测窗的峰值功率和次峰值功率得到第一峰值功率比值为2000，则在进行查表时，可以看出，2000落在1045.44和2400.99之间，峰值功率比值1045.44对应的小数倍时延绝对值为0.03，峰值功率比值2400.99对应的小数倍时延绝对值为0.02，那么，查表时可以用2000左右边界对应的小数倍时延绝对值的均值(即(0.02+0.03)/2＝0.025)作为查表返回的值，也可以是直接返回左边界或者右边界对应的小数倍时延绝对值，即0.03或者0.02。
表1小数倍时延绝对值与峰值功率比值对照表
Figure PCTCN2022125907-appb-000021
Figure PCTCN2022125907-appb-000022
可选地，根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值，包括：
按照峰值功率比值从大到小的顺序，依次将第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定预设对应关系表中小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
根据小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定小数倍时延的绝对值。
一种可能的实现方式中，基于预设对应关系表确定小数倍时延的绝对值，可以先按照峰值功率比值从大到小的顺序，依次将第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定预设对应关系表中小于该第一峰值功率比值的第1个峰值功率比值所对应的索引值。其中，预设对应关系中，索引值可以按照小数倍时延绝对值从小到大的顺序依次增加，也可以按照小数倍时延绝对值从大到小的顺序依次增加，也可以是与小数倍时延绝对值之间有其他的对应关系，在此并不限制。
以表1为例，假设表中每一组小数倍时延绝对值-峰值功率比值对应一个 索引值，且索引值按照小数倍时延绝对值从小到大的顺序依次增加，比如0.01-9800.96对应索引值1，0.02-2400.99对应索引值2，…，0.50-1.00对应索引值50，假设根据目标检测窗的峰值功率和次峰值功率得到第一峰值功率比值为2000，那么可以确定表1中小于该第一峰值功率比值的第1个峰值功率比值为1045.44，其所对应的索引值为3，然后可以根据该索引值确定该第一峰值功率比值所对应的小数倍时延绝对值。例如，可以将索引值3对应的小数倍时延绝对值0.03作为该第一峰值功率比值所对应的小数倍时延绝对值，也可以将索引值3对应的小数倍时延绝对值和索引值2对应的小数倍时延绝对值求取平均值作为该第一峰值功率比值所对应的小数倍时延绝对值，还可以是其他的处理方法。通过索引值获取对应的小数倍时延绝对值，可以有效提升查表效率。
可选地，小数倍时延的绝对值可以通过以下公式确定：
Figure PCTCN2022125907-appb-000023
式中，|n 0|表示小数倍时延n 0的绝对值，index表示小于功率比值的第1个峰值功率比值所对应的索引值，L表示预设对应关系表中小数倍时延绝对值的个数，table(index-1,1)和table(index,1)分别表示预设对应关系表中索引值index-1和索引值index所对应的小数倍时延绝对值；该预设对应关系表中，索引值按照小数倍时延绝对值从小到大的顺序依次增加。
仍以上述表1为例，将表格中所存数据记作矩阵table，其维度为L*2，L为表1中小数倍时延绝对值的个数，table(index,1)返回的是索引值index对应的小数倍时延绝对值。在确定第一峰值功率比值(仍以2000为例)之后，可以将第一峰值功率比值与表1中的峰值功率比值从第1个开始依次进行比较，找到表1中小于第一峰值功率比值的第1个峰值功率比值的索引值index，为3，那么，可以将table(2,1)和table(3,1)返回的小数倍时延绝对值求取平均值，即(0.02+0.03)/2＝0.025，便可以输出第一峰值功率比值2000所对应的小数倍时延的绝对值0.025。通过求取平均值的方式，可以使得查表得到的结 果更加接近理论计算值。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定小数倍时延的绝对值。
具体地，本公开实施例中，可以预先设置用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，分段函数可以通过对峰值功率比值与小数倍时延绝对值之间的函数关系理论表达式进行分段近似得到，从而可以将复杂的计算表达式近似为简单的线性函数，在计算小数倍时延的绝对值时可以有效减少运算量。
一种可能的实现方式中，可以先根据峰值功率比值与小数倍时延绝对值之间的函数关系理论表达式，计算不同的小数倍时延绝对值对应的峰值功率比值，图2为本公开实施例提供的峰值功率比值随小数倍时延绝对值变化的曲线图，如图2所示，图中曲线是以小数倍时延绝对值为横坐标、峰值与次峰值功率比值(即峰值功率和次峰值功率之间的峰值功率比值)为纵坐标所画出的理论曲线，也可以将横坐标和纵坐标交换，即以小数倍时延绝对值为纵坐标、峰值功率比值为横坐标，再用分段函数的多个折线来近似理论曲线，即可得到分段函数的曲线，分段函数曲线的每一段都为直线段，对应分段函数的每一段都为简单的线性函数。
可选地，本公开实施例提供一种分段函数的表达式，小数倍时延的绝对值可以通过以下公式确定：
Figure PCTCN2022125907-appb-000024
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值。 将根据目标检测窗的峰值功率和次峰值功率计算出来的第一峰值功率比值代入以上分段函数表达式中即可得到对应的小数倍时延的绝对值|n 0|，再根据峰值功率和次峰值功率的相对位置关系便可以确定n 0的值。
可选地，小数倍时延的绝对值还可以通过以下公式确定：
Figure PCTCN2022125907-appb-000025
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值。
具体地，本公开实施例提供一种确定小数倍时延的绝对值的方法，其本质是将峰值位置和次峰值位置分别用各自的功率值进行加权平均，用平均后的结果作为更新的峰值位置来计算TA。推导如下：
