WO2016184155A1 - 定时偏移的处理方法及装置 - Google Patents

定时偏移的处理方法及装置 Download PDF

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Publication number
WO2016184155A1
WO2016184155A1 PCT/CN2016/071364 CN2016071364W WO2016184155A1 WO 2016184155 A1 WO2016184155 A1 WO 2016184155A1 CN 2016071364 W CN2016071364 W CN 2016071364W WO 2016184155 A1 WO2016184155 A1 WO 2016184155A1
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sequence
metric
value
subset
timing offset
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PCT/CN2016/071364
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English (en)
French (fr)
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张新
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中兴通讯股份有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H04W56/0035—Synchronisation arrangements detecting errors in frequency or phase
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H04W56/0055—Synchronisation arrangements determining timing error of reception due to propagation delay
    • H04W56/006—Synchronisation arrangements determining timing error of reception due to propagation delay using known positions of transmitter and receiver

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  • This document relates to, but is not limited to, the field of mobile communication technologies, and in particular, to a method and apparatus for processing timing offset.
  • the user equipment In the Long Term Evolution (LTE) and the LTE-Advanced (LTE-A) system, the user equipment (User Equipment, referred to as the “Evolved NodeB” (eNB or eNodeB) needs to be used for uplink synchronization.
  • the uplink signals sent by the UE can arrive at the base station synchronously, so the timing offset of each UE must be estimated, and then the UE is notified by the downlink command to adjust the transmission time.
  • the timing offset of the UE is usually measured on a Physical Random Access Channel (PRACH), a Physical Uplink Shared Channel (PUSCH), and a Sounding Reference Signal (SRS).
  • PRACH Physical Random Access Channel
  • PUSCH Physical Uplink Shared Channel
  • SRS Sounding Reference Signal
  • the methods for obtaining the timing offset mainly include the frequency domain and the time domain.
  • the frequency domain method uses the frequency domain phase of the channel estimation to calculate the time offset.
  • the time domain method converts the channel estimation value into the time domain by a certain method.
  • the timing offset is calculated according to the amplitude of the time domain, but the accuracy of the timing offset calculated by these methods is not high, and for the time domain method, it is only applicable to the positive time offset, and there is no processing for the negative time bias.
  • Embodiments of the present invention provide a method and apparatus for processing timing offsets, which can prevent timing offset estimation from being applied only to timing offset and can improve the accuracy of timing offset estimation.
  • the embodiment of the invention provides a processing method for timing offset, and the processing method for the timing offset includes the following steps:
  • H1 sequence is a sequence obtained by conjugateing a frequency domain signal of a user equipment received by a base station on a predetermined channel with a reference signal sequence;
  • the signal subset S(x1) and the noise subset NI(x2) of the metric sequence P(k) are obtained according to the maximum metric value Power, and the noise subset NI(x2) is calculated.
  • the steps of the feature metric NIPower include:
  • the step of calculating the first path position value according to the maximum metric value Power, the feature metric value NIPower, the noise interference threshold value T1, and the search threshold threshold value T2 includes:
  • the step of acquiring the metric sequence P(k) according to the H1 sequence and acquiring the maximum metric value Power of the metric sequence P(k) includes:
  • the metric sequence P(k) is obtained according to the time domain h1(k) sequence, and the maximum metric value Power of the metric sequence P(k) is obtained.
  • the step of acquiring the metric sequence P(k) according to the time domain h1(k) sequence includes:
  • the modulo square of the search sequence h2(k) is taken as the metric sequence P(k).
  • the embodiment of the present invention further provides a processing device for timing offset, where the processing device for the timing offset includes:
  • a first acquiring module configured to acquire an H1 sequence, where the H1 sequence is a sequence obtained by conjugateing a frequency domain signal of a user equipment received by a base station on a predetermined channel with a reference signal sequence;
  • a second obtaining module configured to acquire a metric sequence P(k) according to the H1 sequence, and obtain a maximum metric value Power of the metric sequence P(k);
  • a first calculating module configured to acquire a signal subset S(x1) and a noise subset NI(x2) of the metric sequence P(k) according to the maximum metric value Power, and calculate the noise subset NI(x2) Characteristic metric NIPower;
  • a second calculating module configured to calculate a first path position value according to the maximum metric value Power, the feature metric value NIPower, the noise interference threshold value T1, and the search threshold threshold value T2;
  • the third calculating module is configured to calculate a timing offset of the user equipment according to the first path position value.
  • the first computing module includes:
  • a first acquiring unit configured to acquire a left window length w1, a right window length w2, and a minimum index value MaxPidx corresponding to the maximum metric value Power of the metric sequence P(k), according to the left window length w1, the right window Long w2 and minimum index value MaxPidx obtain signal subset S(x1);
  • a second acquiring unit configured to acquire the noise subset NI(x2) according to the signal subset S(x1);
  • the calculating unit is configured to acquire a maximum metric value of the noise subset NI(x2) or calculate an average metric value of the noise subset NI(x2) as the feature metric value NIPower.
  • the second calculating module includes:
  • a determining unit configured to determine whether a ratio of the maximum metric value Power to the feature metric value NIPower is less than the noise interference threshold value T1;
  • a first processing unit configured to be, if yes, using the minimum index value MaxPidx as the first path position value
  • the second processing unit is configured to acquire a minimum index value T2idx corresponding to Power/T2 in the signal subset S(x1), and obtain the first path position value according to the minimum index value T2idx.
  • the second obtaining module includes:
  • An increasing unit configured to add a frequency point at both ends of the H1 sequence to obtain an H2(k) sequence, wherein the length of the H2(k) sequence is M;
  • the third obtaining unit is configured to acquire the metric sequence P(k) according to the time domain h1(k) sequence, and acquire the maximum metric value Power of the metric sequence P(k).
  • the third obtaining unit is configured to obtain a metric sequence P(k) according to the time domain h1(k) sequence: acquiring a user equipment search according to the time domain h1(k) sequence The sequence h2(k); the modulus square of the search sequence h2(k) is taken as the metric sequence P(k).