假设峰值位置为n，次峰值位置为n-1或n+1，峰值功率和次峰值功率分别为P max和P sub，那么更新的峰值位置为：
Figure PCTCN2022125907-appb-000026
所以n 0＝n update-n，
Figure PCTCN2022125907-appb-000027
通过这种方法，可以进一步简化运算，减少计算资源的消耗，提升TA估计的效率。
本公开各实施例提供的方法和装置是基于同一申请构思的，由于方法和装置解决问题的原理相似，因此装置和方法的实施可以相互参见，重复之处不再赘述。
图3为本公开实施例提供的网络设备的结构示意图，如图3所示，该网络设备包括存储器320，收发机310和处理器300；其中，处理器300与存储器320也可以物理上分开布置。
存储器320，用于存储计算机程序；收发机310，用于在处理器300的控制下收发数据。
具体地，收发机310用于在处理器300的控制下接收和发送数据。
其中，在图3中，总线架构可以包括任意数量的互联的总线和桥，具体由处理器300代表的一个或多个处理器和存储器320代表的存储器的各种电 路链接在一起。总线架构还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路链接在一起，这些都是本领域所公知的，因此，本公开不再对其进行进一步描述。总线接口提供接口。收发机310可以是多个元件，即包括发送机和接收机，提供用于在传输介质上与各种其他装置通信的单元，这些传输介质包括无线信道、有线信道、光缆等传输介质。
处理器300负责管理总线架构和通常的处理，存储器320可以存储处理器300在执行操作时所使用的数据。
处理器300可以是中央处理器(Central Processing Unit,CPU)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field－Programmable Gate Array，FPGA)或复杂可编程逻辑器件(Complex Programmable Logic Device，CPLD)，处理器也可以采用多核架构。
处理器300通过调用存储器320存储的计算机程序，用于按照获得的可执行指令执行本公开实施例提供的任一所述方法，例如：根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；目标归一化总时延用于表征目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；根据小数倍时延，更新峰值功率的位置索引值；根据更新后的峰值功率的位置索引值，确定峰值功率的位置相对于目标检测窗起始位置的偏移量；根据偏移量，确定目标检测窗对应的TA估计值。
可选地，根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值；
根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的初始位置关系，确定小数倍时延。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及目标检测窗对应的ZC根序列的长度，确定小数倍时延的绝对值。
可选地，小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000028
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值，N表示目标检测窗对应的ZC根序列的长度。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值。
可选地，根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值，包括：
按照峰值功率比值从大到小的顺序，依次将第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定预设对应关系表中小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
根据小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定小数倍时延的绝对值。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定小数倍时延的绝对值。
可选地，小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000029
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值。
可选地，根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的初始位置关系，确定小数倍时延，包括：
在次峰值功率的初始位置索引值小于峰值功率的初始位置索引值的情况下，确定小数倍时延为负数；或者，
在次峰值功率的初始位置索引值大于峰值功率的初始位置索引值的情况下，确定小数倍时延为正数。
可选地，根据小数倍时延，更新峰值功率的位置索引值，包括：
根据峰值功率的初始位置索引值和小数倍时延之和，更新峰值功率的位置索引值。
可选地，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，该方法还包括：
确定与峰值功率的初始位置左、右最近邻的两个样点位置的功率；
根据左、右最近邻的两个样点位置的功率中的最大值，确定次峰值功率。
在此需要说明的是，本公开实施例提供的上述网络设备，能够实现上述方法实施例所实现的所有方法步骤，且能够达到相同的技术效果，在此不再对本实施例中与方法实施例相同的部分及有益效果进行具体赘述。
图4为本公开实施例提供的TA估计装置的结构示意图，该装置可应用于网络设备，如图4所示，该装置包括：
第一确定单元400，用于根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；目标归一化总时延用于表征目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
更新单元410，用于根据小数倍时延，更新峰值功率的位置索引值；
第二确定单元420，用于根据更新后的峰值功率的位置索引值，确定峰值功率的位置相对于目标检测窗起始位置的偏移量；