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the above method.
  • a method and a device for processing a timing offset are obtained by using a H1 sequence obtained by multiplying a frequency domain signal of a user equipment on a predetermined channel by a conjugate of a reference signal sequence to obtain a corresponding metric sequence P(k) and a metric.
  • the threshold threshold value T2 is compared to calculate the first-path position value, and the timing offset of the user equipment is calculated according to the first-path position value.
  • a positive timing offset can be calculated.
  • the shift amount can be calculated to obtain a negative timing offset, and the timing offset calculated by the method of the embodiment of the present invention has high accuracy.
  • FIG. 1 is a schematic flowchart of a method for processing a timing offset according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of a refinement process of step S102 in FIG. 1;
  • step S103 in FIG. 1 is a schematic diagram showing the refinement process of step S103 in FIG. 1;
  • step S104 in FIG. 1 is a schematic diagram of a refinement process of step S104 in FIG. 1;
  • FIG. 5 is a schematic diagram of functional modules of a timing offset processing apparatus according to an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of a refinement function module of the second acquisition module in FIG. 5;
  • FIG. 7 is a schematic diagram of a refinement function module of the first calculation module in FIG. 5;
  • FIG. 8 is a schematic diagram of a refinement function module of the second calculation module in FIG. 5.
  • An embodiment of the present invention provides a method for processing a timing offset, where the method includes a base station.
  • the device includes a base station.
  • the method for processing the timing offset includes:
  • Step S101 acquiring an H1 sequence
  • the H1 sequence is a sequence obtained by multiplying a frequency domain signal of a user equipment received by a base station on a predetermined channel and a reference signal sequence.
  • the predetermined channel is a physical random access channel or a physical uplink shared channel or a sounding reference channel.
  • the reference signal sequence is optionally a Zadoff-Chu sequence.
  • Step S102 acquiring a metric sequence P(k) according to the H1 sequence, and acquiring a maximum metric value Power of the metric sequence P(k);
  • the two ends of the H1 sequence are processed, and corresponding frequency points are added at both ends, so that
  • the length of the sequence after the frequency increase is M
  • the sequence after the frequency increase is converted to the time domain
  • the search sequence is determined by the sequence converted to the time domain according to the configuration of the system.
  • the search is performed.
  • the sequence obtains a metric sequence, for example, the metric series can be obtained by calculating the modulus of the search sequence, or the power sequence can be selected as the metric sequence: the metric series is obtained by calculating the modulo square of the search sequence.
  • the maximum metric Power of the metric sequence P(k) may correspond to one or more index values.
  • Step S103 acquiring a signal subset S(x1) and a noise subset NI(x2) of the metric sequence P(k) according to the maximum metric value Power, and calculating a characteristic metric value of the noise subset NI(x2) NIPower;
  • the metric sequence P(k) has the strongest position at which the metric value is the strongest. Therefore, the metric sequence P(k) can be determined according to the corresponding index value at the largest metric value Power in the metric sequence P(k).
  • the left window length and the right window length can be obtained by simulation or according to actual conditions, according to the left window length, the right window length, and the minimum corresponding to the largest metric value Power in the metric sequence P(k).
  • the index value is used to determine the signal subset S(x1), and then a portion of the sequence other than the signal subset S(x1) in the metric sequence P(k) is taken as the noise subset NI(x2).
  • the maximum metric value of the noise subset NI(x2) may be taken, or the average metric value of the noise subset NI(x2) may be calculated as a feature.
  • the metric NIPower, the feature metric NIPower is used to characterize the size of the noise signal corresponding to the noise subset NI(x2).
  • Step S104 calculating a first-path position value according to the maximum metric value Power, the feature metric value NIPower, the noise interference threshold value T1, and the search threshold threshold value T2;
  • the noise interference threshold T1 and the search threshold threshold T2 are optionally obtained by simulation, and the corresponding noise interference threshold T1 and the search threshold threshold T2 may be determined according to different scenarios.
  • the noise interference threshold T1 and the search threshold threshold T2 are obtained for subsequent use.
  • the first path position value Fidx is determined according to the noise interference threshold value T1; if the noise power of the signal transmitted by the user equipment is small and the signal power is large, the first path position value Fidx is determined by searching the threshold threshold value T2.
  • Step S105 Calculate a timing offset of the user equipment according to the first path position value.
  • the H1 sequence obtained by multiplying the frequency domain signal of the user equipment on the predetermined channel by the conjugate of the reference signal sequence is obtained to obtain the corresponding metric sequence P(k) and the metric sequence P(k).
  • the maximum metric Power, the characteristic metric NIPower of the noise subset NI(x2) of the metric sequence P(k), the maximum metric Power and the characteristic metric NIPower and the noise interference threshold T1 or the search threshold threshold T2 Comparing to calculate the first-path position value, and calculating the timing offset of the user equipment according to the first-path position value.
  • a positive timing offset can be calculated, and a negative timing offset can be calculated, and the embodiment is used.
  • the timing offset calculated by the method is more accurate.
  • the foregoing step S102 includes:
  • Step S1021 adding a frequency point at both ends of the H1 sequence to obtain an H2(k) sequence, wherein the length of the H2(k) sequence is M;
  • Step S1023 Acquire a metric sequence P(k) according to the time domain h1(k) sequence, and obtain a maximum metric value Power of the metric sequence P(k).
  • the two ends of the H1 sequence are processed to obtain an H2(k) sequence.
  • the processing of the H1 sequence is mainly to increase the number of frequency domain points at both ends, and increase the value of the point, optionally 0, or fill in the value by other means.
  • the number of frequency domain points added to the H1 sequence is also different: the number of added frequency domain points is considered to be the complexity of implementation, and the resolution of timing offset is considered. .
  • the number of subcarriers occupied by the signal transmitted by the user equipment through the physical random access channel is 864 or 144
  • the corresponding Zadoff-Chu sequence length is correspondingly 839 or 139, that is, the length of the H1 sequence of the physical random access channel is 839 or 139
  • the length of the H2(k) sequence obtained after the processing may be 864 or 144, or may be an appropriate length according to other rules.
  • the processing method is similar to PRACH.
  • the frequency is increased at both ends of the H1 sequence.
  • the value of the optional increase point is 0, or other values are filled.
  • H1 H2(k).
  • IFT Inverse Discrete Fourier Transform
  • the search sequence h2(k) of the user equipment is obtained by h1(k).
  • the metric sequence P(k) can also be calculated in other ways, such as the magnitude of h2(k).
  • Step S103 includes:
  • Step S1031 Obtain a left window length w1, a right window length w2, and a minimum index value MaxPidx corresponding to the maximum metric value Power of the metric sequence P(k), according to the left window length w1, the right window length w2, and the minimum
  • the index value MaxPidx obtains a subset of signals S(x1);
  • Step S1032 acquiring the noise subset NI(x2) according to the signal subset S(x1);
  • Step S1033 Acquire a maximum metric value of the noise subset NI(x2) or calculate an average metric value of the noise subset NI(x2) as the feature metric value NIPower.
  • the left window length w1 and the right window length w2 of the metric sequence P(k) are obtained, and the left window length w1 and the right window length w2 can be obtained by simulation or according to actual conditions.
  • the feature metric NIpower is obtained by NI(x2).
  • the feature metric NIpower may take the largest metric of the noise subset NI(x2) or calculate the average metric of the noise subset NI(x2) as the feature metric NIPower (the average metric must be non-zero) ).
  • the optional calculation of the signal subset S(x1) and the noise subset NI(x2) is as follows:
  • the foregoing step S104 includes:
  • Step S1041 determining whether the ratio of the maximum metric value Power and the feature metric value NIPower is less than the noise interference threshold value T1; if yes, proceeding to step S1042, and if not, proceeding to step S1043;
  • Step S1042 using the minimum index value MaxPidx as the first path position value, and the process ends;
  • Step S1043 Acquire a minimum index value T2idx corresponding to Power/T2 in the signal subset S(x1), obtain the first path position value according to the minimum index value T2idx, and the process ends.
  • the noise interference threshold T1 and the search threshold threshold T2 are optionally obtained by simulation, and the corresponding noise interference threshold T1 and the search threshold threshold T2 may also be determined according to different scenarios.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the above method.
  • the embodiment of the present invention further provides a processing device for timing offset.
  • the processing device for the timing offset includes:
  • the first obtaining module 101 is configured to acquire an H1 sequence, where the H1 sequence is a sequence obtained by conjugateing a frequency domain signal of a user equipment received by a base station on a predetermined channel with a reference signal sequence;
  • the H1 sequence is a sequence obtained by multiplying a frequency domain signal of a user equipment received by a base station on a predetermined channel and a reference signal sequence.
  • the predetermined channel is a physical random access channel or a physical uplink shared channel or a sounding reference channel.
  • the reference signal sequence is optionally a Zadoff-Chu sequence.
  • the second obtaining module 102 is configured to acquire a metric sequence P(k) according to the H1 sequence, and obtain a maximum metric value Power of the metric sequence P(k);
  • the two ends of the H1 sequence are processed, and the corresponding frequency points are added at both ends, so that the length of the sequence after the frequency increase is M, and then the sequence after the frequency increase is converted to the time domain, and then according to The configuration of the system determines the search sequence by converting to the sequence of the time domain.
  • the metric sequence is obtained by searching the sequence.
  • the metric series can be obtained by calculating the modulus of the search sequence, or the power sequence can be selected as the metric sequence. : by calculating the modulus square of the search sequence Get the metric series.
  • the maximum metric Power of the metric sequence P(k) may correspond to one or more index values.
  • the first calculating module 103 is configured to acquire a signal subset S(x1) and a noise subset NI(x2) of the metric sequence P(k) according to the maximum metric value Power, and calculate the noise subset NI(x2) Characteristic metric NIPower;
  • the metric sequence P(k) has the strongest position at which the metric value is the strongest. Therefore, the metric sequence P(k) can be determined according to the corresponding index value at the largest metric value Power in the metric sequence P(k).
  • the left window length and the right window length can be obtained by simulation or according to actual conditions, according to the left window length, the right window length, and the minimum corresponding to the largest metric value Power in the metric sequence P(k).
  • the index value is used to determine the signal subset S(x1), and then a portion of the sequence other than the signal subset S(x1) in the metric sequence P(k) is taken as the noise subset NI(x2).
  • the maximum metric value of the noise subset NI(x2) may be taken, or the average metric value of the noise subset NI(x2) may be calculated as a feature.
  • the metric NIPower, the feature metric NIPower is used to characterize the size of the noise signal corresponding to the noise subset NI(x2).
  • the second calculating module 104 is configured to calculate a first path position value according to the maximum metric value Power, the feature metric value NIPower, the noise interference threshold value T1, and the search threshold threshold value T2;
  • the noise interference threshold T1 and the search threshold threshold T2 are optionally obtained by simulation, and the corresponding noise interference threshold T1 and the search threshold threshold T2 may also be determined according to different scenarios.
  • the first-path position value Fidx is determined according to the noise interference threshold value T1; if the noise power of the signal sent by the user equipment is small If the signal power is large, the first-path position value Fidx is determined by searching the threshold threshold value T2.
  • the third calculating module 105 is configured to calculate a timing offset of the user equipment according to the first path position value.
  • the second obtaining module 102 includes:
  • the adding unit 1021 is configured to add a frequency point at both ends of the H1 sequence to obtain an H2(k) sequence, wherein the length of the H2(k) sequence is M;
  • the third obtaining unit 1023 is configured to acquire the metric sequence P(k) according to the time domain h1(k) sequence, and acquire the maximum metric value Power of the metric sequence P(k).
  • the two ends of the H1 sequence are processed to obtain an H2(k) sequence.
  • the processing of the H1 sequence is mainly to increase the number of frequency domain points at both ends, and increase the value of the point, optionally 0, or fill in the value by other means.