第三确定单元430，用于根据偏移量，确定目标检测窗对应的TA估计值。
可选地，根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值；
根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的初始位置关系，确定小数倍时延。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率 比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及目标检测窗对应的ZC根序列的长度，确定小数倍时延的绝对值。
可选地，小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000030
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值，N表示目标检测窗对应的ZC根序列的长度。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值。
可选地，根据第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定小数倍时延的绝对值，包括：
按照峰值功率比值从大到小的顺序，依次将第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定预设对应关系表中小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
根据小于第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定小数倍时延的绝对值。
可选地，根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定小数倍时延的绝对值，包括：
根据第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定小数倍时延的绝对值。
可选地，小数倍时延的绝对值通过以下公式确定：
Figure PCTCN2022125907-appb-000031
式中，|n 0|表示小数倍时延n 0的绝对值，peak ratio表示第一峰值功率比值。
可选地，根据小数倍时延的绝对值，以及峰值功率和次峰值功率之间的 初始位置关系，确定小数倍时延，包括：
在次峰值功率的初始位置索引值小于峰值功率的初始位置索引值的情况下，确定小数倍时延为负数；或者，
在次峰值功率的初始位置索引值大于峰值功率的初始位置索引值的情况下，确定小数倍时延为正数。
可选地，根据小数倍时延，更新峰值功率的位置索引值，包括：
根据峰值功率的初始位置索引值和小数倍时延之和，更新峰值功率的位置索引值。
可选地，第一确定单元400还用于：
确定与峰值功率的初始位置左、右最近邻的两个样点位置的功率；
根据左、右最近邻的两个样点位置的功率中的最大值，确定次峰值功率。
需要说明的是，本公开实施例中对单元的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。另外，在本公开各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个处理器可读取存储介质中。基于这样的理解，本公开的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本公开各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
在此需要说明的是，本公开实施例提供的上述装置，能够实现上述方法实施例所实现的所有方法步骤，且能够达到相同的技术效果，在此不再对本实施例中与方法实施例相同的部分及有益效果进行具体赘述。
另一方面，本公开实施例还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序用于使计算机执行上述各实施例提供的TA估计方法。
在此需要说明的是，本公开实施例提供的计算机可读存储介质，能够实现上述方法实施例所实现的所有方法步骤，且能够达到相同的技术效果，在此不再对本实施例中与方法实施例相同的部分及有益效果进行具体赘述。
所述计算机可读存储介质可以是计算机能够存取的任何可用介质或数据存储设备，包括但不限于磁性存储器(例如软盘、硬盘、磁带、磁光盘(MO)等)、光学存储器(例如CD、DVD、BD、HVD等)、以及半导体存储器(例如ROM、EPROM、EEPROM、非易失性存储器(NAND FLASH)、固态硬盘(SSD))等。
本公开实施例提供的技术方案可以适用于多种系统，尤其是5G系统。例如适用的系统可以是全球移动通讯(global system of mobile communication，GSM)系统、码分多址(code division multiple access，CDMA)系统、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)通用分组无线业务(general packet radio service，GPRS)系统、长期演进(long term evolution，LTE)系统、LTE频分双工(frequency division duplex，FDD)系统、LTE时分双工(time division duplex，TDD)系统、高级长期演进(long term evolution advanced，LTE-A)系统、通用移动系统(universal mobile telecommunication system，UMTS)、全球互联微波接入(worldwide interoperability for microwave access，WiMAX)系统、5G新空口(New Radio,NR)系统等。这多种系统中均包括终端设备和网络设备。系统中还可以包括核心网部分，例如演进的分组系统(Evloved Packet System,EPS)、5G系统(5GS)等。