  • the number of frequency domain points added to the H1 sequence is also different: the number of added frequency domain points is considered to be the complexity of implementation, and the resolution of timing offset is considered. .
  • the number of subcarriers occupied by the signal transmitted by the user equipment through the physical random access channel is 864 or 144
  • the corresponding Zadoff-Chu sequence length is correspondingly 839 or 139, that is, the length of the H1 sequence of the physical random access channel is 839 or 139
  • the length of the H2(k) sequence obtained after the processing may be 864 or 144, or may be an appropriate length according to other rules.
  • both ends of the H1 sequence need to be processed.
  • M> N/16, where N is the number of FFT points corresponding to the system bandwidth.
  • the processing method is similar to PRACH.
  • the frequency is increased at both ends of the H1 sequence.
  • the value of the optional increase point is 0, or other values are filled.
  • H1 H2(k).
  • IFT Inverse Discrete Fourier Transform
  • the search sequence h2(k) of the user equipment is obtained by h1(k).
  • the metric sequence P(k) can also be calculated in other ways, such as the magnitude of h2(k).
  • the first calculating module 103 includes:
  • the first obtaining unit 1031 is configured to acquire a left window length w1, a right window length w2, and a minimum index value MaxPidx corresponding to the maximum metric value Power of the metric sequence P(k), according to the left window length w1, right Window length w2 and minimum index value MaxPidx obtain signal subset S(x1);
  • the second obtaining unit 1032 is configured to acquire the noise subset NI(x2) according to the signal subset S(x1);
  • the calculating unit 1033 is configured to acquire a maximum metric value of the noise subset NI(x2) or calculate an average metric value of the noise subset NI(x2) as the feature metric value NIPower.
  • the left window length w1 and the right window length w2 of the metric sequence P(k) are obtained, and the left window length w1 and the right window length w2 can be obtained by simulation or according to actual conditions.
  • the feature metric NIpower is obtained by NI(x2).
  • the feature metric NIpower may take the largest metric of the noise subset NI(x2) or calculate the average metric of the noise subset NI(x2) as the feature metric NIPower (the average metric must be non-zero) ).
  • the optional calculation of the signal subset S(x1) and the noise subset NI(x2) is as follows:
  • the second computing module 104 includes:
  • the determining unit 1041 is configured to determine whether the ratio of the maximum metric value Power to the feature metric value NIPower is less than the noise interference threshold value T1;
  • the first processing unit 1042 is configured to: if yes, use the minimum index value MaxPidx as the first path position value;
  • the second processing unit 1043 is configured to acquire, if not, a minimum index value T2idx corresponding to Power/T2 in the signal subset S(x1), and obtain the first path position value according to the minimum index value T2idx.
  • the noise interference threshold T1 and the search threshold threshold T2 are optionally obtained by simulation, and the corresponding noise interference threshold T1 and the search threshold threshold T2 may also be determined according to different scenarios.
  • each module/unit in the above embodiment may be implemented in the form of hardware, for example, by implementing an integrated circuit to implement its corresponding function, or may be implemented in the form of a software function module, for example, executing a program stored in the memory by a processor. / instruction to achieve its corresponding function.