本公开实施例涉及的终端，可以是指向用户提供语音和/或数据连通性的设备，具有无线连接功能的手持式设备、或连接到无线调制解调器的其他处理设备等。在不同的系统中，终端的名称可能也不相同，例如在5G系统中，终端可以称为用户设备(User Equipment，UE)。无线终端设备可以经无线接入网(Radio Access Network,RAN)与一个或多个核心网(Core Network,CN) 进行通信，无线终端设备可以是移动终端设备，如移动电话(或称为“蜂窝”电话)和具有移动终端设备的计算机，例如，可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置，它们与无线接入网交换语言和/或数据。例如，个人通信业务(Personal Communication Service，PCS)电话、无绳电话、会话发起协议(Session Initiated Protocol，SIP)话机、无线本地环路(Wireless Local Loop，WLL)站、个人数字助理(Personal Digital Assistant，PDA)等设备。无线终端设备也可以称为系统、订户单元(subscriber unit)、订户站(subscriber station)，移动站(mobile station)、移动台(mobile)、远程站(remote station)、接入点(access point)、远程终端设备(remote terminal)、接入终端设备(access terminal)、用户终端设备(user terminal)、用户代理(user agent)、用户装置(user device)，本公开实施例中并不限定。
本公开实施例涉及的网络设备，可以是基站，该基站可以包括多个为终端提供服务的小区。根据具体应用场合不同，基站又可以称为接入点，或者可以是接入网中在空中接口上通过一个或多个扇区与无线终端设备通信的设备，或者其它名称。网络设备可用于将收到的空中帧与网际协议(Internet Protocol，IP)分组进行相互更换，作为无线终端设备与接入网的其余部分之间的路由器，其中接入网的其余部分可包括网际协议(IP)通信网络。网络设备还可协调对空中接口的属性管理。例如，本公开实施例涉及的网络设备可以是全球移动通信系统(Global System for Mobile communications，GSM)或码分多址接入(Code Division Multiple Access，CDMA)中的网络设备(Base Transceiver Station，BTS)，也可以是带宽码分多址接入(Wide-band Code Division Multiple Access，WCDMA)中的网络设备(NodeB)，还可以是长期演进(long term evolution，LTE)系统中的演进型网络设备(evolutional Node B，eNB或e-NodeB)、5G网络架构(next generation system)中的5G基站(gNB)，也可以是家庭演进基站(Home evolved Node B，HeNB)、中继节点(relay node)、家庭基站(femto)、微微基站(pico)等，本公开实施例中并不限定。在一些网络结构中，网络设备可以包括集中单元(centralized unit，CU)节点和分布单元(distributed unit，DU)节点，集中单元和分布单元也可 以地理上分开布置。
网络设备与终端之间可以各自使用一或多根天线进行多输入多输出(Multi Input Multi Output,MIMO)传输，MIMO传输可以是单用户MIMO(Single User MIMO,SU-MIMO)或多用户MIMO(Multiple User MIMO,MU-MIMO)。根据根天线组合的形态和数量，MIMO传输可以是2D-MIMO、3D-MIMO、FD-MIMO或massive-MIMO，也可以是分集传输或预编码传输或波束赋形传输等。
本领域内的技术人员应明白，本公开的实施例可提供为方法、系统、或计算机程序产品。因此，本公开可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本公开可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本公开是参照根据本公开实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机可执行指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机可执行指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些处理器可执行指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的处理器可读存储器中，使得存储在该处理器可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些处理器可执行指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
显然，本领域的技术人员可以对本公开进行各种改动和变型而不脱离本公开的精神和范围。这样，倘若本公开的这些修改和变型属于本公开权利要求及其等同技术的范围之内，则本公开也意图包含这些改动和变型在内。

Claims (34)

  1. 一种时间提前量TA估计方法，其特征在于，包括：
    根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
    根据所述小数倍时延，更新所述峰值功率的位置索引值；
    根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
    根据所述偏移量，确定所述目标检测窗对应的TA估计值。
  2. 根据权利要求1所述的TA估计方法，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
    根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值；
    根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延。
  3. 根据权利要求2所述的TA估计方法，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及所述目标检测窗对应的ZC根序列的长度，确定所述小数倍时延的绝对值。