  • the invention is not limited to any specific form of combination of hardware and software.
  • the above technical solution can calculate a positive timing offset, can calculate a negative timing offset, and the calculated timing offset has high accuracy.

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Abstract

一种定时偏移的处理方法及装置，所述定时偏移的处理方法包括以下步骤：获取H1序列；根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；根据所述首径位置值计算所述用户设备的定时偏移量，上述技术方案适用于正负定时偏移量的估计，并且定时偏移量准确度较高。

Description

定时偏移的处理方法及装置 技术领域
本文涉及但不限于移动通信技术领域，尤其涉及一种定时偏移的处理方法及装置。
背景技术
在长期演进(Long Term Evolution，LTE)和高级长期演进(LTE-Advanced，LTE-A)***中，基站(evolved NodeB，eNB或eNodeB)为了实现上行同步，需要每个用户设备(User Equipment，简称UE)发出的上行信号都能同步到达基站，因此必须估计出每个UE的定时偏移，然后通过下行命令通知UE调整发射时间。UE的定时偏移通常是在物理随机接入信道(Physical Random Access Channel，PRACH)、物理上行共享信道(Physical Uplink Shared Channel，PUSCH)、探测参考信道(Sounding reference signal，SRS)上进行测量。
获取定时偏移的方法主要有频域和时域两种，频域方法是利用信道估计的频域相位来计算时偏，时域方法是通过将信道估计值通过一定的方法转换到时域，根据时域的幅值来计算定时偏移，但是通过这些方法计算出来的定时偏移的精度都不高，并且对于时域方法，也只适用于正时偏，对于负时偏没有处理。
发明内容
以下是对本文详细描述的主题的概述。本概述并非是为了限制权利要求的保护范围。
本发明实施例提供一种定时偏移的处理方法及装置，可避免定时偏移估计只适用于正时偏且可提高定时偏移估计的准确度。
本发明实施例提供一种定时偏移的处理方法，所述定时偏移的处理方法包括以下步骤：
获取H1序列，其中，所述H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列；
根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
根据所述首径位置值计算所述用户设备的定时偏移量。
可选地，所述根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower的步骤包括：
获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
可选地，所述根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值的步骤包括：
判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；
若是，则以所述最小索引值MaxPidx作为所述首径位置值；
若否，则获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值。
可选地，所述根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power的步骤包括：
在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0,…,M-1；
根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
可选地，所述根据所述时域h1(k)序列获取度量序列P(k)的步骤包括：
根据所述时域h1(k)序列获取用户设备的搜索序列h2(k)；
以所述搜索序列h2(k)的模平方作为所述度量序列P(k)。
此外，本发明实施例还提供一种定时偏移的处理装置，所述定时偏移的处理装置包括：
第一获取模块，设置为获取H1序列，其中，所述H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列；
第二获取模块，设置为根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
第一计算模块，设置为根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
第二计算模块，设置为根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
第三计算模块，设置为根据所述首径位置值计算所述用户设备的定时偏移量。
可选地，所述第一计算模块包括：
第一获取单元，设置为获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
第二获取单元，设置为获取根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
计算单元，设置为获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
可选地，所述第二计算模块包括：
判断单元，设置为判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；
第一处理单元，设置为若是，则以所述最小索引值MaxPidx作为所述首径位置值；
第二处理单元，设置为若否，则获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值。
可选地，所述第二获取模块包括：
增加单元，设置为在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
转换单元，设置为将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0,…,M-1；
第三获取单元，设置为根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
可选地，所述第三获取单元是设置为通过如下方式实现根据所述时域h1(k)序列获取度量序列P(k)：根据所述时域h1(k)序列获取用户设备的搜索序列h2(k)；以所述搜索序列h2(k)的模平方作为所述度量序列P(k)。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行上述的方法。
本发明实施例一种定时偏移的处理方法及装置，通过用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的H1序列来获取对应的度量序列P(k)、度量序列P(k)的最大度量值Power、度量序列P(k)的噪声子集NI(x2)的特征度量值NIPower，将最大度量值Power及特征度量值NIPower与噪声干扰门限值T1或搜索门限门限值T2进行比较来计算首径位置值，根据首径位置值计算用户设备的定时偏移量，本发明实施例可以计算得到正的定时偏 移量，可以计算得到负的定时偏移量，并且采用本发明实施例的方法所计算得到的定时偏移量准确度较高。
在阅读并理解了附图和详细描述后，可以明白其他方面。
附图概述
图1为本发明实施例定时偏移的处理方法流程示意图；
图2为图1中步骤S102的细化流程示意图；
图3为图1中步骤S103的细化流程示意图；
图4为图1中步骤S104的细化流程示意图；
图5为本发明实施例定时偏移的处理装置的功能模块示意图；
图6为图5中第二获取模块的细化功能模块示意图；
图7为图5中第一计算模块的细化功能模块示意图；
图8为图5中第二计算模块的细化功能模块示意图。
本发明的实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
本发明实施例提供一种定时偏移的处理方法，该方法用于定时偏移的处理装置，所述装置包括基站，参照图1，在一实施例中，该定时偏移的处理方法包括：
步骤S101，获取H1序列；
本实施例中，H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列。
本实施例中，预定信道为物理随机接入信道或物理上行共享信道或探测参考信道。参考信号序列可选地是Zadoff-Chu序列。
步骤S102，根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
本实施例中，对H1序列的两端进行处理，在两端增加相应的频点，使 得增加频点后的序列的长度为M，然后将增加频点后的序列转换到时域，然后根据***的配置，由转换到时域的序列来确定搜索序列，本实施例中，通过搜索序列得到度量序列，例如可以通过计算搜索序列的模值来得到度量系列，或者可以选择功率序列作为度量序列：即通过计算搜索序列的模平方来得到度量系列。
本实施例中，在获取度量序列P(k)的最大度量值Power中，度量序列P(k)的最大度量值Power可能对应有一个或者多个索引值。通过寻找到度量序列P(k)的最大度量值Power，可以将用户设备发送的信号进行信号与噪声的划分。
步骤S103，根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
本实施例中，度量序列P(k)中度量值最大处表征信号最强的位置，因此，可以根据度量序列P(k)中最大度量值Power处对应的索引值来确定度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)。
本实施例中，可以通过仿真的方式或者根据实际情况来推到得到左窗长及右窗长，根据左窗长、右窗长及度量序列P(k)中最大度量值Power处对应的最小索引值来确定信号子集S(x1)，然后在度量序列P(k)中除信号子集S(x1)外的序列中取其中的一部分作为噪声子集NI(x2)。
本实施例中，在计算噪声子集NI(x2)的特征度量值NIPower中，可以取噪声子集NI(x2)的最大度量值，或者计算噪声子集NI(x2)的平均度量值作为特征度量值NIPower，特征度量值NIPower用于表征噪声子集NI(x2)对应的噪声信号的大小。
步骤S104，根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
本实施例中，噪声干扰门限值T1及搜索门限门限值T2可选地通过仿真获得，也可以根据不同的场景确定对应的噪声干扰门限值T1及搜索门限门限值T2，可在第一次计算首径位置时获取噪声干扰门限值T1及搜索门限门限值T2，以供后续使用。
本实施例中，如果用户设备发送的信号的噪声功率较大而信号功率较小， 则根据噪声干扰门限值T1来确定首径位置值Fidx；如果用户设备发送的信号的噪声功率较小而信号功率较大，则通过搜索门限门限值T2来确定首径位置值Fidx。
步骤S105，根据所述首径位置值计算所述用户设备的定时偏移量。
本实施例中，如果首径位置值Fidx<M/2，则定时偏移量TAest＝Fidx/M*2048；如果首径位置值Fidx>＝M/2,则定时偏移量TAest＝(Fidx-M)/M*2048。由此，可以看出，本实施例即可以计算得到正的定时偏移量，可以计算得到负的定时偏移量，并且采用本实施例的方法所计算得到的定时偏移量准确度较高。
其中，定时偏移量TAest的单位是Ts，1Ts＝0.001/30720秒。根据实际应用情况的要求，对于定时偏移量TAest可采用适当的取整方式，例如采用四舍五入的方式取整。
与相关技术相比，本实施例通过用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的H1序列来获取对应的度量序列P(k)、度量序列P(k)的最大度量值Power、度量序列P(k)的噪声子集NI(x2)的特征度量值NIPower，将最大度量值Power及特征度量值NIPower与噪声干扰门限值T1或搜索门限门限值T2进行比较来计算首径位置值，根据首径位置值计算用户设备的定时偏移量，本实施例可以计算得到正的定时偏移量，可以计算得到负的定时偏移量，并且采用本实施例的方法所计算得到的定时偏移量准确度较高。
在一可选的实施例中，如图2所示，在上述图1的实施例的基础上，上述步骤S102包括：
步骤S1021，在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
步骤S1022，将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0，…，M-1；
步骤S1023，根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
本实施例中，对H1序列两端做处理，得到H2(k)序列。其中，H1序列 是将基站接收到的用户设备在预定信道上的频域信号与Zadoff-Chu序列共轭相乘的结果,k＝0,…,M-1，M为H2(k)序列的长度。
本实施例中，对H1序列的处理主要是在两端增加频域点数，增加的点的值，可选的是0，也可以采用其他方式填值。针对不同信道和用户设备信号的子载波数，对H1序列增加的频域点数也不同：增加的频域点数一方面是考虑实现的复杂度，另一方面要考虑定时偏移量的分辨率。
本实施例中，对于物理随机接入信道，根据LTE和LTE-A协议，用户设备通过物理随机接入信道发送的信号占用的子载波数为864或144，对应的Zadoff-Chu序列长度相应为839或139,即物理随机接入信道的H1序列长度为839或139，处理后得到的H2(k)序列的长度可选的可以取864或144，也可以根据其他规则取合适的长度。
对于物理上行共享信道和探测参考信道，需要对H1序列两端做处理，使得M>＝N/16，其中，N为***带宽对应的FFT点数。处理方式类似PRACH，都是在H1序列两端增加频点，可选增加点的值为0，或者填其他值。增加的点数为0时，H1＝H2(k)。
本实施例中，将H2(k)转化到时域，得到h1(k)，k＝0,…,M-1。频域到时域的转化可以有多种方式，可选的是离散傅里叶逆变换(Inverse Discrete Fourier Transform，IDFT)。根据***配置，由h1(k)得到用户设备的搜索序列h2(k)。可选地，根据用户设备占用的频域位置上复用的码分用户数和码分参数来确定搜索序列h2(k)。如果该频域位置除了该用户设备，还有其他用户设备，则将其他用户设备对应的h1(k)中的值清零，得到h2(k)。如果该频域位置只有该用户设备，没有其他用户设备，则h2(k)＝h1(k)。
其中，由h2(k)得到度量序列P(k)：度量序列P(k)可选的采用功率序列，此时P(k)＝h2(k).*[h2(k)]H，其中[h2(k)]H是h2(k)的共轭。度量序列P(k)也可以采用其他方式计算，如为h2(k)的幅值等。
本实施例中，度量序列P(k)的最大值的点可能有多个，度量序列P(k)的最大值的所有点[Power,MaxPidx]中，最大度量值Power＝P(MaxPidx)，取其中最小的索引值作为本实施例的最小索引值MaxPidx。
在一可选的实施例中，如图3所示，在上述图1的实施例的基础上，上 述步骤S103包括：
步骤S1031，获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
步骤S1032，根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
步骤S1033，获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
本实施例中，获取度量序列P(k)的左窗长w1、右窗长w2，可以通过仿真的方式或者根据实际情况来推到得到左窗长w1及右窗长w2。根据左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)，其中，x1＝0,…,w1-1。然后在度量序列P(k)中除信号子集S(x1)外的序列中取其中的一部分作为噪声子集NI(x2)，x2＝0,…,ni-1，其中，ni是NI序列的长度。由NI(x2)求得特征度量值NIpower。可选地，特征度量值NIpower可以取噪声子集NI(x2)的最大度量值，或者计算噪声子集NI(x2)的平均度量值作为特征度量值NIPower(该平均度量值须为非0值)。
本实施例中，信号子集S(x1)及噪声子集NI(x2)的可选计算的方式如下：
当MaxPidx>＝w1时：
S(x1)＝P(MaxPidx-w1+1:1:MaxPidx)；如果MaxPidx+w1<＝M，则NI(x2)＝[P(0:1:MaxPidx-w1)；P(MaxPidx+w2:1:M-1)]；如果MaxPidx+w1>M，则NI(x2)＝P(MaxPidx+w2-M:1:MaxPidx-w1)；
当MaxPidx<w1时：
S(x1)＝[P(M-(w1-MaxPidx)+2:1:M-1)；P(0:1:MaxPidx)]，NI(x2)＝P(MaxPidx+w2:1:M-(w1-MaxPidx)+1)；
其中(a:1:b)表示索引值a到索引值b之间的每一个索引值。
在一可选的实施例中，如图4所示，在上述图3的实施例的基础上，上述步骤S104包括：