  4. 根据权利要求3所述的TA估计方法，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100001
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值，N表示所述目标检测窗对应的ZC根序列的长度。
  5. 根据权利要求2所述的TA估计方法，其特征在于，所述根据目标检 测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值。
  6. 根据权利要求5所述的TA估计方法，其特征在于，所述根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值，包括：
    按照峰值功率比值从大到小的顺序，依次将所述第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定所述预设对应关系表中小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，所述预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
    根据所述小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定所述小数倍时延的绝对值。
  7. 根据权利要求2所述的TA估计方法，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定所述小数倍时延的绝对值。
  8. 根据权利要求2所述的TA估计方法，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100002
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值。
  9. 根据权利要求2所述的TA估计方法，其特征在于，所述根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延，包括：
    在所述次峰值功率的初始位置索引值小于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为负数；或者，
    在所述次峰值功率的初始位置索引值大于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为正数。
  10. 根据权利要求1至9任一项所述的TA估计方法，其特征在于，所述根据所述小数倍时延，更新所述峰值功率的位置索引值，包括：
    根据所述峰值功率的初始位置索引值和所述小数倍时延之和，更新所述峰值功率的位置索引值。
  11. 根据权利要求1所述的TA估计方法，其特征在于，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，所述方法还包括：
    确定与所述峰值功率的初始位置左、右最近邻的两个样点位置的功率；
    根据所述左、右最近邻的两个样点位置的功率中的最大值，确定所述次峰值功率。
  12. 一种网络设备，其特征在于，包括存储器，收发机，处理器：
    存储器，用于存储计算机程序；收发机，用于在所述处理器的控制下收发数据；处理器，用于读取所述存储器中的计算机程序并执行以下操作：
    根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
    根据所述小数倍时延，更新所述峰值功率的位置索引值；
    根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
    根据所述偏移量，确定所述目标检测窗对应的时间提前量TA估计值。
  13. 根据权利要求12所述的网络设备，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
    根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值；
    根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延。
  14. 根据权利要求13所述的网络设备，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及所述目标检测窗对应的ZC根序列的长度，确定所述小数倍时延的绝对值。
  15. 根据权利要求14所述的网络设备，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100003
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值，N表示所述目标检测窗对应的ZC根序列的长度。
  16. 根据权利要求13所述的网络设备，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值。
  17. 根据权利要求16所述的网络设备，其特征在于，所述根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值，包括：
    按照峰值功率比值从大到小的顺序，依次将所述第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定所述预设对应关系表中小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，所述预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
    根据所述小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定所述小数倍时延的绝对值。
  18. 根据权利要求13所述的网络设备，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定所述小数倍时延的绝对值。
  19. 根据权利要求13所述的网络设备，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100004