步骤S1041，判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；若是，则进入步骤S1042，若不是，进入步骤S1043；
步骤S1042，以所述最小索引值MaxPidx作为所述首径位置值，流程结束；
步骤S1043，获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值，流程结束。
本实施例中，如果Power/NIpower<T1，则首径位置值为Fidx＝MaxPidx；如果Power/NIpower>＝T1，则获取信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，并获取S(T2idx)对应于度量P(k)的索引TP2idx，首径位置Fidx＝TP2idx。
本实施例中，噪声干扰门限值T1及搜索门限门限值T2可选地通过仿真获得，也可以根据不同的场景确定对应的噪声干扰门限值T1及搜索门限门限值T2。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行上述的方法。
本发明实施例还提供一种定时偏移的处理装置，如图5所示，所述定时偏移的处理装置包括：
第一获取模块101，设置为获取H1序列，其中，所述H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列；
本实施例中，H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列。
本实施例中，预定信道为物理随机接入信道或物理上行共享信道或探测参考信道。参考信号序列可选地为Zadoff-Chu序列。
第二获取模块102，设置为根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
本实施例中，对H1序列的两端进行处理，在两端增加相应的频点，使得增加频点后的序列的长度为M，然后将增加频点后的序列转换到时域，然后根据***的配置，由转换到时域的序列来确定搜索序列，本实施例中，通过搜索序列得到度量序列，例如可以通过计算搜索序列的模值来得到度量系列，或者可以选择功率序列作为度量序列：即通过计算搜索序列的模平方来 得到度量系列。
本实施例中，在获取度量序列P(k)的最大度量值Power中，度量序列P(k)的最大度量值Power可能对应有一个或者多个索引值。通过寻找到度量序列P(k)的最大度量值Power，可以将用户设备发送的信号进行信号与噪声的划分。
第一计算模块103，设置为根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
本实施例中，度量序列P(k)中度量值最大处表征信号最强的位置，因此，可以根据度量序列P(k)中最大度量值Power处对应的索引值来确定度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)。
本实施例中，可以通过仿真的方式或者根据实际情况来推到得到左窗长及右窗长，根据左窗长、右窗长及度量序列P(k)中最大度量值Power处对应的最小索引值来确定信号子集S(x1)，然后在度量序列P(k)中除信号子集S(x1)外的序列中取其中的一部分作为噪声子集NI(x2)。
本实施例中，在计算噪声子集NI(x2)的特征度量值NIPower中，可以取噪声子集NI(x2)的最大度量值，或者计算噪声子集NI(x2)的平均度量值作为特征度量值NIPower，特征度量值NIPower用于表征噪声子集NI(x2)对应的噪声信号的大小。
第二计算模块104，设置为根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
本实施例中，噪声干扰门限值T1及搜索门限门限值T2可选地通过仿真获得，也可以根据不同的场景确定对应的噪声干扰门限值T1及搜索门限门限值T2。
本实施例中，如果用户设备发送的信号的噪声功率较大而信号功率较小，则根据噪声干扰门限值T1来确定首径位置值Fidx；如果用户设备发送的信号的噪声功率较小而信号功率较大，则通过搜索门限门限值T2来确定首径位置值Fidx。
第三计算模块105，设置为根据所述首径位置值计算所述用户设备的定时偏移量。
本实施例中，如果首径位置值Fidx<M/2，则定时偏移量TAest＝Fidx/M*2048；如果首径位置值Fidx>＝M/2,则定时偏移量TAest＝(Fidx-M)/M*2048。由此，可以看出，本实施例即可以计算得到正的定时偏移量，可以计算得到负的定时偏移量，并且采用本实施例的方法所计算得到的定时偏移量准确度较高。
其中，定时偏移量TAest的单位是Ts，1Ts＝0.001/30720秒。根据实际应用情况的要求，对于定时偏移量TAest可采用适当的取整方式，例如采用四舍五入的方式取整。
在一可选的实施例中，如图6所示，在上述图5的实施例的基础上，第二获取模块102包括：
增加单元1021，设置为在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
转换单元1022，设置为将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0,…,M-1；
第三获取单元1023，设置为根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
本实施例中，对H1序列两端做处理，得到H2(k)序列。其中，H1序列是将基站接收到的用户设备在预定信道上的频域信号与Zadoff-Chu序列共轭相乘的结果,k＝0,…,M-1，M为H2(k)序列的长度。
本实施例中，对H1序列的处理主要是在两端增加频域点数，增加的点的值，可选的是0，也可以采用其他方式填值。针对不同信道和用户设备信号的子载波数，对H1序列增加的频域点数也不同：增加的频域点数一方面是考虑实现的复杂度，另一方面要考虑定时偏移量的分辨率。
本实施例中，对于物理随机接入信道，根据LTE和LTE-A协议，用户设备通过物理随机接入信道发送的信号占用的子载波数为864或144，对应的Zadoff-Chu序列长度相应为839或139,即物理随机接入信道的H1序列长度为839或139，处理后得到的H2(k)序列的长度可选的可以取864或144，也可以根据其他规则取合适的长度。
对于物理上行共享信道和探测参考信道，需要对H1序列两端做处理， 使得M>＝N/16，其中，N为***带宽对应的FFT点数。处理方式类似PRACH，都是在H1序列两端增加频点，可选增加点的值为0，或者填其他值。增加的点数为0时，H1＝H2(k)。
本实施例中，将H2(k)转化到时域，得到h1(k)，k＝0,…,M-1。频域到时域的转化可以有多种方式，可选的是离散傅里叶逆变换(Inverse Discrete Fourier Transform，IDFT)。根据***配置，由h1(k)得到用户设备的搜索序列h2(k)。可选地，根据用户设备占用的频域位置上复用的码分用户数和码分参数来确定搜索序列h2(k)。如果该频域位置除了该用户设备，还有其他用户设备，则将其他用户设备对应的h1(k)中的值清零，得到h2(k)。如果该频域位置只有该用户设备，没有其他用户设备，则h2(k)＝h1(k)。
其中，由h2(k)得到度量序列P(k)：度量序列P(k)可选的采用功率序列，此时P(k)＝h2(k).*[h2(k)]H，其中[h2(k)]H是h2(k)的共轭。度量序列P(k)也可以采用其他方式计算，如为h2(k)的幅值等。
本实施例中，度量序列P(k)的最大值的点可能有多个，度量序列P(k)的最大值的所有点[Power,MaxPidx]中，最大度量值Power＝P(MaxPidx)，取其中最小的索引值作为本实施例的最小索引值MaxPidx。
在一可选的实施例中，如图7所示，在上述图5的实施例的基础上，所述第一计算模块103包括：
第一获取单元1031，设置为获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
第二获取单元1032，设置为获取根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
计算单元1033，设置为获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
本实施例中，获取度量序列P(k)的左窗长w1、右窗长w2，可以通过仿真的方式或者根据实际情况来推到得到左窗长w1及右窗长w2。根据左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)，其中，x1＝0,…,w1-1。然后在度量序列P(k)中除信号子集S(x1)外的序列中取其中的一部分作 为噪声子集NI(x2)，x2＝0,…,ni-1，其中，ni是NI序列的长度。由NI(x2)求得特征度量值NIpower。可选地，特征度量值NIpower可以取噪声子集NI(x2)的最大度量值，或者计算噪声子集NI(x2)的平均度量值作为特征度量值NIPower(该平均度量值须为非0值)。
本实施例中，信号子集S(x1)及噪声子集NI(x2)的可选计算的方式如下：
当MaxPidx>＝w1时：
S(x1)＝P(MaxPidx-w1+1:1:MaxPidx)；如果MaxPidx+w1<＝M，则NI(x2)＝[P(0:1:MaxPidx-w1)；P(MaxPidx+w2:1:M-1)]；如果MaxPidx+w1>M，则NI(x2)＝P(MaxPidx+w2-M:1:MaxPidx-w1)；
当MaxPidx<w1时：
S(x1)＝[P(M-(w1-MaxPidx)+2:1:M-1)；P(0:1:MaxPidx)]，NI(x2)＝P(MaxPidx+w2:1:M-(w1-MaxPidx)+1)；
其中(a:1:b)表示索引值a到索引值b之间的每一个索引值。
在一可选的实施例中，如图8所示，在上述图7的实施例的基础上，所述第二计算模块104包括：
判断单元1041，设置为判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；
第一处理单元1042，设置为若是，则以所述最小索引值MaxPidx作为所述首径位置值；
第二处理单元1043，设置为若否，则获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值。
本实施例中，如果Power/NIpower<T1，则首径位置值为Fidx＝MaxPidx；如果Power/NIpower>＝T1，则获取信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，并获取S(T2idx)对应于度量P(k)的索引TP2idx，首径位置Fidx＝TP2idx。
本实施例中，噪声干扰门限值T1及搜索门限门限值T2可选地通过仿真获得，也可以根据不同的场景确定对应的噪声干扰门限值T1及搜索门限门限值T2。
本领域普通技术人员可以理解上述方法中的全部或部分步骤可通过程序来指令相关硬件(例如处理器)完成，所述程序可以存储于计算机可读存储介质中，如只读存储器、磁盘或光盘等。可选地，上述实施例的全部或部分步骤也可以使用一个或多个集成电路来实现。相应地，上述实施例中的各模块/单元可以采用硬件的形式实现，例如通过集成电路来实现其相应功能，也可以采用软件功能模块的形式实现，例如通过处理器执行存储于存储器中的程序/指令来实现其相应功能。本发明不限制于任何特定形式的硬件和软件的结合。
本领域的普通技术人员应当理解，可以对本发明的技术方案进行修改或者等同替换，而不脱离本发明技术方案的精神和范围，均应涵盖在本发明的权利要求范围当中。
工业实用性
上述技术方案可以计算得到正的定时偏移量，可以计算得到负的定时偏移量，并且所计算得到的定时偏移量准确度较高。

Claims (11)

  1. 一种定时偏移的处理方法，所述定时偏移的处理方法包括以下步骤：
    获取H1序列，其中，所述H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列；
    根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
    根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
    根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
    根据所述首径位置值计算所述用户设备的定时偏移量。
  2. 如权利要求1所述的定时偏移的处理方法，其中，所述根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower的步骤包括：
    获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
    根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
    获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
  3. 如权利要求2所述的定时偏移的处理方法，其中，所述根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值的步骤包括：
    判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；
    若是，则以所述最小索引值MaxPidx作为所述首径位置值；
    若否，则获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值。
  4. 如权利要求1所述的定时偏移的处理方法，其中，所述根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power的步骤包括：
    在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
    将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0,…,M-1；
    根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
  5. 如权利要求4所述的定时偏移的处理方法，其中，所述根据所述时域h1(k)序列获取度量序列P(k)的步骤包括：
    根据所述时域h1(k)序列获取用户设备的搜索序列h2(k)；
    以所述搜索序列h2(k)的模平方作为所述度量序列P(k)。
  6. 一种定时偏移的处理装置，所述定时偏移的处理装置包括：
    第一获取模块，设置为获取H1序列，其中，所述H1序列为基站接收到的用户设备在预定信道上的频域信号与参考信号序列共轭相乘得到的序列；
    第二获取模块，设置为根据所述H1序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power；
    第一计算模块，设置为根据所述最大度量值Power获取所述度量序列P(k)的信号子集S(x1)及噪声子集NI(x2)，计算所述噪声子集NI(x2)的特征度量值NIPower；
    第二计算模块，设置为根据所述最大度量值Power、特征度量值NIPower、噪声干扰门限值T1及搜索门限门限值T2计算首径位置值；
    第三计算模块，设置为根据所述首径位置值计算所述用户设备的定时偏移量。
  7. 如权利要求6所述的定时偏移的处理装置，其中，所述第一计算模块包括：
    第一获取单元，设置为获取所述度量序列P(k)的左窗长w1、右窗长w2及所述最大度量值Power对应的最小索引值MaxPidx，根据所述左窗长w1、右窗长w2及最小索引值MaxPidx获取信号子集S(x1)；
    第二获取单元，设置为获取根据所述信号子集S(x1)获取所述噪声子集NI(x2)；
    计算单元，设置为获取所述噪声子集NI(x2)的最大度量值或者计算所述噪声子集NI(x2)的平均度量值作为所述特征度量值NIPower。
  8. 如权利要求7所述的定时偏移的处理装置，其中，所述第二计算模块包括：
    判断单元，设置为判断所述最大度量值Power与特征度量值NIPower的比值是否小于所述噪声干扰门限值T1；
    第一处理单元，设置为若是，则以所述最小索引值MaxPidx作为所述首径位置值；
    第二处理单元，设置为若否，则获取所述信号子集S(x1)中大于Power/T2对应的最小索引值T2idx，根据所述最小索引值T2idx获取所述首径位置值。
  9. 如权利要求6所述的定时偏移的处理装置，其中，所述第二获取模块包括：
    增加单元，设置为在所述H1序列的两端增加频点，得到H2(k)序列，其中，所述H2(k)序列的长度为M；
    转换单元，设置为将所述H2(k)序列转换至时域，得到时域h1(k)序列，其中，k＝0,…,M-1；
    第三获取单元，设置为根据所述时域h1(k)序列获取度量序列P(k)，并获取所述度量序列P(k)的最大度量值Power。
  10. 如权利要求9所述的定时偏移的处理装置，其中，所述第三获取单元是设置为通过如下方式实现根据所述时域h1(k)序列获取度量序列P(k)：
    根据所述时域h1(k)序列获取用户设备的搜索序列h2(k)；以所述搜索 序列h2(k)的模平方作为所述度量序列P(k)。
  11. 一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行权利要求1～5中任一项所述的方法。
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