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值。
  20. 根据权利要求13所述的网络设备，其特征在于，所述根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延，包括：
    在所述次峰值功率的初始位置索引值小于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为负数；或者，
    在所述次峰值功率的初始位置索引值大于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为正数。
  21. 根据权利要求12至20任一项所述的网络设备，其特征在于，所述根据所述小数倍时延，更新所述峰值功率的位置索引值，包括：
    根据所述峰值功率的初始位置索引值和所述小数倍时延之和，更新所述峰值功率的位置索引值。
  22. 根据权利要求12所述的网络设备，其特征在于，在根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延之前，所述操作还包括：
    确定与所述峰值功率的初始位置左、右最近邻的两个样点位置的功率；
    根据所述左、右最近邻的两个样点位置的功率中的最大值，确定所述次峰值功率。
  23. 一种时间提前量TA估计装置，其特征在于，包括：
    第一确定单元，用于根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延；所述目标归一化总时延用于表征所述目标检测窗所检测的信号的传输时延相对于相关序列样点间隔的倍数；
    更新单元，用于根据所述小数倍时延，更新所述峰值功率的位置索引值；
    第二确定单元，用于根据更新后的所述峰值功率的位置索引值，确定所述峰值功率的位置相对于所述目标检测窗起始位置的偏移量；
    第三确定单元，用于根据所述偏移量，确定所述目标检测窗对应的TA估计值。
  24. 根据权利要求23所述的TA估计装置，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率，确定目标归一化总时延中的小数倍时延，包括：
    根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值；
    根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延。
  25. 根据权利要求24所述的TA估计装置，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及所述目标检测窗对应的ZC根序列的长度，确定所述小数倍时延的绝对值。
  26. 根据权利要求25所述的TA估计装置，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100005
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值，N表示所述目标检测窗对应的ZC根序列的长度。
  27. 根据权利要求24所述的TA估计装置，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值。
  28. 根据权利要求27所述的TA估计装置，其特征在于，所述根据所述第一峰值功率比值，以及峰值功率比值和小数倍时延绝对值之间的预设对应关系，确定所述小数倍时延的绝对值，包括：
    按照峰值功率比值从大到小的顺序，依次将所述第一峰值功率比值与预设对应关系表中的峰值功率比值进行比较，确定所述预设对应关系表中小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，所述预设对应关系表包括峰值功率比值和小数倍时延绝对值之间的预设对应关系；
    根据所述小于所述第一峰值功率比值的第1个峰值功率比值所对应的索引值，确定所述小数倍时延的绝对值。
  29. 根据权利要求24所述的TA估计装置，其特征在于，所述根据目标检测窗的峰值功率和次峰值功率之间的第一峰值功率比值，确定所述小数倍时延的绝对值，包括：
    根据所述第一峰值功率比值，以及用于表征峰值功率比值和小数倍时延绝对值之间关联关系的分段函数，确定所述小数倍时延的绝对值。
  30. 根据权利要求24所述的TA估计装置，其特征在于，所述小数倍时延的绝对值通过以下公式确定：
    Figure PCTCN2022125907-appb-100006
    式中，|n 0|表示所述小数倍时延n 0的绝对值，peak ratio表示所述第一峰值功率比值。
  31. 根据权利要求24所述的TA估计装置，其特征在于，所述根据所述小数倍时延的绝对值，以及所述峰值功率和所述次峰值功率之间的初始位置关系，确定所述小数倍时延，包括：
    在所述次峰值功率的初始位置索引值小于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为负数；或者，
    在所述次峰值功率的初始位置索引值大于所述峰值功率的初始位置索引值的情况下，确定所述小数倍时延为正数。
  32. 根据权利要求23至31任一项所述的TA估计装置，其特征在于，所述根据所述小数倍时延，更新所述峰值功率的位置索引值，包括：
    根据所述峰值功率的初始位置索引值和所述小数倍时延之和，更新所述峰值功率的位置索引值。
  33. 根据权利要求23所述的TA估计装置，其特征在于，所述第一确定单元还用于：
    确定与所述峰值功率的初始位置左、右最近邻的两个样点位置的功率；
    根据所述左、右最近邻的两个样点位置的功率中的最大值，确定所述次峰值功率。
  34. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机程序，所述计算机程序用于使计算机执行权利要求1至11任一项所述的方法。
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CN104254100A (zh) * 2013-06-25 2014-12-31 普天信息技术研究院有限公司 一种上行定时提前量的测量方法
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